emergency department status boards: a case study in information

30
Emergency Department Status Boards: A Case Study in Information Systems Transition Ann M. Bisantz Priyadarshini R. Pennathur University at Buffalo Theresa K. Guarrera Rollin J. Fairbanks University of Rochester Shawna J. Perry Virginia Commonwealth University Frank Zwemer McGuire VA Medical Center Robert L. Wears University of Florida ABSTRACT : Patient status boards play an important role in coordinating and communi- cating about patient care in hospital emergency departments (EDs). Status boards are transitioning from dry-erase whiteboards to electronic systems. Although electronic systems may preserve some surface features of the manual artifacts, important affor- dances of the manual technology are not always maintained. We compared informa- tion on manual and electronic status boards in an ED. Photographs of the manual board and screen shots of the electronic system were obtained before and after a hos- pital transitioned between systems. Displayed information as well as detailed content regarding patient chief complaints, clinical plans, and dispositions were coded and analyzed to understand the type and function of information present, as well as the use of features such color. Results indicated that although categories of information found were similar, the frequency with which some types of information appeared on the two system displays was substantially different. In particular, information used to coordi- nate aspects of patient treatment was more frequently found in the manual system. Results suggest that in the design of new information technologies, simply matching the format or information fields available on an existing system may not be sufficient to sustain current work practices or to prevent unanticipated shifts in use. Introduction AS WITH MANY COMPONENTS OF THE HEALTH CARE SYSTEM, HOSPITAL EMERGENCY DEPART- ments (EDs) are transitioning to computerized information technologies. An impor- tant technological change involves the replacement of manual patient status boards with electronic patient-tracking systems. The successful design of these new systems ADDRESS CORRESPONDENCE TO: Ann Bisantz, Department of Industrial and Systems Engineering, 438 Bell Hall, University at Buffalo, State University of New York, Amherst, NY 14260, [email protected]. Journal of Cognitive Engineering and Decision Making, Volume 4, Number 1, Spring 2010, pp. 39–68. DOI 10.1518/155534310X495582. © 2010 Human Factors and Ergonomics Society. All rights reserved. 39

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Page 1: Emergency Department Status Boards: A Case Study in Information

Emergency Department Status BoardsA Case Study in Information Systems Transition

Ann M BisantzPriyadarshini R PennathurUniversity at BuffaloTheresa K GuarreraRollin J FairbanksUniversity of RochesterShawna J PerryVirginia Commonwealth UniversityFrank ZwemerMcGuire VA Medical CenterRobert L WearsUniversity of Florida

ABSTRACT Patient status boards play an important role in coordinating and communi-

cating about patient care in hospital emergency departments (EDs) Status boards are

transitioning from dry-erase whiteboards to electronic systems Although electronic

systems may preserve some surface features of the manual artifacts important affor-

dances of the manual technology are not always maintained We compared informa-

tion on manual and electronic status boards in an ED Photographs of the manual

board and screen shots of the electronic system were obtained before and after a hos-

pital transitioned between systems Displayed information as well as detailed content

regarding patient chief complaints clinical plans and dispositions were coded and

analyzed to understand the type and function of information present as well as the use

of features such color Results indicated that although categories of information found

were similar the frequency with which some types of information appeared on the two

system displays was substantially different In particular information used to coordi-

nate aspects of patient treatment was more frequently found in the manual system

Results suggest that in the design of new information technologies simply matching

the format or information fields available on an existing system may not be sufficient to

sustain current work practices or to prevent unanticipated shifts in use

Introduction

AS WITH MANY COMPONENTS OF THE HEALTH CARE SYSTEM HOSPITAL EMERGENCY DEPART-ments (EDs) are transitioning to computerized information technologies An impor-tant technological change involves the replacement of manual patient status boardswith electronic patient-tracking systems The successful design of these new systems

ADDRESS CORRESPONDENCE TO Ann Bisantz Department of Industrial and Systems Engineering 438

Bell Hall University at Buffalo State University of New York Amherst NY 14260 bisantzbuffaloedu

Journal of Cognitive Engineering and Decision Making Volume 4 Number 1 Spring 2010 pp 39ndash68

DOI 101518155534310X495582 copy 2010 Human Factors and Ergonomics Society All rights reserved 39

requires a careful understanding of the functions afforded by the old systems andthe manner in which the manual systems supported clinical work

Manual status boards are typically large dry-erase boards that display informa-tion such as patient demographics (eg name age gender) location (eg roombed) caregiver assignments clinical presentation data (eg symptoms diagnoses)and workup plan (eg planned and completed tests and treatments) Informationis typically represented in rows (corresponding to beds to which patients areassigned) and columns (corresponding to a category of information) often usingsymbols and color (see Figure 1) Manual status boards are located in central areasof the ED and are accessible to and used by a variety of caregivers and staff to com-municate information and coordinate individual and group activities

From the standpoint of distributed cognition (Hutchins 1997) status boards serveas a critical cognitive artifact storing and communicating information across time andindividuals in the ED (Nemeth OrsquoConnor Nunnally amp Cook 2007 Pennathuret al 2007 Wears amp Perry 2007 Xiao 2005) For example physicians may use thestatus board to track their own activities in treating and documenting the care of apatient whereas nurses may use them to indicate needs for testing or transportationto other ED staff Status boards support the maintenance of shared situation aware-ness across ED staff and preserve critical information across shift changes (Wears ampPerry 2007) In general these boards support an ED process whereby patients areinitially screened for condition severity when they come to the ED (the triageprocess) are examined by one or more physicians physicians-in-training and med-ical students receive tests and treatments appropriate to their conditions and eitherare admitted to stay in the hospital or leave for home (discharged)

Manual status boards were developed from the ground up over the past three tofour decades by ED practitioners to meet their immediate needs (Wears amp Perry2007) Similar to paper artifacts that co-evolve with an organizationrsquos work practices(Sellen amp Harper 2003) ED status boards developed based on usersrsquo needs andfunctions that the whiteboard medium can support They evolved from a simple listof patients and locations to a rich source of clinical and workflow informationAlthough the basic row-column format is similar across locations the particular for-mat of information representation on status boards is unique and customized to theneeds of caregivers in each hospital setting the boards dynamically represent thestate of the ED in densely encoded idiosyncratic but locally meaningful ways

Interaction with the manual status boards is direct fast and flexible Staff canread portions of the board in detail or get an overview of the level of demand byassessing the overall information density Staff are visible when they gather aroundand mark the whiteboard making it possible for others to notice and infer theiractivities (which may be difficult or impossible to tell when interacting with indi-vidual workstations) Information is primarily entered using markers and includesalphanumeric input as well as hand-drawn symbols and annotations

The status boards are malleable in the sense that they are flexible enough toadapt and support a variety of functions For example in some EDs staff use spe-cially designed prelabeled magnets to provide alerts and may use magnets or tape

40 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 41

Figu

re 1

Man

ual s

tatu

s bo

ard

phot

ogra

ph (n

ames

obs

cure

d) R

epri

nted

from

Pen

nath

ur e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

007

to attach paper forms or test results to the whiteboard (Wears Perry WilsonGalliers amp Fone 2007) Inputs are not restricted to the matrix format but caninclude annotations around the edges of the board or notations that continueacross multiple cells in a row or column Manual whiteboards thus share many ofthe affordances of other manual (paper-based) systems as described by Sellen andHarper (2003) including easy direct marking allowing flexible and ldquotailorablerdquomarkings based on the circumstances providing ldquoinformation at a glancerdquo that issimultaneously available to multiple ED staff and allowing activity to be implicitlycommunicated and coordinated because team members can observe one anotherrsquosactions or the trace of those actions on the status board

Manual to Electronic Status Board TransitionElectronic patient-tracking systems are being implemented as part of an overall

movement to computerize health care information that is driven by anticipatedimprovements in care coordination patient safety and efficiency (Aspden CorriganWolcott amp Erickson 2004 Committee on Quality of Health Care in America 2001Kohn Corrigan amp Donaldson 1999) Generally speaking these boards have beendeveloped by third-party vendors and usually have visual display layouts similarin nature to the whiteboards they have replaced Researchers have noted advan-tages in having a customized electronic tool to support multitasking in ED environ-ments (Laxmisan Hakimzada Sayan Green amp Patel 2007) Electronic systemsmay also address shortcomings of manual status boards Once erased informationcannot be recovered and information entered into one system (eg at hospitalregistration) cannot automatically populate the manual status board Thus repeateddata entry tasks may be required and information may be incomplete outdated orinconsistent across systems Electronic systems are often components of or linked toother hospital information systems and have the ability to log information inputs

Unlike the bottom-up evolutionary design of manual whiteboards the elec-tronic systems are typically purchased from third-party vendors often with onlymodest abilities for customization to reflect the individual uses in each hospital(but see Aronsky Jones Lanaghan amp Slovis 2008 for an example of a ldquohome-grownrdquo electronic system) Procurement is often led by organizational informationtechnology (IT) staff rather than clinicians and can be driven by overall organiza-tional needs and management goals such as system interoperability cost abilityto collect quality and efficiency measures integration with hospital bed manage-ment systems and data storage (Poon et al 2006) These needs may overshadowthose of the clinicians who have been using the manual whiteboard to supporttheir minute-by-minute work

For a variety of economic quality and policy reasons health care providerswill continue to transition to electronic systems Research in a number of settingshas indicated that when systems are designed based on an incorrect or rational-ized model of work performance suffers (Berg 1997 2004 Bisantz amp Ockerman2002 Button amp Harper 1993 Mackay 1999 Sachs 1995) New technology oftencreates a necessity for users to reorient themselves to the electronic system and

42 Journal of Cognitive Engineering and Decision Making Spring 2010

change their existing work practices by altering their tasks and configuring thenew systems In some cases the new technology may increase workload or lead toerrors if users are forced to adapt either the system or their tasks and strategiesduring critical periods (Cook amp Woods 1996) For new technologies to success-fully support or augment evolved work practices designers must start with a deepunderstanding of what functions the manual technologies support

Research ObjectivesIn observing a transition from manual to electronic status boards in two hospi-

tal emergency departments we found that providers reported a negative impact ofthe transition on communication and their ability to make sense of the overallstate of the ED (Pennathur et al 2007) This paper investigates the two technolo-gies in detail to try to identify design-oriented reasons for these difficulties Itcould be simply that the new system does not provide access to record or view thesame type or amount of information as the manual system Alternatively problemscould stem from the format of presentation or method of interaction or the differ-ences in affordances between the two technologies

Whereas other studies have documented aspects of the manual ED white-board technology (Wears amp Perry 2007 Wears et al 2007) these studies did notprovide a detailed comparison of the manual and new systems Thus the goals ofthis study were to document the information content functionality and format ofboth manual and electronic status boards in one particular ED to gain insight intospecific changes (in functionality and availability of information) that occurredduring the transition to the new technology

Methods

Data were collected from manual and electronic systems at a large academicmedical center hospital emergency department which had a patient volume of95000 patients per year Patient-tracking systems were used in multiple func-tional areas (such as adult care trauma and pediatric care) in this ED The EDcompletely transitioned to the computerized patient-tracking system at the timethe system was installed (that is the manual whiteboards were removed once theelectronic system became operational)

Data CollectionA month before the electronic patient-tracking system was implemented

manual status boards in two ED treatment areas were systematically photographedfor their information content Similarly 18 months after the electronic system wasimplemented digital images (screen shots) of the electronic patient-tracking sys-tem were recorded (see Figure 2 for an example) To support the most direct compar-ison we took screen shots of and analyzed only the primary screen of the electronicpatient-tracking display because this display corresponded most closely to the man-ual status board and served as the default ED display We did not analyze addi-tional linked screens in the electronic system or other information sources used

Emergency Department Status Boards in Transition 43

44 Journal of Cognitive Engineering and Decision Making Spring 2010

Figu

re 2

Ele

ctro

nic

stat

us d

ispl

ay s

cree

n sh

ot (n

ames

obs

cure

d) R

epri

nted

from

Fai

rban

ks e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

008

concurrently in the manual system (eg paper charts) Additionally whereas theelectronic system included both desktop and wall-mounted large-format dis-plays the wall-mounted system consistently displayed only the primary screen(scrolling to show all patients)

Data were collected in two distinct areas of the ED the adult acute area whichtreats sick and injured patients requiring urgent or semiurgent treatment (such asheart attacks or strokes) and the adult nonacute area which treats routine nonur-gent cases (such as ankle sprains or minor lacerations) These areas are geographi-cally separated and have separate nurse stations with specifically assigned ED staffIn both cases data were captured every 30 min for continuous 8-hr periods duringa day shift (two different periods for the photographs and one period for thescreen shots because the latter could be accessed from a single remote location)

For the manual system there was a secondary board in the acute area that wasused on some days to track some (but not all) information regarding a small num-ber of ldquooverflowrdquo patients who did not fit on the primary board Typically thesewere less acute patients assigned to overflow locations This board was not pho-tographed because it was not used consistently and because not all data fieldswere represented

In all a total of 68 images (34 photos and 34 screen shots) were captured andedited for patient de-identification Example images from both systems are pro-vided in Figures 1 and 2 Note that the primary organizing scheme for both sys-tems is a matrix format with patients represented in rows (each row correspondingto a bed or location in the ED) and with different kinds of information about thepatient (demographic details assigned caregivers treatment plans) located incolumns Text symbols and colors are used in both systems

AnalysisTwo levels of analysis were conducted by an interdisciplinary research team

composed of emergency medicine physiciansresearchers and human factorsresearchers (authors TG RF AB and PP) For one analysis an overall assessmentof the range of information provided by both systems was conducted by examin-ing the photographs and screen shots We noted the type or function of the infor-mation its location on the whiteboard or screen (eg left side of board nursecolumn) the method of entry (handwritten indicated on a preprinted magnet ortaped or otherwise attached for the manual board typed picked or selected froma list or automatically filled when other entries were made for the electronic board)whether the entry was alphanumeric or symbolic (either hand-drawn or typed)whether there was color or font coding and for the electronic system whether anicon was used whether information could be clicked or selected and whetherhovering with a mouse revealed additional details

The second analysis provided additional details for specific areas of the statusboards We focused on fields that contained significant information related to clinicalcare and workflow specifically columns related to chief complaints and those relatedto patient treatment and disposition The chief complaint provides information about

Emergency Department Status Boards in Transition 45

the primary reason a patient has come to the emergency department as providedby patients to nurses during the triage process in which the criticality of patientsrsquocondition is assessed

Disposition is a term commonly used in emergency medicine to describe thepatientrsquos destination once the ED care has been completed and might include hospi-tal admission transfer to another hospital or discharge to home These areas weretranscribed into spreadsheets (maintaining the use of symbols text color etc) andcoded by the research team Columns between the two systems did not alwaysdirectly correspond For example the column labeled Disposition on the manualwhiteboard contained (among other things) clinical orders and disposition informa-tion regarding the patient On the electronic status board there were three columnsrelated to these functions two columns with alphanumericcolored codes (labeledCustom and Disposition) and one column that accepted free text or click-and-selecttext entries (labeled Comments) Thus all three columns were coded in the lattercase to allow comparison with the disposition column on the manual board

Codes were developed iteratively during the analysis using a grounded-theoryapproach (Glaser amp Strauss 1967) and represented the different functions thatthe information present on the status boards could provide Because coding wasperformed by group consensus we did not compute interrater reliability statisticsIn analyzing and categorizing the information we also computed quantitativeindicators to understand the differences between the electronic and the manualwhiteboard Each photograph or screen shot contained information about multi-ple patients and because images were obtained across a continuous time spaninformation about a particular patient typically appeared in multiple images Wecombined entries for each patient when evaluating the frequency of coded entriesso that identical information was counted only a single time for each patient

The columns we coded could contain multiple pieces of information for a sin-gle patient These were analyzed separately as they could represent different cate-gories of information Figure 3 shows two chief complaint entries associated with asingle patient The chief complaint entry changed over time (between two photo-graphs) Four different chief complaint functions were coded for this entry ldquocar vsdeerrdquo indicated the mechanism of injury ldquoL arm injuryrdquo represents the problem(injury) location of the problem (arm) and laterality (LLeft) Similarly in the com-ments column (electronic system) the entry ldquoGET EKG EKG DONErdquo contains twodisposition functions ldquoclinical workup planrdquo and ldquoplan progressrdquo That is a plan

46 Journal of Cognitive Engineering and Decision Making Spring 2010

Figure 3 Example of transcribed chief complaint data

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

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Location Outside of Matrix Form

Marker (handwritten)

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Typed

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StickiesNotepad

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Actionable

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Emergency Department Status Boards in Transition 49

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50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

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ue

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nu

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ctro

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Location Outside of Matrix Form

Marker (handwritten)

Magnet

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Automatically Filled

AlphanumericKBD Symbol

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PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

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Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

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yx

xB

ed

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typ

e

of

com

me

nt)

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ly if

th

e

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st r

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nt

com

me

nt

an

d it

wa

s p

ick-

sele

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d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

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d

33

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00

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02

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Inp

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en

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ign

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re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

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f ldquoC

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eck

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MR

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93

0rdquo

95

39

03

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wo

rku

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lab

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(pa

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ing

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r M

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t 6

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PM

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nti

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ed n

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ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

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Fre

qu

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cy

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te p

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rt C

Trdquo

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T)

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isp

osi

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nd

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mm

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ts e

ntr

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to

tale

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th

e T

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lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 2: Emergency Department Status Boards: A Case Study in Information

requires a careful understanding of the functions afforded by the old systems andthe manner in which the manual systems supported clinical work

Manual status boards are typically large dry-erase boards that display informa-tion such as patient demographics (eg name age gender) location (eg roombed) caregiver assignments clinical presentation data (eg symptoms diagnoses)and workup plan (eg planned and completed tests and treatments) Informationis typically represented in rows (corresponding to beds to which patients areassigned) and columns (corresponding to a category of information) often usingsymbols and color (see Figure 1) Manual status boards are located in central areasof the ED and are accessible to and used by a variety of caregivers and staff to com-municate information and coordinate individual and group activities

From the standpoint of distributed cognition (Hutchins 1997) status boards serveas a critical cognitive artifact storing and communicating information across time andindividuals in the ED (Nemeth OrsquoConnor Nunnally amp Cook 2007 Pennathuret al 2007 Wears amp Perry 2007 Xiao 2005) For example physicians may use thestatus board to track their own activities in treating and documenting the care of apatient whereas nurses may use them to indicate needs for testing or transportationto other ED staff Status boards support the maintenance of shared situation aware-ness across ED staff and preserve critical information across shift changes (Wears ampPerry 2007) In general these boards support an ED process whereby patients areinitially screened for condition severity when they come to the ED (the triageprocess) are examined by one or more physicians physicians-in-training and med-ical students receive tests and treatments appropriate to their conditions and eitherare admitted to stay in the hospital or leave for home (discharged)

Manual status boards were developed from the ground up over the past three tofour decades by ED practitioners to meet their immediate needs (Wears amp Perry2007) Similar to paper artifacts that co-evolve with an organizationrsquos work practices(Sellen amp Harper 2003) ED status boards developed based on usersrsquo needs andfunctions that the whiteboard medium can support They evolved from a simple listof patients and locations to a rich source of clinical and workflow informationAlthough the basic row-column format is similar across locations the particular for-mat of information representation on status boards is unique and customized to theneeds of caregivers in each hospital setting the boards dynamically represent thestate of the ED in densely encoded idiosyncratic but locally meaningful ways

Interaction with the manual status boards is direct fast and flexible Staff canread portions of the board in detail or get an overview of the level of demand byassessing the overall information density Staff are visible when they gather aroundand mark the whiteboard making it possible for others to notice and infer theiractivities (which may be difficult or impossible to tell when interacting with indi-vidual workstations) Information is primarily entered using markers and includesalphanumeric input as well as hand-drawn symbols and annotations

The status boards are malleable in the sense that they are flexible enough toadapt and support a variety of functions For example in some EDs staff use spe-cially designed prelabeled magnets to provide alerts and may use magnets or tape

40 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 41

Figu

re 1

Man

ual s

tatu

s bo

ard

phot

ogra

ph (n

ames

obs

cure

d) R

epri

nted

from

Pen

nath

ur e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

007

to attach paper forms or test results to the whiteboard (Wears Perry WilsonGalliers amp Fone 2007) Inputs are not restricted to the matrix format but caninclude annotations around the edges of the board or notations that continueacross multiple cells in a row or column Manual whiteboards thus share many ofthe affordances of other manual (paper-based) systems as described by Sellen andHarper (2003) including easy direct marking allowing flexible and ldquotailorablerdquomarkings based on the circumstances providing ldquoinformation at a glancerdquo that issimultaneously available to multiple ED staff and allowing activity to be implicitlycommunicated and coordinated because team members can observe one anotherrsquosactions or the trace of those actions on the status board

Manual to Electronic Status Board TransitionElectronic patient-tracking systems are being implemented as part of an overall

movement to computerize health care information that is driven by anticipatedimprovements in care coordination patient safety and efficiency (Aspden CorriganWolcott amp Erickson 2004 Committee on Quality of Health Care in America 2001Kohn Corrigan amp Donaldson 1999) Generally speaking these boards have beendeveloped by third-party vendors and usually have visual display layouts similarin nature to the whiteboards they have replaced Researchers have noted advan-tages in having a customized electronic tool to support multitasking in ED environ-ments (Laxmisan Hakimzada Sayan Green amp Patel 2007) Electronic systemsmay also address shortcomings of manual status boards Once erased informationcannot be recovered and information entered into one system (eg at hospitalregistration) cannot automatically populate the manual status board Thus repeateddata entry tasks may be required and information may be incomplete outdated orinconsistent across systems Electronic systems are often components of or linked toother hospital information systems and have the ability to log information inputs

Unlike the bottom-up evolutionary design of manual whiteboards the elec-tronic systems are typically purchased from third-party vendors often with onlymodest abilities for customization to reflect the individual uses in each hospital(but see Aronsky Jones Lanaghan amp Slovis 2008 for an example of a ldquohome-grownrdquo electronic system) Procurement is often led by organizational informationtechnology (IT) staff rather than clinicians and can be driven by overall organiza-tional needs and management goals such as system interoperability cost abilityto collect quality and efficiency measures integration with hospital bed manage-ment systems and data storage (Poon et al 2006) These needs may overshadowthose of the clinicians who have been using the manual whiteboard to supporttheir minute-by-minute work

For a variety of economic quality and policy reasons health care providerswill continue to transition to electronic systems Research in a number of settingshas indicated that when systems are designed based on an incorrect or rational-ized model of work performance suffers (Berg 1997 2004 Bisantz amp Ockerman2002 Button amp Harper 1993 Mackay 1999 Sachs 1995) New technology oftencreates a necessity for users to reorient themselves to the electronic system and

42 Journal of Cognitive Engineering and Decision Making Spring 2010

change their existing work practices by altering their tasks and configuring thenew systems In some cases the new technology may increase workload or lead toerrors if users are forced to adapt either the system or their tasks and strategiesduring critical periods (Cook amp Woods 1996) For new technologies to success-fully support or augment evolved work practices designers must start with a deepunderstanding of what functions the manual technologies support

Research ObjectivesIn observing a transition from manual to electronic status boards in two hospi-

tal emergency departments we found that providers reported a negative impact ofthe transition on communication and their ability to make sense of the overallstate of the ED (Pennathur et al 2007) This paper investigates the two technolo-gies in detail to try to identify design-oriented reasons for these difficulties Itcould be simply that the new system does not provide access to record or view thesame type or amount of information as the manual system Alternatively problemscould stem from the format of presentation or method of interaction or the differ-ences in affordances between the two technologies

Whereas other studies have documented aspects of the manual ED white-board technology (Wears amp Perry 2007 Wears et al 2007) these studies did notprovide a detailed comparison of the manual and new systems Thus the goals ofthis study were to document the information content functionality and format ofboth manual and electronic status boards in one particular ED to gain insight intospecific changes (in functionality and availability of information) that occurredduring the transition to the new technology

Methods

Data were collected from manual and electronic systems at a large academicmedical center hospital emergency department which had a patient volume of95000 patients per year Patient-tracking systems were used in multiple func-tional areas (such as adult care trauma and pediatric care) in this ED The EDcompletely transitioned to the computerized patient-tracking system at the timethe system was installed (that is the manual whiteboards were removed once theelectronic system became operational)

Data CollectionA month before the electronic patient-tracking system was implemented

manual status boards in two ED treatment areas were systematically photographedfor their information content Similarly 18 months after the electronic system wasimplemented digital images (screen shots) of the electronic patient-tracking sys-tem were recorded (see Figure 2 for an example) To support the most direct compar-ison we took screen shots of and analyzed only the primary screen of the electronicpatient-tracking display because this display corresponded most closely to the man-ual status board and served as the default ED display We did not analyze addi-tional linked screens in the electronic system or other information sources used

Emergency Department Status Boards in Transition 43

44 Journal of Cognitive Engineering and Decision Making Spring 2010

Figu

re 2

Ele

ctro

nic

stat

us d

ispl

ay s

cree

n sh

ot (n

ames

obs

cure

d) R

epri

nted

from

Fai

rban

ks e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

008

concurrently in the manual system (eg paper charts) Additionally whereas theelectronic system included both desktop and wall-mounted large-format dis-plays the wall-mounted system consistently displayed only the primary screen(scrolling to show all patients)

Data were collected in two distinct areas of the ED the adult acute area whichtreats sick and injured patients requiring urgent or semiurgent treatment (such asheart attacks or strokes) and the adult nonacute area which treats routine nonur-gent cases (such as ankle sprains or minor lacerations) These areas are geographi-cally separated and have separate nurse stations with specifically assigned ED staffIn both cases data were captured every 30 min for continuous 8-hr periods duringa day shift (two different periods for the photographs and one period for thescreen shots because the latter could be accessed from a single remote location)

For the manual system there was a secondary board in the acute area that wasused on some days to track some (but not all) information regarding a small num-ber of ldquooverflowrdquo patients who did not fit on the primary board Typically thesewere less acute patients assigned to overflow locations This board was not pho-tographed because it was not used consistently and because not all data fieldswere represented

In all a total of 68 images (34 photos and 34 screen shots) were captured andedited for patient de-identification Example images from both systems are pro-vided in Figures 1 and 2 Note that the primary organizing scheme for both sys-tems is a matrix format with patients represented in rows (each row correspondingto a bed or location in the ED) and with different kinds of information about thepatient (demographic details assigned caregivers treatment plans) located incolumns Text symbols and colors are used in both systems

AnalysisTwo levels of analysis were conducted by an interdisciplinary research team

composed of emergency medicine physiciansresearchers and human factorsresearchers (authors TG RF AB and PP) For one analysis an overall assessmentof the range of information provided by both systems was conducted by examin-ing the photographs and screen shots We noted the type or function of the infor-mation its location on the whiteboard or screen (eg left side of board nursecolumn) the method of entry (handwritten indicated on a preprinted magnet ortaped or otherwise attached for the manual board typed picked or selected froma list or automatically filled when other entries were made for the electronic board)whether the entry was alphanumeric or symbolic (either hand-drawn or typed)whether there was color or font coding and for the electronic system whether anicon was used whether information could be clicked or selected and whetherhovering with a mouse revealed additional details

The second analysis provided additional details for specific areas of the statusboards We focused on fields that contained significant information related to clinicalcare and workflow specifically columns related to chief complaints and those relatedto patient treatment and disposition The chief complaint provides information about

Emergency Department Status Boards in Transition 45

the primary reason a patient has come to the emergency department as providedby patients to nurses during the triage process in which the criticality of patientsrsquocondition is assessed

Disposition is a term commonly used in emergency medicine to describe thepatientrsquos destination once the ED care has been completed and might include hospi-tal admission transfer to another hospital or discharge to home These areas weretranscribed into spreadsheets (maintaining the use of symbols text color etc) andcoded by the research team Columns between the two systems did not alwaysdirectly correspond For example the column labeled Disposition on the manualwhiteboard contained (among other things) clinical orders and disposition informa-tion regarding the patient On the electronic status board there were three columnsrelated to these functions two columns with alphanumericcolored codes (labeledCustom and Disposition) and one column that accepted free text or click-and-selecttext entries (labeled Comments) Thus all three columns were coded in the lattercase to allow comparison with the disposition column on the manual board

Codes were developed iteratively during the analysis using a grounded-theoryapproach (Glaser amp Strauss 1967) and represented the different functions thatthe information present on the status boards could provide Because coding wasperformed by group consensus we did not compute interrater reliability statisticsIn analyzing and categorizing the information we also computed quantitativeindicators to understand the differences between the electronic and the manualwhiteboard Each photograph or screen shot contained information about multi-ple patients and because images were obtained across a continuous time spaninformation about a particular patient typically appeared in multiple images Wecombined entries for each patient when evaluating the frequency of coded entriesso that identical information was counted only a single time for each patient

The columns we coded could contain multiple pieces of information for a sin-gle patient These were analyzed separately as they could represent different cate-gories of information Figure 3 shows two chief complaint entries associated with asingle patient The chief complaint entry changed over time (between two photo-graphs) Four different chief complaint functions were coded for this entry ldquocar vsdeerrdquo indicated the mechanism of injury ldquoL arm injuryrdquo represents the problem(injury) location of the problem (arm) and laterality (LLeft) Similarly in the com-ments column (electronic system) the entry ldquoGET EKG EKG DONErdquo contains twodisposition functions ldquoclinical workup planrdquo and ldquoplan progressrdquo That is a plan

46 Journal of Cognitive Engineering and Decision Making Spring 2010

Figure 3 Example of transcribed chief complaint data

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 T

ype

s o

f In

form

ati

on

Re

pre

sen

ted

on

th

e M

an

ua

l an

do

r E

lect

ron

ic S

tatu

s D

isp

lay

Alo

ng

Wit

h M

eth

od

of

Info

rma

tio

n E

ntr

y

or

Dis

pla

y a

nd

Cla

rify

ing

No

tes

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Att

en

din

g p

hys

icia

nrsquos

x

xS

pe

cifi

c to

ph

ysic

ian

wo

rkfl

ow

sym

bo

ls

ind

ica

tin

g p

rog

ress

wit

h p

ati

en

t

Be

d r

ea

ssig

nm

en

t p

lan

x

xx

Loca

ted

to

th

e le

ft o

f th

e

cha

ng

ing

th

e w

ritt

en

m

atr

ix

roo

m n

um

be

r o

r st

icke

r

ED

ph

arm

aci

st o

no

ff d

uty

xx

xO

n d

uty

(gre

en

) o

ff d

uty

(re

d)

loca

ted

on

to

p o

f

the

bo

ard

Pat

ien

t is

pe

dia

tric

xP

atie

nt

nam

e w

ritt

en

in r

ed

Re

sid

en

t p

hys

icia

nrsquos

x

xx

Sp

eci

fic

to r

esi

de

nt

wo

rkfl

ow

sym

bo

ls

ind

ica

tin

g p

rog

ress

wit

h p

ati

en

t

Ro

om

is s

tock

ed

wit

h

xH

an

d-d

raw

n d

ot

ne

xt t

o

sup

plie

s ro

om

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 49

Ro

om

sa

ve

d f

or

pa

rtic

ula

r x

xx

Eg

ldquoS

av

e f

or

Gyn

rdquo

tre

atm

en

ts

Sh

ift

of

pa

tie

nt

arr

iva

lx

Pa

tie

nt

info

rma

tio

n

wri

tte

n in

sa

me

co

lor

thro

ug

ho

ut

a s

hif

t

ldquoold

er

colo

rsrdquo

sig

nif

y

lon

ge

r-d

ura

tio

n

pa

tie

nts

Tim

e (h

ou

r) t

ha

t n

ext

vit

als

x

x

sho

uld

be

ta

ken

Tim

e p

ati

en

t a

rriv

ed

at

xx

tria

ge

Tim

e p

ati

en

t m

ov

ed

fro

m

xx

wa

itin

g r

oo

m t

o b

ed

in E

D

Ch

ief

com

pla

int

wit

h

xb

ar

xH

igh

-ris

k ch

ief

com

pla

ints

po

ten

tia

l ris

k o

r (r

ed

ba

r to

left

of

cell)

qu

alit

y m

ea

sure

qu

alit

y m

ea

sure

(gre

en

ba

r) p

rese

nt

on

ly if

com

pla

int

wa

s

pic

k-se

lect

ed

Dia

gn

osi

s in

form

ati

on

x

xx

Blu

e le

tte

r D

en

tere

d e

lse

wh

ere

in t

he

sys

tem

Dis

po

siti

on

scr

ee

n a

cce

ssx

ba

rx

Co

lore

d b

ar

to le

ft o

f ce

ll

(gre

en

if ldquo

En

terrdquo

clic

ked

on

Dis

po

siti

on

scr

ee

n)

Flo

w s

he

et

info

rma

tio

n

xx

xLe

tte

r F

(vit

al s

ign

s) is

av

aila

ble

(ab

sen

ce o

f in

dic

ato

r

do

es

no

t in

dic

ate

ab

sen

ce o

f fl

ow

sh

ee

t)

Len

gth

-of-

sta

y a

lert

xx

xx

A c

olo

red

clo

ck ic

on

gre

en

if L

OS

lt 6

hr

red

oth

erw

ise

Co

nti

nu

ed n

ext p

ag

e

50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Len

gth

of

sta

y t

ime

sin

ce

xx

x

pa

tie

ntrsquo

s in

form

ati

on

en

tere

d a

t tr

iag

e

Mo

st r

ece

nt

pa

tie

nt

xx

Ast

eri

sks

ma

rk p

ati

en

t

acc

ess

ed

th

at

the

use

r la

st

acc

ess

ed

in s

yste

m

Pa

tie

nt

care

d f

or

by

no

n-E

D

xx

xx

OB

SB

RD

or

INP

TB

RD

tea

m (b

oa

rdin

g o

r d

isp

laye

d in

a b

lue

lab

el

ad

mit

ted

) in

dic

ate

s b

elo

w t

he

be

d n

am

e

pa

tie

nt

no

lon

ge

r in

ca

re

AD

MT

or

INP

T

of

ED

ph

ysic

ian

dis

pla

yed

inst

ea

d o

f

att

en

din

g p

hys

icia

n

na

me

Act

ion

ab

le o

r

Ho

ve

r ca

teg

ori

es

ap

ply

on

ly t

o A

DM

T o

r IN

PT

Pa

tie

nt

info

rma

tio

n c

alle

d

xx

xP

ho

ne

ico

n

in b

y p

rim

ary

ph

ysic

ian

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

ed

ce

ll w

as

red

ora

ng

e

yello

w g

ree

n b

lue

or

gra

y (i

f n

o a

cuit

y

sele

cte

d)

Typ

e o

f co

mm

en

tx

ba

rx

Re

d g

ree

n y

ello

w p

urp

le

gra

y b

lue

co

lore

d b

ar

to le

ft o

f co

mm

en

t ce

ll

(co

rre

spo

nd

ing

to

typ

e

of

com

me

nt)

on

ly if

th

e

mo

st r

ece

nt

com

me

nt

an

d it

wa

s p

ick-

sele

cte

d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

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um

be

r 1

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2)

Te

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lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

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re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

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00

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ue

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tra

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ort

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a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

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T)

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sto

m D

isp

osi

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nd

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ies

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e T

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n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 3: Emergency Department Status Boards: A Case Study in Information

Emergency Department Status Boards in Transition 41

Figu

re 1

Man

ual s

tatu

s bo

ard

phot

ogra

ph (n

ames

obs

cure

d) R

epri

nted

from

Pen

nath

ur e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

007

to attach paper forms or test results to the whiteboard (Wears Perry WilsonGalliers amp Fone 2007) Inputs are not restricted to the matrix format but caninclude annotations around the edges of the board or notations that continueacross multiple cells in a row or column Manual whiteboards thus share many ofthe affordances of other manual (paper-based) systems as described by Sellen andHarper (2003) including easy direct marking allowing flexible and ldquotailorablerdquomarkings based on the circumstances providing ldquoinformation at a glancerdquo that issimultaneously available to multiple ED staff and allowing activity to be implicitlycommunicated and coordinated because team members can observe one anotherrsquosactions or the trace of those actions on the status board

Manual to Electronic Status Board TransitionElectronic patient-tracking systems are being implemented as part of an overall

movement to computerize health care information that is driven by anticipatedimprovements in care coordination patient safety and efficiency (Aspden CorriganWolcott amp Erickson 2004 Committee on Quality of Health Care in America 2001Kohn Corrigan amp Donaldson 1999) Generally speaking these boards have beendeveloped by third-party vendors and usually have visual display layouts similarin nature to the whiteboards they have replaced Researchers have noted advan-tages in having a customized electronic tool to support multitasking in ED environ-ments (Laxmisan Hakimzada Sayan Green amp Patel 2007) Electronic systemsmay also address shortcomings of manual status boards Once erased informationcannot be recovered and information entered into one system (eg at hospitalregistration) cannot automatically populate the manual status board Thus repeateddata entry tasks may be required and information may be incomplete outdated orinconsistent across systems Electronic systems are often components of or linked toother hospital information systems and have the ability to log information inputs

Unlike the bottom-up evolutionary design of manual whiteboards the elec-tronic systems are typically purchased from third-party vendors often with onlymodest abilities for customization to reflect the individual uses in each hospital(but see Aronsky Jones Lanaghan amp Slovis 2008 for an example of a ldquohome-grownrdquo electronic system) Procurement is often led by organizational informationtechnology (IT) staff rather than clinicians and can be driven by overall organiza-tional needs and management goals such as system interoperability cost abilityto collect quality and efficiency measures integration with hospital bed manage-ment systems and data storage (Poon et al 2006) These needs may overshadowthose of the clinicians who have been using the manual whiteboard to supporttheir minute-by-minute work

For a variety of economic quality and policy reasons health care providerswill continue to transition to electronic systems Research in a number of settingshas indicated that when systems are designed based on an incorrect or rational-ized model of work performance suffers (Berg 1997 2004 Bisantz amp Ockerman2002 Button amp Harper 1993 Mackay 1999 Sachs 1995) New technology oftencreates a necessity for users to reorient themselves to the electronic system and

42 Journal of Cognitive Engineering and Decision Making Spring 2010

change their existing work practices by altering their tasks and configuring thenew systems In some cases the new technology may increase workload or lead toerrors if users are forced to adapt either the system or their tasks and strategiesduring critical periods (Cook amp Woods 1996) For new technologies to success-fully support or augment evolved work practices designers must start with a deepunderstanding of what functions the manual technologies support

Research ObjectivesIn observing a transition from manual to electronic status boards in two hospi-

tal emergency departments we found that providers reported a negative impact ofthe transition on communication and their ability to make sense of the overallstate of the ED (Pennathur et al 2007) This paper investigates the two technolo-gies in detail to try to identify design-oriented reasons for these difficulties Itcould be simply that the new system does not provide access to record or view thesame type or amount of information as the manual system Alternatively problemscould stem from the format of presentation or method of interaction or the differ-ences in affordances between the two technologies

Whereas other studies have documented aspects of the manual ED white-board technology (Wears amp Perry 2007 Wears et al 2007) these studies did notprovide a detailed comparison of the manual and new systems Thus the goals ofthis study were to document the information content functionality and format ofboth manual and electronic status boards in one particular ED to gain insight intospecific changes (in functionality and availability of information) that occurredduring the transition to the new technology

Methods

Data were collected from manual and electronic systems at a large academicmedical center hospital emergency department which had a patient volume of95000 patients per year Patient-tracking systems were used in multiple func-tional areas (such as adult care trauma and pediatric care) in this ED The EDcompletely transitioned to the computerized patient-tracking system at the timethe system was installed (that is the manual whiteboards were removed once theelectronic system became operational)

Data CollectionA month before the electronic patient-tracking system was implemented

manual status boards in two ED treatment areas were systematically photographedfor their information content Similarly 18 months after the electronic system wasimplemented digital images (screen shots) of the electronic patient-tracking sys-tem were recorded (see Figure 2 for an example) To support the most direct compar-ison we took screen shots of and analyzed only the primary screen of the electronicpatient-tracking display because this display corresponded most closely to the man-ual status board and served as the default ED display We did not analyze addi-tional linked screens in the electronic system or other information sources used

Emergency Department Status Boards in Transition 43

44 Journal of Cognitive Engineering and Decision Making Spring 2010

Figu

re 2

Ele

ctro

nic

stat

us d

ispl

ay s

cree

n sh

ot (n

ames

obs

cure

d) R

epri

nted

from

Fai

rban

ks e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

008

concurrently in the manual system (eg paper charts) Additionally whereas theelectronic system included both desktop and wall-mounted large-format dis-plays the wall-mounted system consistently displayed only the primary screen(scrolling to show all patients)

Data were collected in two distinct areas of the ED the adult acute area whichtreats sick and injured patients requiring urgent or semiurgent treatment (such asheart attacks or strokes) and the adult nonacute area which treats routine nonur-gent cases (such as ankle sprains or minor lacerations) These areas are geographi-cally separated and have separate nurse stations with specifically assigned ED staffIn both cases data were captured every 30 min for continuous 8-hr periods duringa day shift (two different periods for the photographs and one period for thescreen shots because the latter could be accessed from a single remote location)

For the manual system there was a secondary board in the acute area that wasused on some days to track some (but not all) information regarding a small num-ber of ldquooverflowrdquo patients who did not fit on the primary board Typically thesewere less acute patients assigned to overflow locations This board was not pho-tographed because it was not used consistently and because not all data fieldswere represented

In all a total of 68 images (34 photos and 34 screen shots) were captured andedited for patient de-identification Example images from both systems are pro-vided in Figures 1 and 2 Note that the primary organizing scheme for both sys-tems is a matrix format with patients represented in rows (each row correspondingto a bed or location in the ED) and with different kinds of information about thepatient (demographic details assigned caregivers treatment plans) located incolumns Text symbols and colors are used in both systems

AnalysisTwo levels of analysis were conducted by an interdisciplinary research team

composed of emergency medicine physiciansresearchers and human factorsresearchers (authors TG RF AB and PP) For one analysis an overall assessmentof the range of information provided by both systems was conducted by examin-ing the photographs and screen shots We noted the type or function of the infor-mation its location on the whiteboard or screen (eg left side of board nursecolumn) the method of entry (handwritten indicated on a preprinted magnet ortaped or otherwise attached for the manual board typed picked or selected froma list or automatically filled when other entries were made for the electronic board)whether the entry was alphanumeric or symbolic (either hand-drawn or typed)whether there was color or font coding and for the electronic system whether anicon was used whether information could be clicked or selected and whetherhovering with a mouse revealed additional details

The second analysis provided additional details for specific areas of the statusboards We focused on fields that contained significant information related to clinicalcare and workflow specifically columns related to chief complaints and those relatedto patient treatment and disposition The chief complaint provides information about

Emergency Department Status Boards in Transition 45

the primary reason a patient has come to the emergency department as providedby patients to nurses during the triage process in which the criticality of patientsrsquocondition is assessed

Disposition is a term commonly used in emergency medicine to describe thepatientrsquos destination once the ED care has been completed and might include hospi-tal admission transfer to another hospital or discharge to home These areas weretranscribed into spreadsheets (maintaining the use of symbols text color etc) andcoded by the research team Columns between the two systems did not alwaysdirectly correspond For example the column labeled Disposition on the manualwhiteboard contained (among other things) clinical orders and disposition informa-tion regarding the patient On the electronic status board there were three columnsrelated to these functions two columns with alphanumericcolored codes (labeledCustom and Disposition) and one column that accepted free text or click-and-selecttext entries (labeled Comments) Thus all three columns were coded in the lattercase to allow comparison with the disposition column on the manual board

Codes were developed iteratively during the analysis using a grounded-theoryapproach (Glaser amp Strauss 1967) and represented the different functions thatthe information present on the status boards could provide Because coding wasperformed by group consensus we did not compute interrater reliability statisticsIn analyzing and categorizing the information we also computed quantitativeindicators to understand the differences between the electronic and the manualwhiteboard Each photograph or screen shot contained information about multi-ple patients and because images were obtained across a continuous time spaninformation about a particular patient typically appeared in multiple images Wecombined entries for each patient when evaluating the frequency of coded entriesso that identical information was counted only a single time for each patient

The columns we coded could contain multiple pieces of information for a sin-gle patient These were analyzed separately as they could represent different cate-gories of information Figure 3 shows two chief complaint entries associated with asingle patient The chief complaint entry changed over time (between two photo-graphs) Four different chief complaint functions were coded for this entry ldquocar vsdeerrdquo indicated the mechanism of injury ldquoL arm injuryrdquo represents the problem(injury) location of the problem (arm) and laterality (LLeft) Similarly in the com-ments column (electronic system) the entry ldquoGET EKG EKG DONErdquo contains twodisposition functions ldquoclinical workup planrdquo and ldquoplan progressrdquo That is a plan

46 Journal of Cognitive Engineering and Decision Making Spring 2010

Figure 3 Example of transcribed chief complaint data

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 T

ype

s o

f In

form

ati

on

Re

pre

sen

ted

on

th

e M

an

ua

l an

do

r E

lect

ron

ic S

tatu

s D

isp

lay

Alo

ng

Wit

h M

eth

od

of

Info

rma

tio

n E

ntr

y

or

Dis

pla

y a

nd

Cla

rify

ing

No

tes

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Att

en

din

g p

hys

icia

nrsquos

x

xS

pe

cifi

c to

ph

ysic

ian

wo

rkfl

ow

sym

bo

ls

ind

ica

tin

g p

rog

ress

wit

h p

ati

en

t

Be

d r

ea

ssig

nm

en

t p

lan

x

xx

Loca

ted

to

th

e le

ft o

f th

e

cha

ng

ing

th

e w

ritt

en

m

atr

ix

roo

m n

um

be

r o

r st

icke

r

ED

ph

arm

aci

st o

no

ff d

uty

xx

xO

n d

uty

(gre

en

) o

ff d

uty

(re

d)

loca

ted

on

to

p o

f

the

bo

ard

Pat

ien

t is

pe

dia

tric

xP

atie

nt

nam

e w

ritt

en

in r

ed

Re

sid

en

t p

hys

icia

nrsquos

x

xx

Sp

eci

fic

to r

esi

de

nt

wo

rkfl

ow

sym

bo

ls

ind

ica

tin

g p

rog

ress

wit

h p

ati

en

t

Ro

om

is s

tock

ed

wit

h

xH

an

d-d

raw

n d

ot

ne

xt t

o

sup

plie

s ro

om

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 49

Ro

om

sa

ve

d f

or

pa

rtic

ula

r x

xx

Eg

ldquoS

av

e f

or

Gyn

rdquo

tre

atm

en

ts

Sh

ift

of

pa

tie

nt

arr

iva

lx

Pa

tie

nt

info

rma

tio

n

wri

tte

n in

sa

me

co

lor

thro

ug

ho

ut

a s

hif

t

ldquoold

er

colo

rsrdquo

sig

nif

y

lon

ge

r-d

ura

tio

n

pa

tie

nts

Tim

e (h

ou

r) t

ha

t n

ext

vit

als

x

x

sho

uld

be

ta

ken

Tim

e p

ati

en

t a

rriv

ed

at

xx

tria

ge

Tim

e p

ati

en

t m

ov

ed

fro

m

xx

wa

itin

g r

oo

m t

o b

ed

in E

D

Ch

ief

com

pla

int

wit

h

xb

ar

xH

igh

-ris

k ch

ief

com

pla

ints

po

ten

tia

l ris

k o

r (r

ed

ba

r to

left

of

cell)

qu

alit

y m

ea

sure

qu

alit

y m

ea

sure

(gre

en

ba

r) p

rese

nt

on

ly if

com

pla

int

wa

s

pic

k-se

lect

ed

Dia

gn

osi

s in

form

ati

on

x

xx

Blu

e le

tte

r D

en

tere

d e

lse

wh

ere

in t

he

sys

tem

Dis

po

siti

on

scr

ee

n a

cce

ssx

ba

rx

Co

lore

d b

ar

to le

ft o

f ce

ll

(gre

en

if ldquo

En

terrdquo

clic

ked

on

Dis

po

siti

on

scr

ee

n)

Flo

w s

he

et

info

rma

tio

n

xx

xLe

tte

r F

(vit

al s

ign

s) is

av

aila

ble

(ab

sen

ce o

f in

dic

ato

r

do

es

no

t in

dic

ate

ab

sen

ce o

f fl

ow

sh

ee

t)

Len

gth

-of-

sta

y a

lert

xx

xx

A c

olo

red

clo

ck ic

on

gre

en

if L

OS

lt 6

hr

red

oth

erw

ise

Co

nti

nu

ed n

ext p

ag

e

50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Len

gth

of

sta

y t

ime

sin

ce

xx

x

pa

tie

ntrsquo

s in

form

ati

on

en

tere

d a

t tr

iag

e

Mo

st r

ece

nt

pa

tie

nt

xx

Ast

eri

sks

ma

rk p

ati

en

t

acc

ess

ed

th

at

the

use

r la

st

acc

ess

ed

in s

yste

m

Pa

tie

nt

care

d f

or

by

no

n-E

D

xx

xx

OB

SB

RD

or

INP

TB

RD

tea

m (b

oa

rdin

g o

r d

isp

laye

d in

a b

lue

lab

el

ad

mit

ted

) in

dic

ate

s b

elo

w t

he

be

d n

am

e

pa

tie

nt

no

lon

ge

r in

ca

re

AD

MT

or

INP

T

of

ED

ph

ysic

ian

dis

pla

yed

inst

ea

d o

f

att

en

din

g p

hys

icia

n

na

me

Act

ion

ab

le o

r

Ho

ve

r ca

teg

ori

es

ap

ply

on

ly t

o A

DM

T o

r IN

PT

Pa

tie

nt

info

rma

tio

n c

alle

d

xx

xP

ho

ne

ico

n

in b

y p

rim

ary

ph

ysic

ian

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

ed

ce

ll w

as

red

ora

ng

e

yello

w g

ree

n b

lue

or

gra

y (i

f n

o a

cuit

y

sele

cte

d)

Typ

e o

f co

mm

en

tx

ba

rx

Re

d g

ree

n y

ello

w p

urp

le

gra

y b

lue

co

lore

d b

ar

to le

ft o

f co

mm

en

t ce

ll

(co

rre

spo

nd

ing

to

typ

e

of

com

me

nt)

on

ly if

th

e

mo

st r

ece

nt

com

me

nt

an

d it

wa

s p

ick-

sele

cte

d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 4: Emergency Department Status Boards: A Case Study in Information

to attach paper forms or test results to the whiteboard (Wears Perry WilsonGalliers amp Fone 2007) Inputs are not restricted to the matrix format but caninclude annotations around the edges of the board or notations that continueacross multiple cells in a row or column Manual whiteboards thus share many ofthe affordances of other manual (paper-based) systems as described by Sellen andHarper (2003) including easy direct marking allowing flexible and ldquotailorablerdquomarkings based on the circumstances providing ldquoinformation at a glancerdquo that issimultaneously available to multiple ED staff and allowing activity to be implicitlycommunicated and coordinated because team members can observe one anotherrsquosactions or the trace of those actions on the status board

Manual to Electronic Status Board TransitionElectronic patient-tracking systems are being implemented as part of an overall

movement to computerize health care information that is driven by anticipatedimprovements in care coordination patient safety and efficiency (Aspden CorriganWolcott amp Erickson 2004 Committee on Quality of Health Care in America 2001Kohn Corrigan amp Donaldson 1999) Generally speaking these boards have beendeveloped by third-party vendors and usually have visual display layouts similarin nature to the whiteboards they have replaced Researchers have noted advan-tages in having a customized electronic tool to support multitasking in ED environ-ments (Laxmisan Hakimzada Sayan Green amp Patel 2007) Electronic systemsmay also address shortcomings of manual status boards Once erased informationcannot be recovered and information entered into one system (eg at hospitalregistration) cannot automatically populate the manual status board Thus repeateddata entry tasks may be required and information may be incomplete outdated orinconsistent across systems Electronic systems are often components of or linked toother hospital information systems and have the ability to log information inputs

Unlike the bottom-up evolutionary design of manual whiteboards the elec-tronic systems are typically purchased from third-party vendors often with onlymodest abilities for customization to reflect the individual uses in each hospital(but see Aronsky Jones Lanaghan amp Slovis 2008 for an example of a ldquohome-grownrdquo electronic system) Procurement is often led by organizational informationtechnology (IT) staff rather than clinicians and can be driven by overall organiza-tional needs and management goals such as system interoperability cost abilityto collect quality and efficiency measures integration with hospital bed manage-ment systems and data storage (Poon et al 2006) These needs may overshadowthose of the clinicians who have been using the manual whiteboard to supporttheir minute-by-minute work

For a variety of economic quality and policy reasons health care providerswill continue to transition to electronic systems Research in a number of settingshas indicated that when systems are designed based on an incorrect or rational-ized model of work performance suffers (Berg 1997 2004 Bisantz amp Ockerman2002 Button amp Harper 1993 Mackay 1999 Sachs 1995) New technology oftencreates a necessity for users to reorient themselves to the electronic system and

42 Journal of Cognitive Engineering and Decision Making Spring 2010

change their existing work practices by altering their tasks and configuring thenew systems In some cases the new technology may increase workload or lead toerrors if users are forced to adapt either the system or their tasks and strategiesduring critical periods (Cook amp Woods 1996) For new technologies to success-fully support or augment evolved work practices designers must start with a deepunderstanding of what functions the manual technologies support

Research ObjectivesIn observing a transition from manual to electronic status boards in two hospi-

tal emergency departments we found that providers reported a negative impact ofthe transition on communication and their ability to make sense of the overallstate of the ED (Pennathur et al 2007) This paper investigates the two technolo-gies in detail to try to identify design-oriented reasons for these difficulties Itcould be simply that the new system does not provide access to record or view thesame type or amount of information as the manual system Alternatively problemscould stem from the format of presentation or method of interaction or the differ-ences in affordances between the two technologies

Whereas other studies have documented aspects of the manual ED white-board technology (Wears amp Perry 2007 Wears et al 2007) these studies did notprovide a detailed comparison of the manual and new systems Thus the goals ofthis study were to document the information content functionality and format ofboth manual and electronic status boards in one particular ED to gain insight intospecific changes (in functionality and availability of information) that occurredduring the transition to the new technology

Methods

Data were collected from manual and electronic systems at a large academicmedical center hospital emergency department which had a patient volume of95000 patients per year Patient-tracking systems were used in multiple func-tional areas (such as adult care trauma and pediatric care) in this ED The EDcompletely transitioned to the computerized patient-tracking system at the timethe system was installed (that is the manual whiteboards were removed once theelectronic system became operational)

Data CollectionA month before the electronic patient-tracking system was implemented

manual status boards in two ED treatment areas were systematically photographedfor their information content Similarly 18 months after the electronic system wasimplemented digital images (screen shots) of the electronic patient-tracking sys-tem were recorded (see Figure 2 for an example) To support the most direct compar-ison we took screen shots of and analyzed only the primary screen of the electronicpatient-tracking display because this display corresponded most closely to the man-ual status board and served as the default ED display We did not analyze addi-tional linked screens in the electronic system or other information sources used

Emergency Department Status Boards in Transition 43

44 Journal of Cognitive Engineering and Decision Making Spring 2010

Figu

re 2

Ele

ctro

nic

stat

us d

ispl

ay s

cree

n sh

ot (n

ames

obs

cure

d) R

epri

nted

from

Fai

rban

ks e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

008

concurrently in the manual system (eg paper charts) Additionally whereas theelectronic system included both desktop and wall-mounted large-format dis-plays the wall-mounted system consistently displayed only the primary screen(scrolling to show all patients)

Data were collected in two distinct areas of the ED the adult acute area whichtreats sick and injured patients requiring urgent or semiurgent treatment (such asheart attacks or strokes) and the adult nonacute area which treats routine nonur-gent cases (such as ankle sprains or minor lacerations) These areas are geographi-cally separated and have separate nurse stations with specifically assigned ED staffIn both cases data were captured every 30 min for continuous 8-hr periods duringa day shift (two different periods for the photographs and one period for thescreen shots because the latter could be accessed from a single remote location)

For the manual system there was a secondary board in the acute area that wasused on some days to track some (but not all) information regarding a small num-ber of ldquooverflowrdquo patients who did not fit on the primary board Typically thesewere less acute patients assigned to overflow locations This board was not pho-tographed because it was not used consistently and because not all data fieldswere represented

In all a total of 68 images (34 photos and 34 screen shots) were captured andedited for patient de-identification Example images from both systems are pro-vided in Figures 1 and 2 Note that the primary organizing scheme for both sys-tems is a matrix format with patients represented in rows (each row correspondingto a bed or location in the ED) and with different kinds of information about thepatient (demographic details assigned caregivers treatment plans) located incolumns Text symbols and colors are used in both systems

AnalysisTwo levels of analysis were conducted by an interdisciplinary research team

composed of emergency medicine physiciansresearchers and human factorsresearchers (authors TG RF AB and PP) For one analysis an overall assessmentof the range of information provided by both systems was conducted by examin-ing the photographs and screen shots We noted the type or function of the infor-mation its location on the whiteboard or screen (eg left side of board nursecolumn) the method of entry (handwritten indicated on a preprinted magnet ortaped or otherwise attached for the manual board typed picked or selected froma list or automatically filled when other entries were made for the electronic board)whether the entry was alphanumeric or symbolic (either hand-drawn or typed)whether there was color or font coding and for the electronic system whether anicon was used whether information could be clicked or selected and whetherhovering with a mouse revealed additional details

The second analysis provided additional details for specific areas of the statusboards We focused on fields that contained significant information related to clinicalcare and workflow specifically columns related to chief complaints and those relatedto patient treatment and disposition The chief complaint provides information about

Emergency Department Status Boards in Transition 45

the primary reason a patient has come to the emergency department as providedby patients to nurses during the triage process in which the criticality of patientsrsquocondition is assessed

Disposition is a term commonly used in emergency medicine to describe thepatientrsquos destination once the ED care has been completed and might include hospi-tal admission transfer to another hospital or discharge to home These areas weretranscribed into spreadsheets (maintaining the use of symbols text color etc) andcoded by the research team Columns between the two systems did not alwaysdirectly correspond For example the column labeled Disposition on the manualwhiteboard contained (among other things) clinical orders and disposition informa-tion regarding the patient On the electronic status board there were three columnsrelated to these functions two columns with alphanumericcolored codes (labeledCustom and Disposition) and one column that accepted free text or click-and-selecttext entries (labeled Comments) Thus all three columns were coded in the lattercase to allow comparison with the disposition column on the manual board

Codes were developed iteratively during the analysis using a grounded-theoryapproach (Glaser amp Strauss 1967) and represented the different functions thatthe information present on the status boards could provide Because coding wasperformed by group consensus we did not compute interrater reliability statisticsIn analyzing and categorizing the information we also computed quantitativeindicators to understand the differences between the electronic and the manualwhiteboard Each photograph or screen shot contained information about multi-ple patients and because images were obtained across a continuous time spaninformation about a particular patient typically appeared in multiple images Wecombined entries for each patient when evaluating the frequency of coded entriesso that identical information was counted only a single time for each patient

The columns we coded could contain multiple pieces of information for a sin-gle patient These were analyzed separately as they could represent different cate-gories of information Figure 3 shows two chief complaint entries associated with asingle patient The chief complaint entry changed over time (between two photo-graphs) Four different chief complaint functions were coded for this entry ldquocar vsdeerrdquo indicated the mechanism of injury ldquoL arm injuryrdquo represents the problem(injury) location of the problem (arm) and laterality (LLeft) Similarly in the com-ments column (electronic system) the entry ldquoGET EKG EKG DONErdquo contains twodisposition functions ldquoclinical workup planrdquo and ldquoplan progressrdquo That is a plan

46 Journal of Cognitive Engineering and Decision Making Spring 2010

Figure 3 Example of transcribed chief complaint data

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 T

ype

s o

f In

form

ati

on

Re

pre

sen

ted

on

th

e M

an

ua

l an

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s D

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h M

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of

Info

rma

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Dis

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rma

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Loca

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Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 49

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om

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ldquoS

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ha

t n

ext

vit

als

x

x

sho

uld

be

ta

ken

Tim

e p

ati

en

t a

rriv

ed

at

xx

tria

ge

Tim

e p

ati

en

t m

ov

ed

fro

m

xx

wa

itin

g r

oo

m t

o b

ed

in E

D

Ch

ief

com

pla

int

wit

h

xb

ar

xH

igh

-ris

k ch

ief

com

pla

ints

po

ten

tia

l ris

k o

r (r

ed

ba

r to

left

of

cell)

qu

alit

y m

ea

sure

qu

alit

y m

ea

sure

(gre

en

ba

r) p

rese

nt

on

ly if

com

pla

int

wa

s

pic

k-se

lect

ed

Dia

gn

osi

s in

form

ati

on

x

xx

Blu

e le

tte

r D

en

tere

d e

lse

wh

ere

in t

he

sys

tem

Dis

po

siti

on

scr

ee

n a

cce

ssx

ba

rx

Co

lore

d b

ar

to le

ft o

f ce

ll

(gre

en

if ldquo

En

terrdquo

clic

ked

on

Dis

po

siti

on

scr

ee

n)

Flo

w s

he

et

info

rma

tio

n

xx

xLe

tte

r F

(vit

al s

ign

s) is

av

aila

ble

(ab

sen

ce o

f in

dic

ato

r

do

es

no

t in

dic

ate

ab

sen

ce o

f fl

ow

sh

ee

t)

Len

gth

-of-

sta

y a

lert

xx

xx

A c

olo

red

clo

ck ic

on

gre

en

if L

OS

lt 6

hr

red

oth

erw

ise

Co

nti

nu

ed n

ext p

ag

e

50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Len

gth

of

sta

y t

ime

sin

ce

xx

x

pa

tie

ntrsquo

s in

form

ati

on

en

tere

d a

t tr

iag

e

Mo

st r

ece

nt

pa

tie

nt

xx

Ast

eri

sks

ma

rk p

ati

en

t

acc

ess

ed

th

at

the

use

r la

st

acc

ess

ed

in s

yste

m

Pa

tie

nt

care

d f

or

by

no

n-E

D

xx

xx

OB

SB

RD

or

INP

TB

RD

tea

m (b

oa

rdin

g o

r d

isp

laye

d in

a b

lue

lab

el

ad

mit

ted

) in

dic

ate

s b

elo

w t

he

be

d n

am

e

pa

tie

nt

no

lon

ge

r in

ca

re

AD

MT

or

INP

T

of

ED

ph

ysic

ian

dis

pla

yed

inst

ea

d o

f

att

en

din

g p

hys

icia

n

na

me

Act

ion

ab

le o

r

Ho

ve

r ca

teg

ori

es

ap

ply

on

ly t

o A

DM

T o

r IN

PT

Pa

tie

nt

info

rma

tio

n c

alle

d

xx

xP

ho

ne

ico

n

in b

y p

rim

ary

ph

ysic

ian

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

ed

ce

ll w

as

red

ora

ng

e

yello

w g

ree

n b

lue

or

gra

y (i

f n

o a

cuit

y

sele

cte

d)

Typ

e o

f co

mm

en

tx

ba

rx

Re

d g

ree

n y

ello

w p

urp

le

gra

y b

lue

co

lore

d b

ar

to le

ft o

f co

mm

en

t ce

ll

(co

rre

spo

nd

ing

to

typ

e

of

com

me

nt)

on

ly if

th

e

mo

st r

ece

nt

com

me

nt

an

d it

wa

s p

ick-

sele

cte

d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 5: Emergency Department Status Boards: A Case Study in Information

change their existing work practices by altering their tasks and configuring thenew systems In some cases the new technology may increase workload or lead toerrors if users are forced to adapt either the system or their tasks and strategiesduring critical periods (Cook amp Woods 1996) For new technologies to success-fully support or augment evolved work practices designers must start with a deepunderstanding of what functions the manual technologies support

Research ObjectivesIn observing a transition from manual to electronic status boards in two hospi-

tal emergency departments we found that providers reported a negative impact ofthe transition on communication and their ability to make sense of the overallstate of the ED (Pennathur et al 2007) This paper investigates the two technolo-gies in detail to try to identify design-oriented reasons for these difficulties Itcould be simply that the new system does not provide access to record or view thesame type or amount of information as the manual system Alternatively problemscould stem from the format of presentation or method of interaction or the differ-ences in affordances between the two technologies

Whereas other studies have documented aspects of the manual ED white-board technology (Wears amp Perry 2007 Wears et al 2007) these studies did notprovide a detailed comparison of the manual and new systems Thus the goals ofthis study were to document the information content functionality and format ofboth manual and electronic status boards in one particular ED to gain insight intospecific changes (in functionality and availability of information) that occurredduring the transition to the new technology

Methods

Data were collected from manual and electronic systems at a large academicmedical center hospital emergency department which had a patient volume of95000 patients per year Patient-tracking systems were used in multiple func-tional areas (such as adult care trauma and pediatric care) in this ED The EDcompletely transitioned to the computerized patient-tracking system at the timethe system was installed (that is the manual whiteboards were removed once theelectronic system became operational)

Data CollectionA month before the electronic patient-tracking system was implemented

manual status boards in two ED treatment areas were systematically photographedfor their information content Similarly 18 months after the electronic system wasimplemented digital images (screen shots) of the electronic patient-tracking sys-tem were recorded (see Figure 2 for an example) To support the most direct compar-ison we took screen shots of and analyzed only the primary screen of the electronicpatient-tracking display because this display corresponded most closely to the man-ual status board and served as the default ED display We did not analyze addi-tional linked screens in the electronic system or other information sources used

Emergency Department Status Boards in Transition 43

44 Journal of Cognitive Engineering and Decision Making Spring 2010

Figu

re 2

Ele

ctro

nic

stat

us d

ispl

ay s

cree

n sh

ot (n

ames

obs

cure

d) R

epri

nted

from

Fai

rban

ks e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

008

concurrently in the manual system (eg paper charts) Additionally whereas theelectronic system included both desktop and wall-mounted large-format dis-plays the wall-mounted system consistently displayed only the primary screen(scrolling to show all patients)

Data were collected in two distinct areas of the ED the adult acute area whichtreats sick and injured patients requiring urgent or semiurgent treatment (such asheart attacks or strokes) and the adult nonacute area which treats routine nonur-gent cases (such as ankle sprains or minor lacerations) These areas are geographi-cally separated and have separate nurse stations with specifically assigned ED staffIn both cases data were captured every 30 min for continuous 8-hr periods duringa day shift (two different periods for the photographs and one period for thescreen shots because the latter could be accessed from a single remote location)

For the manual system there was a secondary board in the acute area that wasused on some days to track some (but not all) information regarding a small num-ber of ldquooverflowrdquo patients who did not fit on the primary board Typically thesewere less acute patients assigned to overflow locations This board was not pho-tographed because it was not used consistently and because not all data fieldswere represented

In all a total of 68 images (34 photos and 34 screen shots) were captured andedited for patient de-identification Example images from both systems are pro-vided in Figures 1 and 2 Note that the primary organizing scheme for both sys-tems is a matrix format with patients represented in rows (each row correspondingto a bed or location in the ED) and with different kinds of information about thepatient (demographic details assigned caregivers treatment plans) located incolumns Text symbols and colors are used in both systems

AnalysisTwo levels of analysis were conducted by an interdisciplinary research team

composed of emergency medicine physiciansresearchers and human factorsresearchers (authors TG RF AB and PP) For one analysis an overall assessmentof the range of information provided by both systems was conducted by examin-ing the photographs and screen shots We noted the type or function of the infor-mation its location on the whiteboard or screen (eg left side of board nursecolumn) the method of entry (handwritten indicated on a preprinted magnet ortaped or otherwise attached for the manual board typed picked or selected froma list or automatically filled when other entries were made for the electronic board)whether the entry was alphanumeric or symbolic (either hand-drawn or typed)whether there was color or font coding and for the electronic system whether anicon was used whether information could be clicked or selected and whetherhovering with a mouse revealed additional details

The second analysis provided additional details for specific areas of the statusboards We focused on fields that contained significant information related to clinicalcare and workflow specifically columns related to chief complaints and those relatedto patient treatment and disposition The chief complaint provides information about

Emergency Department Status Boards in Transition 45

the primary reason a patient has come to the emergency department as providedby patients to nurses during the triage process in which the criticality of patientsrsquocondition is assessed

Disposition is a term commonly used in emergency medicine to describe thepatientrsquos destination once the ED care has been completed and might include hospi-tal admission transfer to another hospital or discharge to home These areas weretranscribed into spreadsheets (maintaining the use of symbols text color etc) andcoded by the research team Columns between the two systems did not alwaysdirectly correspond For example the column labeled Disposition on the manualwhiteboard contained (among other things) clinical orders and disposition informa-tion regarding the patient On the electronic status board there were three columnsrelated to these functions two columns with alphanumericcolored codes (labeledCustom and Disposition) and one column that accepted free text or click-and-selecttext entries (labeled Comments) Thus all three columns were coded in the lattercase to allow comparison with the disposition column on the manual board

Codes were developed iteratively during the analysis using a grounded-theoryapproach (Glaser amp Strauss 1967) and represented the different functions thatthe information present on the status boards could provide Because coding wasperformed by group consensus we did not compute interrater reliability statisticsIn analyzing and categorizing the information we also computed quantitativeindicators to understand the differences between the electronic and the manualwhiteboard Each photograph or screen shot contained information about multi-ple patients and because images were obtained across a continuous time spaninformation about a particular patient typically appeared in multiple images Wecombined entries for each patient when evaluating the frequency of coded entriesso that identical information was counted only a single time for each patient

The columns we coded could contain multiple pieces of information for a sin-gle patient These were analyzed separately as they could represent different cate-gories of information Figure 3 shows two chief complaint entries associated with asingle patient The chief complaint entry changed over time (between two photo-graphs) Four different chief complaint functions were coded for this entry ldquocar vsdeerrdquo indicated the mechanism of injury ldquoL arm injuryrdquo represents the problem(injury) location of the problem (arm) and laterality (LLeft) Similarly in the com-ments column (electronic system) the entry ldquoGET EKG EKG DONErdquo contains twodisposition functions ldquoclinical workup planrdquo and ldquoplan progressrdquo That is a plan

46 Journal of Cognitive Engineering and Decision Making Spring 2010

Figure 3 Example of transcribed chief complaint data

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 T

ype

s o

f In

form

ati

on

Re

pre

sen

ted

on

th

e M

an

ua

l an

do

r E

lect

ron

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tatu

s D

isp

lay

Alo

ng

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h M

eth

od

of

Info

rma

tio

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ntr

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Dis

pla

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rify

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No

tes

Ma

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em

Ele

ctro

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Sy

ste

m

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rma

tio

n T

ype

an

d

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al N

ote

s

De

scri

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Use

Att

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hys

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nrsquos

x

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cifi

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ysic

ian

wo

rkfl

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ind

ica

tin

g p

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ress

wit

h p

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Loca

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Emergency Department Status Boards in Transition 49

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sa

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d f

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rtic

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ldquoS

av

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Gyn

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50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

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ue

d)

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ctro

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st r

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tea

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isp

laye

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lab

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in b

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AlphanumericKBD Symbol

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StickiesNotepad

Icons

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Emergency Department Status Boards in Transition 51

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me

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wa

s p

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rna

me

of

seco

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x

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ass

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nu

rse

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tio

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lore

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va

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Ta

ble

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or

ad

dit

ion

al d

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ils)

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nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

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ste

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Info

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scri

pti

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or

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tie

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xx

xx

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Pa

tie

ntrsquo

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en

de

rx

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xx

xT

he

lett

er

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O o

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(fe

ma

le m

ale

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er

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kno

wn

) (E

) t

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bo

ls f

or

ma

le o

r

fem

ale

(M)

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tie

ntrsquo

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ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

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41

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41

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gre

sscl

inic

al w

ork

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n c

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lan

ne

d

Be

d n

um

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ast

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Te

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De

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r ca

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ive

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P 1

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ran

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rt C

Trdquo

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nt

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r p

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isp

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n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 6: Emergency Department Status Boards: A Case Study in Information

44 Journal of Cognitive Engineering and Decision Making Spring 2010

Figu

re 2

Ele

ctro

nic

stat

us d

ispl

ay s

cree

n sh

ot (n

ames

obs

cure

d) R

epri

nted

from

Fai

rban

ks e

t al

Pro

ceed

ings

of t

he H

uman

Fac

tors

and

Erg

onom

ics

Soci

ety

Ann

ual M

eeti

ng2

008

concurrently in the manual system (eg paper charts) Additionally whereas theelectronic system included both desktop and wall-mounted large-format dis-plays the wall-mounted system consistently displayed only the primary screen(scrolling to show all patients)

Data were collected in two distinct areas of the ED the adult acute area whichtreats sick and injured patients requiring urgent or semiurgent treatment (such asheart attacks or strokes) and the adult nonacute area which treats routine nonur-gent cases (such as ankle sprains or minor lacerations) These areas are geographi-cally separated and have separate nurse stations with specifically assigned ED staffIn both cases data were captured every 30 min for continuous 8-hr periods duringa day shift (two different periods for the photographs and one period for thescreen shots because the latter could be accessed from a single remote location)

For the manual system there was a secondary board in the acute area that wasused on some days to track some (but not all) information regarding a small num-ber of ldquooverflowrdquo patients who did not fit on the primary board Typically thesewere less acute patients assigned to overflow locations This board was not pho-tographed because it was not used consistently and because not all data fieldswere represented

In all a total of 68 images (34 photos and 34 screen shots) were captured andedited for patient de-identification Example images from both systems are pro-vided in Figures 1 and 2 Note that the primary organizing scheme for both sys-tems is a matrix format with patients represented in rows (each row correspondingto a bed or location in the ED) and with different kinds of information about thepatient (demographic details assigned caregivers treatment plans) located incolumns Text symbols and colors are used in both systems

AnalysisTwo levels of analysis were conducted by an interdisciplinary research team

composed of emergency medicine physiciansresearchers and human factorsresearchers (authors TG RF AB and PP) For one analysis an overall assessmentof the range of information provided by both systems was conducted by examin-ing the photographs and screen shots We noted the type or function of the infor-mation its location on the whiteboard or screen (eg left side of board nursecolumn) the method of entry (handwritten indicated on a preprinted magnet ortaped or otherwise attached for the manual board typed picked or selected froma list or automatically filled when other entries were made for the electronic board)whether the entry was alphanumeric or symbolic (either hand-drawn or typed)whether there was color or font coding and for the electronic system whether anicon was used whether information could be clicked or selected and whetherhovering with a mouse revealed additional details

The second analysis provided additional details for specific areas of the statusboards We focused on fields that contained significant information related to clinicalcare and workflow specifically columns related to chief complaints and those relatedto patient treatment and disposition The chief complaint provides information about

Emergency Department Status Boards in Transition 45

the primary reason a patient has come to the emergency department as providedby patients to nurses during the triage process in which the criticality of patientsrsquocondition is assessed

Disposition is a term commonly used in emergency medicine to describe thepatientrsquos destination once the ED care has been completed and might include hospi-tal admission transfer to another hospital or discharge to home These areas weretranscribed into spreadsheets (maintaining the use of symbols text color etc) andcoded by the research team Columns between the two systems did not alwaysdirectly correspond For example the column labeled Disposition on the manualwhiteboard contained (among other things) clinical orders and disposition informa-tion regarding the patient On the electronic status board there were three columnsrelated to these functions two columns with alphanumericcolored codes (labeledCustom and Disposition) and one column that accepted free text or click-and-selecttext entries (labeled Comments) Thus all three columns were coded in the lattercase to allow comparison with the disposition column on the manual board

Codes were developed iteratively during the analysis using a grounded-theoryapproach (Glaser amp Strauss 1967) and represented the different functions thatthe information present on the status boards could provide Because coding wasperformed by group consensus we did not compute interrater reliability statisticsIn analyzing and categorizing the information we also computed quantitativeindicators to understand the differences between the electronic and the manualwhiteboard Each photograph or screen shot contained information about multi-ple patients and because images were obtained across a continuous time spaninformation about a particular patient typically appeared in multiple images Wecombined entries for each patient when evaluating the frequency of coded entriesso that identical information was counted only a single time for each patient

The columns we coded could contain multiple pieces of information for a sin-gle patient These were analyzed separately as they could represent different cate-gories of information Figure 3 shows two chief complaint entries associated with asingle patient The chief complaint entry changed over time (between two photo-graphs) Four different chief complaint functions were coded for this entry ldquocar vsdeerrdquo indicated the mechanism of injury ldquoL arm injuryrdquo represents the problem(injury) location of the problem (arm) and laterality (LLeft) Similarly in the com-ments column (electronic system) the entry ldquoGET EKG EKG DONErdquo contains twodisposition functions ldquoclinical workup planrdquo and ldquoplan progressrdquo That is a plan

46 Journal of Cognitive Engineering and Decision Making Spring 2010

Figure 3 Example of transcribed chief complaint data

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 T

ype

s o

f In

form

ati

on

Re

pre

sen

ted

on

th

e M

an

ua

l an

do

r E

lect

ron

ic S

tatu

s D

isp

lay

Alo

ng

Wit

h M

eth

od

of

Info

rma

tio

n E

ntr

y

or

Dis

pla

y a

nd

Cla

rify

ing

No

tes

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Att

en

din

g p

hys

icia

nrsquos

x

xS

pe

cifi

c to

ph

ysic

ian

wo

rkfl

ow

sym

bo

ls

ind

ica

tin

g p

rog

ress

wit

h p

ati

en

t

Be

d r

ea

ssig

nm

en

t p

lan

x

xx

Loca

ted

to

th

e le

ft o

f th

e

cha

ng

ing

th

e w

ritt

en

m

atr

ix

roo

m n

um

be

r o

r st

icke

r

ED

ph

arm

aci

st o

no

ff d

uty

xx

xO

n d

uty

(gre

en

) o

ff d

uty

(re

d)

loca

ted

on

to

p o

f

the

bo

ard

Pat

ien

t is

pe

dia

tric

xP

atie

nt

nam

e w

ritt

en

in r

ed

Re

sid

en

t p

hys

icia

nrsquos

x

xx

Sp

eci

fic

to r

esi

de

nt

wo

rkfl

ow

sym

bo

ls

ind

ica

tin

g p

rog

ress

wit

h p

ati

en

t

Ro

om

is s

tock

ed

wit

h

xH

an

d-d

raw

n d

ot

ne

xt t

o

sup

plie

s ro

om

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 49

Ro

om

sa

ve

d f

or

pa

rtic

ula

r x

xx

Eg

ldquoS

av

e f

or

Gyn

rdquo

tre

atm

en

ts

Sh

ift

of

pa

tie

nt

arr

iva

lx

Pa

tie

nt

info

rma

tio

n

wri

tte

n in

sa

me

co

lor

thro

ug

ho

ut

a s

hif

t

ldquoold

er

colo

rsrdquo

sig

nif

y

lon

ge

r-d

ura

tio

n

pa

tie

nts

Tim

e (h

ou

r) t

ha

t n

ext

vit

als

x

x

sho

uld

be

ta

ken

Tim

e p

ati

en

t a

rriv

ed

at

xx

tria

ge

Tim

e p

ati

en

t m

ov

ed

fro

m

xx

wa

itin

g r

oo

m t

o b

ed

in E

D

Ch

ief

com

pla

int

wit

h

xb

ar

xH

igh

-ris

k ch

ief

com

pla

ints

po

ten

tia

l ris

k o

r (r

ed

ba

r to

left

of

cell)

qu

alit

y m

ea

sure

qu

alit

y m

ea

sure

(gre

en

ba

r) p

rese

nt

on

ly if

com

pla

int

wa

s

pic

k-se

lect

ed

Dia

gn

osi

s in

form

ati

on

x

xx

Blu

e le

tte

r D

en

tere

d e

lse

wh

ere

in t

he

sys

tem

Dis

po

siti

on

scr

ee

n a

cce

ssx

ba

rx

Co

lore

d b

ar

to le

ft o

f ce

ll

(gre

en

if ldquo

En

terrdquo

clic

ked

on

Dis

po

siti

on

scr

ee

n)

Flo

w s

he

et

info

rma

tio

n

xx

xLe

tte

r F

(vit

al s

ign

s) is

av

aila

ble

(ab

sen

ce o

f in

dic

ato

r

do

es

no

t in

dic

ate

ab

sen

ce o

f fl

ow

sh

ee

t)

Len

gth

-of-

sta

y a

lert

xx

xx

A c

olo

red

clo

ck ic

on

gre

en

if L

OS

lt 6

hr

red

oth

erw

ise

Co

nti

nu

ed n

ext p

ag

e

50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Len

gth

of

sta

y t

ime

sin

ce

xx

x

pa

tie

ntrsquo

s in

form

ati

on

en

tere

d a

t tr

iag

e

Mo

st r

ece

nt

pa

tie

nt

xx

Ast

eri

sks

ma

rk p

ati

en

t

acc

ess

ed

th

at

the

use

r la

st

acc

ess

ed

in s

yste

m

Pa

tie

nt

care

d f

or

by

no

n-E

D

xx

xx

OB

SB

RD

or

INP

TB

RD

tea

m (b

oa

rdin

g o

r d

isp

laye

d in

a b

lue

lab

el

ad

mit

ted

) in

dic

ate

s b

elo

w t

he

be

d n

am

e

pa

tie

nt

no

lon

ge

r in

ca

re

AD

MT

or

INP

T

of

ED

ph

ysic

ian

dis

pla

yed

inst

ea

d o

f

att

en

din

g p

hys

icia

n

na

me

Act

ion

ab

le o

r

Ho

ve

r ca

teg

ori

es

ap

ply

on

ly t

o A

DM

T o

r IN

PT

Pa

tie

nt

info

rma

tio

n c

alle

d

xx

xP

ho

ne

ico

n

in b

y p

rim

ary

ph

ysic

ian

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

ed

ce

ll w

as

red

ora

ng

e

yello

w g

ree

n b

lue

or

gra

y (i

f n

o a

cuit

y

sele

cte

d)

Typ

e o

f co

mm

en

tx

ba

rx

Re

d g

ree

n y

ello

w p

urp

le

gra

y b

lue

co

lore

d b

ar

to le

ft o

f co

mm

en

t ce

ll

(co

rre

spo

nd

ing

to

typ

e

of

com

me

nt)

on

ly if

th

e

mo

st r

ece

nt

com

me

nt

an

d it

wa

s p

ick-

sele

cte

d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 7: Emergency Department Status Boards: A Case Study in Information

concurrently in the manual system (eg paper charts) Additionally whereas theelectronic system included both desktop and wall-mounted large-format dis-plays the wall-mounted system consistently displayed only the primary screen(scrolling to show all patients)

Data were collected in two distinct areas of the ED the adult acute area whichtreats sick and injured patients requiring urgent or semiurgent treatment (such asheart attacks or strokes) and the adult nonacute area which treats routine nonur-gent cases (such as ankle sprains or minor lacerations) These areas are geographi-cally separated and have separate nurse stations with specifically assigned ED staffIn both cases data were captured every 30 min for continuous 8-hr periods duringa day shift (two different periods for the photographs and one period for thescreen shots because the latter could be accessed from a single remote location)

For the manual system there was a secondary board in the acute area that wasused on some days to track some (but not all) information regarding a small num-ber of ldquooverflowrdquo patients who did not fit on the primary board Typically thesewere less acute patients assigned to overflow locations This board was not pho-tographed because it was not used consistently and because not all data fieldswere represented

In all a total of 68 images (34 photos and 34 screen shots) were captured andedited for patient de-identification Example images from both systems are pro-vided in Figures 1 and 2 Note that the primary organizing scheme for both sys-tems is a matrix format with patients represented in rows (each row correspondingto a bed or location in the ED) and with different kinds of information about thepatient (demographic details assigned caregivers treatment plans) located incolumns Text symbols and colors are used in both systems

AnalysisTwo levels of analysis were conducted by an interdisciplinary research team

composed of emergency medicine physiciansresearchers and human factorsresearchers (authors TG RF AB and PP) For one analysis an overall assessmentof the range of information provided by both systems was conducted by examin-ing the photographs and screen shots We noted the type or function of the infor-mation its location on the whiteboard or screen (eg left side of board nursecolumn) the method of entry (handwritten indicated on a preprinted magnet ortaped or otherwise attached for the manual board typed picked or selected froma list or automatically filled when other entries were made for the electronic board)whether the entry was alphanumeric or symbolic (either hand-drawn or typed)whether there was color or font coding and for the electronic system whether anicon was used whether information could be clicked or selected and whetherhovering with a mouse revealed additional details

The second analysis provided additional details for specific areas of the statusboards We focused on fields that contained significant information related to clinicalcare and workflow specifically columns related to chief complaints and those relatedto patient treatment and disposition The chief complaint provides information about

Emergency Department Status Boards in Transition 45

the primary reason a patient has come to the emergency department as providedby patients to nurses during the triage process in which the criticality of patientsrsquocondition is assessed

Disposition is a term commonly used in emergency medicine to describe thepatientrsquos destination once the ED care has been completed and might include hospi-tal admission transfer to another hospital or discharge to home These areas weretranscribed into spreadsheets (maintaining the use of symbols text color etc) andcoded by the research team Columns between the two systems did not alwaysdirectly correspond For example the column labeled Disposition on the manualwhiteboard contained (among other things) clinical orders and disposition informa-tion regarding the patient On the electronic status board there were three columnsrelated to these functions two columns with alphanumericcolored codes (labeledCustom and Disposition) and one column that accepted free text or click-and-selecttext entries (labeled Comments) Thus all three columns were coded in the lattercase to allow comparison with the disposition column on the manual board

Codes were developed iteratively during the analysis using a grounded-theoryapproach (Glaser amp Strauss 1967) and represented the different functions thatthe information present on the status boards could provide Because coding wasperformed by group consensus we did not compute interrater reliability statisticsIn analyzing and categorizing the information we also computed quantitativeindicators to understand the differences between the electronic and the manualwhiteboard Each photograph or screen shot contained information about multi-ple patients and because images were obtained across a continuous time spaninformation about a particular patient typically appeared in multiple images Wecombined entries for each patient when evaluating the frequency of coded entriesso that identical information was counted only a single time for each patient

The columns we coded could contain multiple pieces of information for a sin-gle patient These were analyzed separately as they could represent different cate-gories of information Figure 3 shows two chief complaint entries associated with asingle patient The chief complaint entry changed over time (between two photo-graphs) Four different chief complaint functions were coded for this entry ldquocar vsdeerrdquo indicated the mechanism of injury ldquoL arm injuryrdquo represents the problem(injury) location of the problem (arm) and laterality (LLeft) Similarly in the com-ments column (electronic system) the entry ldquoGET EKG EKG DONErdquo contains twodisposition functions ldquoclinical workup planrdquo and ldquoplan progressrdquo That is a plan

46 Journal of Cognitive Engineering and Decision Making Spring 2010

Figure 3 Example of transcribed chief complaint data

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 T

ype

s o

f In

form

ati

on

Re

pre

sen

ted

on

th

e M

an

ua

l an

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ron

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tatu

s D

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lay

Alo

ng

Wit

h M

eth

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Info

rma

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No

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Ma

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ctro

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Att

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ind

ica

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g p

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Loca

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no

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xx

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Emergency Department Status Boards in Transition 49

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Co

nti

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ed n

ext p

ag

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50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

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ue

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gth

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Mo

st r

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pa

tie

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xx

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rim

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Emergency Department Status Boards in Transition 51

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seco

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rse

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n

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pe

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roo

m n

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be

r (E

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x

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ee

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ble

2 f

or

ad

dit

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al d

eta

ils)

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nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

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d

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dit

ion

al N

ote

s

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scri

pti

on

or

Co

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nt

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tie

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ge

xx

xx

xx

Pa

tie

ntrsquo

s g

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de

rx

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xx

xT

he

lett

er

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O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

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) t

he

sym

bo

ls f

or

ma

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fem

ale

(M)

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tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

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mi-

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00

00

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00

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mp

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size

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en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

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ldquoOp

tho

Clin

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00

03

03

00

00

04

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00

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tie

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pa

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oth

er

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n

(op

tho

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log

y cl

inic

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loca

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ne

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ed

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nsp

ort

Xra

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lan

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rog

ress

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gre

sscl

inic

al w

ork

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n c

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lan

ne

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Be

d n

um

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r o

r a

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ast

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2Lrdquo

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it O

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at

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issi

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Te

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De

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r ca

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ive

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P 1

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2 6

-14

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r 1

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2)

Te

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00

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rt C

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nd

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n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 8: Emergency Department Status Boards: A Case Study in Information

the primary reason a patient has come to the emergency department as providedby patients to nurses during the triage process in which the criticality of patientsrsquocondition is assessed

Disposition is a term commonly used in emergency medicine to describe thepatientrsquos destination once the ED care has been completed and might include hospi-tal admission transfer to another hospital or discharge to home These areas weretranscribed into spreadsheets (maintaining the use of symbols text color etc) andcoded by the research team Columns between the two systems did not alwaysdirectly correspond For example the column labeled Disposition on the manualwhiteboard contained (among other things) clinical orders and disposition informa-tion regarding the patient On the electronic status board there were three columnsrelated to these functions two columns with alphanumericcolored codes (labeledCustom and Disposition) and one column that accepted free text or click-and-selecttext entries (labeled Comments) Thus all three columns were coded in the lattercase to allow comparison with the disposition column on the manual board

Codes were developed iteratively during the analysis using a grounded-theoryapproach (Glaser amp Strauss 1967) and represented the different functions thatthe information present on the status boards could provide Because coding wasperformed by group consensus we did not compute interrater reliability statisticsIn analyzing and categorizing the information we also computed quantitativeindicators to understand the differences between the electronic and the manualwhiteboard Each photograph or screen shot contained information about multi-ple patients and because images were obtained across a continuous time spaninformation about a particular patient typically appeared in multiple images Wecombined entries for each patient when evaluating the frequency of coded entriesso that identical information was counted only a single time for each patient

The columns we coded could contain multiple pieces of information for a sin-gle patient These were analyzed separately as they could represent different cate-gories of information Figure 3 shows two chief complaint entries associated with asingle patient The chief complaint entry changed over time (between two photo-graphs) Four different chief complaint functions were coded for this entry ldquocar vsdeerrdquo indicated the mechanism of injury ldquoL arm injuryrdquo represents the problem(injury) location of the problem (arm) and laterality (LLeft) Similarly in the com-ments column (electronic system) the entry ldquoGET EKG EKG DONErdquo contains twodisposition functions ldquoclinical workup planrdquo and ldquoplan progressrdquo That is a plan

46 Journal of Cognitive Engineering and Decision Making Spring 2010

Figure 3 Example of transcribed chief complaint data

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

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t is

pe

dia

tric

xP

atie

nt

nam

e w

ritt

en

in r

ed

Re

sid

en

t p

hys

icia

nrsquos

x

xx

Sp

eci

fic

to r

esi

de

nt

wo

rkfl

ow

sym

bo

ls

ind

ica

tin

g p

rog

ress

wit

h p

ati

en

t

Ro

om

is s

tock

ed

wit

h

xH

an

d-d

raw

n d

ot

ne

xt t

o

sup

plie

s ro

om

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 49

Ro

om

sa

ve

d f

or

pa

rtic

ula

r x

xx

Eg

ldquoS

av

e f

or

Gyn

rdquo

tre

atm

en

ts

Sh

ift

of

pa

tie

nt

arr

iva

lx

Pa

tie

nt

info

rma

tio

n

wri

tte

n in

sa

me

co

lor

thro

ug

ho

ut

a s

hif

t

ldquoold

er

colo

rsrdquo

sig

nif

y

lon

ge

r-d

ura

tio

n

pa

tie

nts

Tim

e (h

ou

r) t

ha

t n

ext

vit

als

x

x

sho

uld

be

ta

ken

Tim

e p

ati

en

t a

rriv

ed

at

xx

tria

ge

Tim

e p

ati

en

t m

ov

ed

fro

m

xx

wa

itin

g r

oo

m t

o b

ed

in E

D

Ch

ief

com

pla

int

wit

h

xb

ar

xH

igh

-ris

k ch

ief

com

pla

ints

po

ten

tia

l ris

k o

r (r

ed

ba

r to

left

of

cell)

qu

alit

y m

ea

sure

qu

alit

y m

ea

sure

(gre

en

ba

r) p

rese

nt

on

ly if

com

pla

int

wa

s

pic

k-se

lect

ed

Dia

gn

osi

s in

form

ati

on

x

xx

Blu

e le

tte

r D

en

tere

d e

lse

wh

ere

in t

he

sys

tem

Dis

po

siti

on

scr

ee

n a

cce

ssx

ba

rx

Co

lore

d b

ar

to le

ft o

f ce

ll

(gre

en

if ldquo

En

terrdquo

clic

ked

on

Dis

po

siti

on

scr

ee

n)

Flo

w s

he

et

info

rma

tio

n

xx

xLe

tte

r F

(vit

al s

ign

s) is

av

aila

ble

(ab

sen

ce o

f in

dic

ato

r

do

es

no

t in

dic

ate

ab

sen

ce o

f fl

ow

sh

ee

t)

Len

gth

-of-

sta

y a

lert

xx

xx

A c

olo

red

clo

ck ic

on

gre

en

if L

OS

lt 6

hr

red

oth

erw

ise

Co

nti

nu

ed n

ext p

ag

e

50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Len

gth

of

sta

y t

ime

sin

ce

xx

x

pa

tie

ntrsquo

s in

form

ati

on

en

tere

d a

t tr

iag

e

Mo

st r

ece

nt

pa

tie

nt

xx

Ast

eri

sks

ma

rk p

ati

en

t

acc

ess

ed

th

at

the

use

r la

st

acc

ess

ed

in s

yste

m

Pa

tie

nt

care

d f

or

by

no

n-E

D

xx

xx

OB

SB

RD

or

INP

TB

RD

tea

m (b

oa

rdin

g o

r d

isp

laye

d in

a b

lue

lab

el

ad

mit

ted

) in

dic

ate

s b

elo

w t

he

be

d n

am

e

pa

tie

nt

no

lon

ge

r in

ca

re

AD

MT

or

INP

T

of

ED

ph

ysic

ian

dis

pla

yed

inst

ea

d o

f

att

en

din

g p

hys

icia

n

na

me

Act

ion

ab

le o

r

Ho

ve

r ca

teg

ori

es

ap

ply

on

ly t

o A

DM

T o

r IN

PT

Pa

tie

nt

info

rma

tio

n c

alle

d

xx

xP

ho

ne

ico

n

in b

y p

rim

ary

ph

ysic

ian

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

ed

ce

ll w

as

red

ora

ng

e

yello

w g

ree

n b

lue

or

gra

y (i

f n

o a

cuit

y

sele

cte

d)

Typ

e o

f co

mm

en

tx

ba

rx

Re

d g

ree

n y

ello

w p

urp

le

gra

y b

lue

co

lore

d b

ar

to le

ft o

f co

mm

en

t ce

ll

(co

rre

spo

nd

ing

to

typ

e

of

com

me

nt)

on

ly if

th

e

mo

st r

ece

nt

com

me

nt

an

d it

wa

s p

ick-

sele

cte

d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 9: Emergency Department Status Boards: A Case Study in Information

for the clinical workflow of the patient is described by specifying the taskmdashldquoGETEKGrdquomdashto be performed as well as the status of the plan as it progressesmdashldquoEKGDONErdquo A list and definitions of all categories developed for both the chief com-plaint and dispositioncomments analysis is provided in the results section

Results

Overall 105 patients were shown on the manual whiteboards analyzed and80 on the electronic whiteboard representing differences in the patient numberstreated in the areas of the ED studied for the days on which data were collectedQuantitative results (described later) have been scaled to patient count to facilitatecomparisons between the manual and electronic systems The overall analysis isdescribed first followed by the detailed analysis of the chief complaint and dispo-sitioncomments columns of the status boards

Overall Information ContentWe identified 41 categories of information across the manual and electronic sta-

tus boards as shown in Table 1 In 37 of the cases the information was present inboth systems representing the primary information fields containing patient demo-graphic details and provider information However there were important differencesSymbols (hand drawn) used by attending and resident physicians to track theirpatient-specific workflow (eg if they had examined or written notes about a patient)were present on the manual whiteboard but not in the electronic system The manualsystem also provided information about the overall ED (presenceabsence of an EDpharmacist) and individual rooms (stocked set up for pediatric patients) which wasnot available in the electronic system These annotations were either outside thematrix structure (eg notes at the top lines along the side of the board) or were indi-vidualized to care providers (workflow codes) In contrast information unique to theelectronic status board exploited the systemrsquos ability to automatically flag or computeinformation The electronic system provided the (computed) length of stay (colorcoded if longer than a specified time) rather than the time of arrival an indication ofchief complaints associated with regulatory quality measures or high-risk chief com-plaints the most recent patient viewed or edited by the user and an indication ofwhether the patient had a previous ED visit recorded in the electronic system

Both systems made use of color to code or highlight information For instanceon the manual board names and information regarding pediatric patients in thenonacute section of the ED (where both pediatric and adult patients are seen)were written in red and rooms configured for pediatric patients were highlightedwith a red line next to the room numbers In a different ED area the marker colorused changed with each shift so that the mix of colors on the board indicated(approximately) the overall progress in moving patients through the ED and afourth color was used to indicate admitted patients Previous studies have alsonoted the use of color on ED status boards (Wears et al 2007)

Emergency Department Status Boards in Transition 47

(text continues on page 54)

48 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 T

ype

s o

f In

form

ati

on

Re

pre

sen

ted

on

th

e M

an

ua

l an

do

r E

lect

ron

ic S

tatu

s D

isp

lay

Alo

ng

Wit

h M

eth

od

of

Info

rma

tio

n E

ntr

y

or

Dis

pla

y a

nd

Cla

rify

ing

No

tes

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

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al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Att

en

din

g p

hys

icia

nrsquos

x

xS

pe

cifi

c to

ph

ysic

ian

wo

rkfl

ow

sym

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ls

ind

ica

tin

g p

rog

ress

wit

h p

ati

en

t

Be

d r

ea

ssig

nm

en

t p

lan

x

xx

Loca

ted

to

th

e le

ft o

f th

e

cha

ng

ing

th

e w

ritt

en

m

atr

ix

roo

m n

um

be

r o

r st

icke

r

ED

ph

arm

aci

st o

no

ff d

uty

xx

xO

n d

uty

(gre

en

) o

ff d

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(re

d)

loca

ted

on

to

p o

f

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bo

ard

Pat

ien

t is

pe

dia

tric

xP

atie

nt

nam

e w

ritt

en

in r

ed

Re

sid

en

t p

hys

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x

xx

Sp

eci

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esi

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ica

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g p

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wit

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ed

wit

h

xH

an

d-d

raw

n d

ot

ne

xt t

o

sup

plie

s ro

om

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 49

Ro

om

sa

ve

d f

or

pa

rtic

ula

r x

xx

Eg

ldquoS

av

e f

or

Gyn

rdquo

tre

atm

en

ts

Sh

ift

of

pa

tie

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arr

iva

lx

Pa

tie

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rma

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n

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tte

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sa

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ug

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ut

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Tim

e (h

ou

r) t

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uld

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Tim

e p

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tria

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Tim

e p

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itin

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left

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int

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lect

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Dia

gn

osi

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form

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on

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Blu

e le

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wh

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in t

he

sys

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Dis

po

siti

on

scr

ee

n a

cce

ssx

ba

rx

Co

lore

d b

ar

to le

ft o

f ce

ll

(gre

en

if ldquo

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clic

ked

on

Dis

po

siti

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ee

n)

Flo

w s

he

et

info

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n

xx

xLe

tte

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(vit

al s

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aila

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sen

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gth

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if L

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lt 6

hr

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ise

Co

nti

nu

ed n

ext p

ag

e

50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

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Ad

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Len

gth

of

sta

y t

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xx

x

pa

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ntrsquo

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tere

d a

t tr

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Mo

st r

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pa

tie

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xx

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ati

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use

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r d

isp

laye

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lue

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mit

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elo

w t

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be

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am

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tie

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lon

ge

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INP

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ysic

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pla

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ea

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din

g p

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Act

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PT

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alle

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xP

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ico

n

in b

y p

rim

ary

ph

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ian

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

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AlphanumericKBD Symbol

StickiesNotepad

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Actionable

Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

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ll w

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ora

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lue

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roo

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nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

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ste

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Pa

tie

ntrsquo

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ge

xx

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Pa

tie

ntrsquo

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en

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rx

xx

xx

xT

he

lett

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r U

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ma

le m

ale

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kno

wn

) (E

) t

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fem

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(M)

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ntrsquo

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ll n

am

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)

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pa

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ntrsquo

s la

st n

am

e a

nd

som

e f

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)

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se

t u

p f

or

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dia

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sx

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me

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r re

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s (M

)

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sta

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x

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w is

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le y

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)

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)

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) or

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rna

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r fi

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x

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f th

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Location Outside of Matrix Form

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Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

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StickiesNotepad

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Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

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r in

itia

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xU

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drdquo

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ns

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y co

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cte

d f

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furt

he

r d

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or

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rma

tio

n ldquo

Ho

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he

mo

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log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 10: Emergency Department Status Boards: A Case Study in Information

48 Journal of Cognitive Engineering and Decision Making Spring 2010

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50 Journal of Cognitive Engineering and Decision Making Spring 2010

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seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

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tie

nt

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ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

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MR

I1

93

0rdquo

95

39

03

27

11

53

10

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wo

rku

p

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nn

ed

lab

s

(pa

tie

nt

sch

ed

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ag

ing

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sts

fo

r M

RI a

t 6

30

PM

)

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dic

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on

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eq

ue

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rem

ind

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r

act

ivit

ies

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llow

-up

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nsu

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y 1

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ed

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alu

ate

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tie

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in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

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Xra

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rt C

Trdquo

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nsp

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r p

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re

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T)

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osi

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nd

Co

mm

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ts e

ntr

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to

tale

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lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 11: Emergency Department Status Boards: A Case Study in Information

Emergency Department Status Boards in Transition 49

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n)

Flo

w s

he

et

info

rma

tio

n

xx

xLe

tte

r F

(vit

al s

ign

s) is

av

aila

ble

(ab

sen

ce o

f in

dic

ato

r

do

es

no

t in

dic

ate

ab

sen

ce o

f fl

ow

sh

ee

t)

Len

gth

-of-

sta

y a

lert

xx

xx

A c

olo

red

clo

ck ic

on

gre

en

if L

OS

lt 6

hr

red

oth

erw

ise

Co

nti

nu

ed n

ext p

ag

e

50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Len

gth

of

sta

y t

ime

sin

ce

xx

x

pa

tie

ntrsquo

s in

form

ati

on

en

tere

d a

t tr

iag

e

Mo

st r

ece

nt

pa

tie

nt

xx

Ast

eri

sks

ma

rk p

ati

en

t

acc

ess

ed

th

at

the

use

r la

st

acc

ess

ed

in s

yste

m

Pa

tie

nt

care

d f

or

by

no

n-E

D

xx

xx

OB

SB

RD

or

INP

TB

RD

tea

m (b

oa

rdin

g o

r d

isp

laye

d in

a b

lue

lab

el

ad

mit

ted

) in

dic

ate

s b

elo

w t

he

be

d n

am

e

pa

tie

nt

no

lon

ge

r in

ca

re

AD

MT

or

INP

T

of

ED

ph

ysic

ian

dis

pla

yed

inst

ea

d o

f

att

en

din

g p

hys

icia

n

na

me

Act

ion

ab

le o

r

Ho

ve

r ca

teg

ori

es

ap

ply

on

ly t

o A

DM

T o

r IN

PT

Pa

tie

nt

info

rma

tio

n c

alle

d

xx

xP

ho

ne

ico

n

in b

y p

rim

ary

ph

ysic

ian

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

ed

ce

ll w

as

red

ora

ng

e

yello

w g

ree

n b

lue

or

gra

y (i

f n

o a

cuit

y

sele

cte

d)

Typ

e o

f co

mm

en

tx

ba

rx

Re

d g

ree

n y

ello

w p

urp

le

gra

y b

lue

co

lore

d b

ar

to le

ft o

f co

mm

en

t ce

ll

(co

rre

spo

nd

ing

to

typ

e

of

com

me

nt)

on

ly if

th

e

mo

st r

ece

nt

com

me

nt

an

d it

wa

s p

ick-

sele

cte

d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

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lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

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req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

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ctro

nic

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an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

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en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

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oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

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ckb

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s d

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t 7

30

rdquoP

lan

ne

d

Be

d n

um

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r o

r a

rea

ldquoE

ast

21

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2Lrdquo

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64

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01

50

15

10

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ed

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ati

en

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ign

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ve

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wit

hin

ED

Se

rvic

eD

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n h

osp

ita

l ldquoa

dm

it O

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rdquo ldquo

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mit

pcp

rdquo1

40

03

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23

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75

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up

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at

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re

for

pa

tie

nt

up

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a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

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on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 12: Emergency Department Status Boards: A Case Study in Information

50 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Len

gth

of

sta

y t

ime

sin

ce

xx

x

pa

tie

ntrsquo

s in

form

ati

on

en

tere

d a

t tr

iag

e

Mo

st r

ece

nt

pa

tie

nt

xx

Ast

eri

sks

ma

rk p

ati

en

t

acc

ess

ed

th

at

the

use

r la

st

acc

ess

ed

in s

yste

m

Pa

tie

nt

care

d f

or

by

no

n-E

D

xx

xx

OB

SB

RD

or

INP

TB

RD

tea

m (b

oa

rdin

g o

r d

isp

laye

d in

a b

lue

lab

el

ad

mit

ted

) in

dic

ate

s b

elo

w t

he

be

d n

am

e

pa

tie

nt

no

lon

ge

r in

ca

re

AD

MT

or

INP

T

of

ED

ph

ysic

ian

dis

pla

yed

inst

ea

d o

f

att

en

din

g p

hys

icia

n

na

me

Act

ion

ab

le o

r

Ho

ve

r ca

teg

ori

es

ap

ply

on

ly t

o A

DM

T o

r IN

PT

Pa

tie

nt

info

rma

tio

n c

alle

d

xx

xP

ho

ne

ico

n

in b

y p

rim

ary

ph

ysic

ian

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

ed

ce

ll w

as

red

ora

ng

e

yello

w g

ree

n b

lue

or

gra

y (i

f n

o a

cuit

y

sele

cte

d)

Typ

e o

f co

mm

en

tx

ba

rx

Re

d g

ree

n y

ello

w p

urp

le

gra

y b

lue

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lore

d b

ar

to le

ft o

f co

mm

en

t ce

ll

(co

rre

spo

nd

ing

to

typ

e

of

com

me

nt)

on

ly if

th

e

mo

st r

ece

nt

com

me

nt

an

d it

wa

s p

ick-

sele

cte

d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

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vio

us

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anto

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mn

wit

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att

en

din

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ssig

ne

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d s

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of

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ials

in

na

me

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lum

n (M

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rna

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(E) o

r in

itia

ls

xx

xx

xx

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sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

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2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

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on

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ga

rdin

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ldquo2

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-de

live

ryrdquo

(2 m

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21

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20

01

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0

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fte

n q

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rtin

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rsP

osi

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e o

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eg

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ve

ind

ica

tors

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ldquondash L

OC

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ss o

f co

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ss)

15

00

10

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7

are

re

lev

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t to

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no

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Pre

sum

ed

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gn

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sP

resu

me

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au

se o

f p

ati

en

t p

rob

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ldquoAst

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ardquo

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idn

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Sto

ne

rdquo1

97

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80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

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by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 13: Emergency Department Status Boards: A Case Study in Information

Emergency Department Status Boards in Transition 51

Tri

ag

e a

cuit

yx

xB

ed

ce

ll w

as

red

ora

ng

e

yello

w g

ree

n b

lue

or

gra

y (i

f n

o a

cuit

y

sele

cte

d)

Typ

e o

f co

mm

en

tx

ba

rx

Re

d g

ree

n y

ello

w p

urp

le

gra

y b

lue

co

lore

d b

ar

to le

ft o

f co

mm

en

t ce

ll

(co

rre

spo

nd

ing

to

typ

e

of

com

me

nt)

on

ly if

th

e

mo

st r

ece

nt

com

me

nt

an

d it

wa

s p

ick-

sele

cte

d

Use

rna

me

of

seco

nd

x

xx

x

ass

ign

ed

nu

rse

Vit

al s

ign

info

rma

tio

n

xx

xx

Lett

er

V is

co

lore

d r

ed

is a

va

ilab

le o

n

yello

w o

r b

lue

co

lor

oth

er

scre

en

de

pe

nd

s o

n v

alu

es

Zo

ne

s fo

r p

rov

ide

r x

x

ass

ign

me

nt

to p

ati

en

ts

Ass

ign

ed

be

d a

rea

an

d

xx

xx

xx

roo

m n

um

be

r (E

)

roo

m n

um

be

r (M

)

Ca

re P

lan

Ord

ers

x

xx

xx

xx

xx

xx

Co

lor-

cod

ed

nu

mb

ers

(E)

Dis

po

siti

on

(se

e

ma

gn

eti

c cl

ips

ho

ldin

g

Ta

ble

4 f

or

de

tails

)p

ap

er

EK

G f

or

ph

ysic

al

ha

nd

off

of

rep

ort

s o

r

pa

tie

nt

na

me

sti

cke

rs

tap

ed

on

EK

G

stic

kers

(M)

Ch

ief

com

pla

int

xx

xx

xx

info

rma

tio

n (s

ee

Ta

ble

2 f

or

ad

dit

ion

al d

eta

ils)

Co

nti

nu

ed n

ext p

ag

e

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 14: Emergency Department Status Boards: A Case Study in Information

52 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

1 (

con

tin

ue

d)

Ma

nu

al S

yst

em

Ele

ctro

nic

Sy

ste

m

Info

rma

tio

n T

ype

an

d

Ad

dit

ion

al N

ote

s

De

scri

pti

on

or

Co

lor

Fo

nt

Use

Pa

tie

ntrsquo

s a

ge

xx

xx

xx

Pa

tie

ntrsquo

s g

en

de

rx

xx

xx

xT

he

lett

er

F M

O o

r U

(fe

ma

le m

ale

oth

er

un

kno

wn

) (E

) t

he

sym

bo

ls f

or

ma

le o

r

fem

ale

(M)

Pa

tie

ntrsquo

s fu

ll n

am

e (E

)

xx

xx

xx

pa

tie

ntrsquo

s la

st n

am

e a

nd

som

e f

irst

na

me

s (M

)

Ro

om

se

t u

p f

or

pe

dia

tric

sx

xx

xx

Ro

om

na

me

(E) o

r re

d b

ox

aro

un

d r

ow

s (M

)

Ro

om

sta

te (E

MP

TY

x

xx

xx

xx

Ro

w is

pa

le y

ello

w (E

)

HO

USE

KEE

PIN

G

wo

rds

line

run

acr

oss

th

e

Ne

ed

s B

ed

)co

lum

ns

for

the

ro

w (M

)

Sa

me

na

me

ale

rtx

xx

xx

Ico

n (E

) or

ma

gn

et

(M)

Use

rna

me

(E) o

r fi

rst

na

me

x

xx

xx

xx

cod

e o

f th

e n

urs

e (M

)

Location Outside of Matrix Form

Marker (handwritten)

Magnet

Drawn Symbols

Automatically Filled

AlphanumericKBD Symbol

Typed

PickedSelected

AlphanumericKBD Symbol

StickiesNotepad

Icons

Other

Actionable

Hover

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

r in

itia

ls o

f x

xx

xx

xx

xU

sern

am

e b

old

(E)

add

itio

nal

pre

vio

us

ldquoph

anto

mrdquo

colu

mn

wit

h

att

en

din

g a

ssig

ne

dse

con

d s

et

of

init

ials

in

na

me

co

lum

n (M

)

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

ssig

ne

d

resi

de

nt

ph

ysic

ian

Use

rna

me

(E) o

r in

itia

ls

xx

xx

xx

x

sym

bo

ls o

f th

e a

tte

nd

ing

ph

ysic

ian

(M)

Use

rna

me

(E) o

r th

e in

itia

ls

xx

xx

x

sym

bo

l (M

) of

ass

ign

ed

me

dic

al s

tud

en

t

Zo

ne

fo

r n

urs

e a

ssig

nm

en

t x

xx

xC

olo

r o

r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

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en

tin

pa

tie

nt

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ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

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MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

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ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

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on

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eq

ue

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rem

ind

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r

act

ivit

ies

fo

llow

-up

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nsu

lt

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UR

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y 1

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e b

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ed

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alu

ate

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tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

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To

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Typ

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on

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lect

ron

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ruct

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Xra

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it O

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Te

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P 1

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-14

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r 1

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2)

Te

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NR

gt 1

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K 2

9rdquo

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01

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16

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(blo

od

te

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Tra

nsp

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re

ad

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be

ldquoT

ran

spo

rt C

Trdquo

00

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nsp

ort

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a

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tie

nt

tra

nsp

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te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

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ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 15: Emergency Department Status Boards: A Case Study in Information

Emergency Department Status Boards in Transition 53

Use

rna

me

(E) o

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r Z

p

ort

ion

of

the

to p

ati

en

tsb

ed

ass

ign

me

nt

ie

ldquoSO

UT

H B

lue

51

rdquo o

r

ldquoWE

ST

08

R-(

Z3

)rdquo (E

)

gre

en

lin

es

sep

ara

tin

g

the

be

ds

into

zo

ne

s (M

)

No

tes

ldquoPic

ked

se

lect

ed

rdquo in

dic

ate

s th

at

en

trie

s co

uld

be

pic

ked

an

d s

ele

cte

d w

ith

th

e m

ou

sek

eyb

oa

rd ldquo

Sti

ckie

sn

ote

pa

drdquo

refe

rs t

o a

n ic

on

on

th

e e

lect

ron

ic

bo

ard

th

at

led

to

ad

dit

ion

al d

ata

ldquoA

ctio

na

ble

rdquo m

ea

ns

tha

t th

e e

ntr

y co

uld

be

clic

ked

or

sele

cte

d f

or

furt

he

r d

ata

en

try

or

info

rma

tio

n ldquo

Ho

ve

rrdquo m

ea

ns

tha

t a

dd

itio

na

l

info

rma

tio

n w

as

av

aila

ble

if t

he

mo

use

ho

ve

red

ov

er

pa

rt o

f th

e e

ntr

y S

ha

de

d c

ells

ind

ica

te t

ha

t th

e e

ntr

y w

as

no

t fo

un

d f

or

tha

t ty

pe

of

tech

no

log

y

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 16: Emergency Department Status Boards: A Case Study in Information

On the electronic board colors were associated with a variety of automatedflags or alerts For instance the background of the room number was color-codedto indicate triage acuity (the medical urgency of the chief complaint) and smallcolored bars (adjacent to the cell borders) were used to show that particular com-ment types had been entered that particular chief complaints were entered orthat some additional information screens had been accessed

The electronic system provided additional functionality in the form of items orentire cells that could be hovered over or clicked Of the 18 cells or items that hadhover capabilities only 9 provided additional relevant details including the fullnames of caregivers a link to additional patient details the categories for length-of-stay warnings (eg long gt 6 hr) definitions of codes in the Custom columnand values for patient vital signs The remaining 9 either provided the name of acolor associated with an icon (eg ldquoredrdquo when the mouse hovered over a red bar)or a text label for an icon or symbol (eg ldquoName Alertrdquo for the name alert icon)Additionally 19 items could be selected Clicking the items either selected thepatient (8 instances) provided a link to another screen with additional details (5instances) caused a care provider to be assigned or another screen to displaydepending on the situation (5 instances) or caused the same name alert to beremoved (1 instance) (Note that counts from Table 1 are higher because multipleitems in cells with hoverclick capabilities may be listed separately if they pro-vided different types of information)

Chief Complaint AnalysesA primary function of both the manual and electronic whiteboards is to provide

information about the reasons for a patientrsquos visit to the emergency department (chiefcomplaints) Chief complaints are provided by patients to triage nurses during thetriage process In the manual system a coordinating ED nurse (the charge nurse)copied the chief complaint information from the triage nursersquos chief complaint fieldon the paper chart onto the ED whiteboard at the time the patient was brought fromtriage to the ED treatment area In the electronic system the triage nurse entered thechief complaint into the patient-tracking display directly and this information wasautomatically displayed when the patient was moved to the treatment area

We analyzed several aspects of the chief complaints entered in both systemstheir syntactic variability the functional content of the information provided inthe chief complaint field of the status board and the degree to which differentinformation types were represented across the two types of systems

Chief Complaint Syntactic Analysis Both the manual and electronic status boardsallow entries to be written as free text Additionally the electronic system had anautocomplete feature that provided suggested text (standard chief complaints)based on the beginning characters that were typed To understand the degree towhich chief complaint entries were identical to standard chief complaints differedbecause of abbreviations or typographical errors or differed because of the con-tent of information presented we analyzed the words and syntax used to enterchief complaint information Chief complaint entries were inspected to identify

54 Journal of Cognitive Engineering and Decision Making Spring 2010

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

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ate

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r P

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en

t

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nu

al

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ctro

nic

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an

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Typ

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efi

nit

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mp

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lect

(1

08

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tie

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)(8

0 P

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ts)

Ele

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Ale

rtS

pe

cia

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rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

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Arr

iva

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Me

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ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

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)2

00

02

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ED

Co

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re

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ad

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to

ho

spit

al)

2

00

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0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

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me

Vis

it is

pla

nn

ed

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d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

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lde

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sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 17: Emergency Department Status Boards: A Case Study in Information

(a) identical versus unique entries (b) entries that are clinically identical exceptfor syntactic variations (eg abbreviations) and (c) chief complaints that repre-sented a general type of problem with some additional information or modifierFor example ldquoChest painrdquo ldquoCHEST PAINrdquo ldquoCHST PNrdquo and ldquoCHST Pain wSOBrdquo arefour original entries in the chief complaint column Here the words chest pain arewritten in three syntactically different ways The fourth entry adds a qualifier (ldquowithshortness of breathrdquo) but refers to the same general category of complaint (ldquochestpainrdquo) Thus there are four original entries two variations (chest pain and chestpain with shortness of breath) and one general chief complaint (ldquochest painrdquo)

As seen in Table 2 there were more unique chief complaints per patient forthe manual than for the electronic system Per-patient ratios were similar whensyntactic variations (abbreviations fonts spellings) were removed These entriescorresponded to 06 general chief complaints per patient for the manual and 045entries per patient for the electronic system Thus across all three measures therewere 14 times as many unique entries per patient in the manual versus the elec-tronic system 15 times as many entries controlled for syntactic variation and 13times as many general chief complaints in the manual system compared to theelectronic system That is the variability appeared to be caused by actual differ-ences in the presenting conditions of the patients (general chief complaints) ratherthan the manner (manual or typing) in which information was entered

One might have expected that the presence of the autocomplete feature wouldhave resulted in greater consistency in entries in the electronic as opposed to themanual system However the similarity across these ratios indicates that the elec-tronic whiteboard did not seem to provide greater control or enforce greater con-sistency in entries than did the manual board This interpretation is substantiatedby an additional analysis that was performed regarding the degree to which entriesin the electronic board could have been generated using autocomplete Only 45of entries were identical to autocomplete entries indicating that in more than halfthe cases nurses were overriding the autocomplete function to enter free text(Note that this percentage represents an upper bound It is possible that stafftyped in text that was identical to autocomplete text)

Chief Complaint Content Analysis Content analysis of the chief complaint fieldsrevealed a rich array of functional information types presented as a chief complaint

Emergency Department Status Boards in Transition 55

TABLE 2 Syntax Analysis of Chief Complaint Entries

Frequency Rate Per Patient

Manual Electronic

Manual Electronic (105 Patients) (80 Patients)

Syntactically unique entries 108 58 103 073

Identical entries syntax variations excluded 105 52 100 065

General complaint categories 63 36 060 045

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

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mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

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D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

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rog

ress

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rou

gh

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T S

can

(wit

h a

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31

96

41

76

09

41

87

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gre

sscl

inic

al w

ork

up

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nh

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n c

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s d

on

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t 7

30

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lan

ne

d

Be

d n

um

be

r o

r a

rea

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ast

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2Lrdquo

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10

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n h

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it O

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up

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at

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re

for

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tie

nt

up

on

a

dm

issi

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Te

am

De

tails

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r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

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urs

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50

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r 1

69

2)

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gt 1

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K 2

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40

01

10

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16

00

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od

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Tra

nsp

ort

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be

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ran

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rt C

Trdquo

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03

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nsp

ort

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a

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nt

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nsp

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r p

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du

re

to C

T)

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isp

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nd

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lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 18: Emergency Department Status Boards: A Case Study in Information

In addition to patient-reported symptoms and their location on the body the chiefcomplaint field included information such as past medical history hypothesizeddiagnoses and the mechanism of injury (eg motor vehicle accident) Fourteen cat-egories were identified (see Table 3 for definitions and examples) For the most partthese categories were represented in both the manual and electronic systems how-ever the frequency of representation indicated differences As indicated in Table 3ED staff were 26 times as likely (on a per-patient basis) to note ldquosignsrdquo (informationthat could be measured through tests or observation such as heart rate) in the man-ual compared with the electronic board twice as likely to note a presumed diag-noses 18 times as likely to note the mechanism of injury and twice as likely toindicate medical history information on the manual board

In contrast complaints on the electronic board were more likely to include infor-mation regarding patient-reported symptoms In several cases categories of informa-tion present in the manual board chief complaint field were not represented in thatfield on the electronic board This may reflect a subtle difference between normativeand empirical uses of the concept of chief complaint between work as imagined andwork as performed Normatively the chief complaint has been considered to be thepatientrsquos actual words (eg ldquofeeling weakrdquo) hence the predominance of symptoms inthe pick-lists and autocomplete lists of the electronic system But empirically clini-cians commonly capture not the patientrsquos exact words but their interpretive catego-rization of the patientrsquos problem (eg ldquotachycardiardquo) hence the increased prevalenceof diagnoses and signs in manual status board and free-text entries

Finally we analyzed the degree of change in the chief complaint entries over timeA higher percentage of whiteboard patients (95) showed changes made to the chiefcomplaint field during the course of the patientrsquos stay (additional details clarifica-tions or treatmentdisposition-related information) compared with only 00125 ofpatients in the electronic case This finding suggests that the chief complaint portionof the whiteboard was used more dynamically in the manual case

Workflow-Related Field AnalysisSimilar content analyses were performed for columns related to workflow and

patient care We selected columns to compare across systems with similar func-tions for the ED staff such as providing information about plans for patient treat-ment during the ED stay needs for tests or transportation to other hospital areasor plans for discharge or hospital admission On the manual board we analyzedentries from the Disposition column along with the Diet column (in which therewere only a few entries) For example during a patientrsquos stay in the ED caregiverscould add or change information in the Disposition column to indicate that a testwas needed (eg write ldquoEKGrdquo followed by a small square checkbox) indicate thetest was completed (put a check in the box) and indicate that a consulting physi-cian had been called

On the electronic board we analyzed entries in the Comments column (whichaccepted free text as well as click-and-select phrases) the Disposition column(which provided an alphanumeric code indicating the patientrsquos disposition such

56 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

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ir F

req

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oss

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nt

Te

chn

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gie

s

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ate

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r P

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t

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ctro

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nit

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mp

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(1

08

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)(8

0 P

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rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

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rgie

s)

Arr

iva

l mo

de

Me

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ED

ldquoME

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rdquo (i

n-h

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2

00

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(pa

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De

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Vis

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Late

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)1

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Loca

tio

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tio

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inrdquo

64

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De

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inju

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ldquoF

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VC

rdquo (M

oto

r v

eh

icle

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sh)

17

70

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urr

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Me

dic

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isto

ryIn

form

ati

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ga

rdin

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ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 19: Emergency Department Status Boards: A Case Study in Information

Emergency Department Status Boards in Transition 57

TA

BLE

3 C

ate

go

rie

s o

f C

hie

f C

om

pla

ints

an

d T

he

ir F

req

ue

ncy

Acr

oss

Dif

fere

nt

Te

chn

olo

gie

s

Fre

qu

en

cyR

ate

Pe

r P

ati

en

t

Ma

nu

al

Ele

ctro

nic

M

an

Ra

te

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lE

lect

(1

08

Pa

tie

nts

)(8

0 P

ati

en

ts)

Ele

c R

ate

Ale

rtS

pe

cia

l ale

rts

to c

are

giv

ers

(eg

ldquoL

AT

EX

rdquo2

00

02

00

0ndash

alle

rgie

s)

Arr

iva

l mo

de

Me

cha

nis

m o

f a

rriv

al t

o t

he

ED

ldquoME

RT

rdquo (i

n-h

osp

ita

l te

am

)2

00

02

00

0ndash

ED

Co

ord

ina

tio

nW

ork

re

qu

est

s m

ov

em

en

t

ldquoAD

MIT

TE

Drdquo(

ad

mit

ted

to

ho

spit

al)

2

00

02

00

0ndash

dis

po

siti

on

pla

ns

ldquoEK

Grdquo

(pa

tie

nt

ne

ed

s a

n E

KG

)

De

sire

d v

isit

ou

tco

me

Vis

it is

pla

nn

ed

an

d e

xpre

sse

d a

s ldquoS

titc

h r

em

ov

alrdquo

ldquoN

ee

ds

Rx

Re

fillrdquo

52

00

50

03

16

7

an

ou

tco

me

Late

ralit

y D

esc

rip

tio

n o

f si

de

of

bo

dy

limb

ldquoL

Sh

ou

lde

r In

jrdquo (L

eft

sh

ou

lde

r in

jury

)1

07

00

90

09

1

aff

ect

ed

Loca

tio

nD

esc

rip

tio

n o

f b

od

y p

art

aff

ect

ed

ldquoBa

ck H

ip P

ain

rdquo ldquo

fla

nk

pa

inrdquo

64

51

05

90

64

09

2

Me

cha

nis

m o

f in

jury

De

scri

pti

on

of

ho

w t

he

inju

ry(i

es)

ldquoF

allrdquo

ldquoM

VC

rdquo (M

oto

r v

eh

icle

cra

sh)

17

70

16

00

91

78

occ

urr

ed

Me

dic

al h

isto

ryIn

form

ati

on

re

ga

rdin

g p

ast

ldquo2

m p

-de

live

ryrdquo

(2 m

on

ths

21

00

20

01

20

0

me

dic

al h

isto

ry (o

fte

n q

ua

lifyi

ng

p

ost

-de

live

ry)

a s

ymp

tom

or

dia

gn

osi

s)

Pe

rtin

en

t in

dic

ato

rsP

osi

tiv

e o

r n

eg

ati

ve

ind

ica

tors

th

at

ldquondash L

OC

rdquo (n

o lo

ss o

f co

nsc

iou

sne

ss)

15

00

10

06

01

7

are

re

lev

an

t to

a d

iag

no

ses

Pre

sum

ed

dia

gn

ose

sP

resu

me

d c

au

se o

f p

ati

en

t p

rob

lem

ldquoAst

hm

ardquo

ldquoK

idn

ey

Sto

ne

rdquo1

97

01

80

09

2

Pri

ma

ry s

ymp

tom

Co

mp

lain

t d

esc

rib

ed

by

pa

tie

nt

ldquoCh

est

pa

inrdquo

ldquoS

ho

rtn

ess

of

Bre

ath

rdquo4

84

80

44

06

00

73

Pro

ble

m

Ge

ne

ral d

esc

rip

tio

n o

f p

rob

lem

ldquoAn

kle

inju

ryrdquo

ldquoD

en

tal p

rob

lem

rdquo1

06

00

90

08

11

3

Ru

le o

ut

dia

gn

ose

sP

oss

ible

dia

gn

ose

s th

at

sho

uld

be

ldquoR

O M

Irdquo (r

ule

ou

t h

ea

rt a

tta

ck)

ldquoR

O

77

00

60

09

06

7

rule

d o

ut

(oft

en

a s

et

of

PN

Ardquo

(ru

le o

ut

pn

eu

mo

nia

)

dif

fere

nti

al d

iag

no

ses)

Sig

ns

Info

rma

tio

n g

ath

ere

d t

hro

ug

h

ldquoBlo

od

y S

too

lrdquo ldquo

Incr

ea

sed

he

art

ra

terdquo

39

11

03

60

14

25

7

ob

serv

ati

on

su

ch a

s la

b v

alu

es

vit

al s

ign

s o

r cl

inic

al o

bse

rva

tio

ns

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

Th

eir

Fre

qu

en

cy A

cro

ss D

iffe

ren

t T

ech

no

log

ies

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Ad

dit

ion

al

Pa

tie

nt

ha

s sp

eci

fic

Re

pre

sen

ted

by

a

00

02

20

00

00

30

00

info

rma

tio

n

pro

toco

ls o

n f

ile

ldquono

tep

ad

rdquo ic

on

(eg

ty

pe

s o

f

me

dic

ati

on

to

be

giv

en

)

Ad

mis

sio

n

Sta

tus

wh

en

pa

tie

nt

ldquoAd

mit

HM

Urdquo

rdquoAd

mit

5

13

31

62

20

82

03

22

56

pro

cess

g

oe

s th

rou

gh

m

ed

icin

erdquo

sta

tus

ad

mis

sio

n p

roce

ss

Ale

rtS

pe

cia

l ale

rts

to

ldquoHip

pa

filt

er

resp

pre

crdquo

00

03

30

00

00

40

00

care

giv

ers

(ne

ed

s sp

eci

al

resp

ira

tor)

Be

d

Sta

tus

of

the

ED

be

d

ldquo6R

wh

en

cle

an

ed

rdquo0

00

11

00

00

01

00

0

sta

tus

ED

ass

ign

ed

Be

d s

tatu

s

Sta

tus

of

the

po

ten

tia

l ldquo5

14

RE

AD

Yrdquo

(be

d

33

58

16

00

50

24

02

1

Inp

ati

en

tin

pa

tie

nt

ass

ign

ed

is

re

ad

y o

n in

pa

tie

nt

un

it 5

14

) ldquo

Aw

ait

ing

be

d a

ssig

nm

en

trdquo

Clin

ica

l C

linic

al d

eta

ils o

f ldquoC

T N

eck

rdquo ldquo

MR

I1

93

0rdquo

95

39

03

27

11

53

10

41

47

wo

rku

p

pla

nn

ed

lab

s

(pa

tie

nt

sch

ed

ule

d

pla

nim

ag

ing

te

sts

fo

r M

RI a

t 6

30

PM

)

me

dic

ati

on

s r

eq

ue

sts

or

rem

ind

ers

fo

r

act

ivit

ies

fo

llow

-up

s

Co

nsu

lt

Co

nsu

lt s

pe

cia

lists

wh

o

ldquoNE

UR

Ordquo

(Ne

uro

log

y 1

50

07

70

24

01

02

40

req

ue

sth

av

e b

ee

n a

ske

d t

o

con

sult

re

qu

est

ed

)

ev

alu

ate

pa

tie

nt

in t

he

ED

Co

nti

nu

ed n

ext p

ag

e

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

4 (

con

tin

ue

d)

Fre

qu

en

cy

Ra

te p

er

Pa

tie

nt

To

tal

Ma

nu

al

Ele

ctro

nic

M

an

ua

l

Typ

eD

efi

nit

ion

Exa

mp

leM

an

ua

lC

ust

om

Dis

po

siti

on

Co

mm

en

tsE

lect

ron

ic(6

2 P

ati

en

ts)

(68

Pa

tie

nts

)E

lect

ron

ic

Die

tP

ati

en

t-sp

eci

fic

die

t ldquoD

iet-

LOW

SO

DIU

Mrdquo

10

02

42

40

02

03

50

06

inst

ruct

ion

s D

isp

osi

tio

nD

isp

osi

tio

n in

stru

ctio

ns

ldquoAd

mit

ted

rdquo

28

28

57

59

00

45

13

20

34

aft

er

ED

tre

atm

en

t ldquoD

isch

arg

e

com

ple

tio

nco

mp

lete

rdquoE

mp

ha

sis

Use

of

spe

cia

l ch

ara

cte

rs

ldquoMia

mi-

J C

olla

r D

Crdquo

10

00

00

02

00

0-

to e

mp

ha

size

att

en

tio

n

to in

form

ati

on

Oth

er

Po

ssib

le lo

cati

on

of

ldquoOp

tho

Clin

icrdquo

00

03

03

00

00

04

40

00

pa

tie

nt

pa

tie

nt

oth

er

tha

n

(op

tho

mo

log

y cl

inic

)

loca

tio

na

ssig

ne

d E

D b

ed

ldquoTra

nsp

ort

Xra

yrdquoP

lan

P

rog

ress

th

rou

gh

C

T S

can

(wit

h a

1

09

42

31

96

41

76

09

41

87

pro

gre

sscl

inic

al w

ork

up

pla

nh

an

d-d

raw

n c

he

ckb

ox)

ldquol

ab

s d

on

e a

t 7

30

rdquoP

lan

ne

d

Be

d n

um

be

r o

r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 20: Emergency Department Status Boards: A Case Study in Information

as admission to the hospital transfer to another hospital or discharge home) anda custom area displaying colored dots with numeric labels (ldquocustom codesrdquo) cor-responding to a wide variety of orders or qualifying information regarding thepatient (eg number of visitors allowed requests for EKGs communications regard-ing admissions potential security concerns)

Note that the software allowed definitions of the custom codes to be configuredby individual hospitals however the format of the codes (numbered dots) wasfixed Often codes in the custom area duplicated information in the Disposition orthe Comments column however because these could be entered independently(by different staff) and because some staff may have relied on information in onecolumn whereas other staff relied on another all entries were coded and countedseparately Similar to the manual system caregivers could enter information in thecomments area (eg indicate the need for an EKG and its completion) or selectcustom codes Because of space restrictions only the three most recent commentsappeared on the primary screen (and thus were analyzed) also comments werelimited to a set character length Information in the Disposition column appearedautomatically when other aspects of the patientsrsquo record was changed

As with the chief complaints column content analysis of the dispositioncom-ments fields indicated that these areas of both the manual and electronic boardswere used to support a variety of functions including those related to the careplans for the patient and the status of those plans with respect to processes of hos-pital admission and discharge (see Table 4) In both systems for some patientsinformation had not yet been entered into these fields Thus these data wereavailable for 62 patients in the manual case and 68 in the electronic case

Across both systems 17 functional categories of information were identified(12 for manual 16 for electronic) Although both systems were used to representa wide range of information the usage patterns were very different across the twosystems Compared with the electronic system (on a per-patient basis) the man-ual system showed 575 times more information regarding the hospital service towhich the patient would be admitted 26 times the information regarding the sta-tus of the admission process 24 times the information regarding consult requests19 times as much information regarding progress through the patientsrsquo clinicalworkup plan 15 times as much information regarding the clinical care plan itselfand approximately the same amount of information regarding patient movementto new beds within the ED

In contrast the electronic board showed more information regarding transportrequests and diet (with no entries in the manual board for transport and only oneentry for diet) 49 times the information regarding the status of in-patient beds foradmitted patients and almost 3 times the entries regarding disposition Most of thedisposition information on the electronic board was communicated through theCustom and Disposition columns (colored alphanumeric codes) rather thanthrough text entries shown in the Comments column In fact the manual boardhad five times as many disposition comments (text entries in the column) perpatient compared with the text comments area of the electronic board

58 Journal of Cognitive Engineering and Decision Making Spring 2010

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

ate

go

rie

s o

f D

isp

osi

tio

nC

om

me

nts

Info

rma

tio

n a

nd

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ss D

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ies

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dic

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to

be

giv

en

)

Ad

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Sta

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ldquoAd

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icin

erdquo

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ss

Ale

rtS

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rts

to

ldquoHip

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00

03

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40

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ers

(ne

ed

s sp

eci

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tor)

Be

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ign

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it 5

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) ldquo

Aw

ait

ing

be

d a

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en

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Clin

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0rdquo

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41

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s

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tie

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ing

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r M

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60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

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tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 21: Emergency Department Status Boards: A Case Study in Information

Emergency Department Status Boards in Transition 59

TA

BLE

4 C

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Ad

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60 Journal of Cognitive Engineering and Decision Making Spring 2010

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r a

rea

ldquoE

ast

21

rdquordquo1

2Lrdquo

90

64

10

01

50

15

10

0b

ed

p

ati

en

t is

ass

ign

ed

a

ssig

nm

en

tto

mo

ve

to

wit

hin

ED

Se

rvic

eD

eta

ils o

n h

osp

ita

l ldquoa

dm

it O

BS

rdquo ldquo

ad

mit

pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

will

ca

re

for

pa

tie

nt

up

on

a

dm

issi

on

Te

am

De

tails

fo

r ca

reg

ive

r ldquoN

P 1

69

2 6

-14

NP

rdquo (n

urs

e

10

50

50

02

00

70

29

tea

m c

oo

rdin

ati

on

pra

ctit

ion

er

tea

m

fro

m u

nit

6-1

4 a

va

ilab

le

via

pa

ge

r n

um

be

r 1

69

2)

Te

st r

esu

lts

Lab

an

d t

est

re

sult

s ldquoI

NR

gt 1

25

K 2

9rdquo

40

01

10

06

00

16

00

(blo

od

te

st r

esu

lts)

Tra

nsp

ort

P

ati

en

t is

re

ad

y to

be

ldquoT

ran

spo

rt C

Trdquo

00

03

03

00

00

04

40

00

req

ue

sts

tra

nsp

ort

ed

to

a

(pa

tie

nt

tra

nsp

ort

ed

te

st o

r p

roce

du

re

to C

T)

Cu

sto

m D

isp

osi

tio

n a

nd

Co

mm

en

ts e

ntr

ies

are

to

tale

d in

th

e T

ota

l Ele

ctro

nic

co

lum

n

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 22: Emergency Department Status Boards: A Case Study in Information

60 Journal of Cognitive Engineering and Decision Making Spring 2010

TA

BLE

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n h

osp

ita

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it O

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rdquo ldquo

ad

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pcp

rdquo1

40

03

30

23

00

45

75

gro

up

th

at

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ca

re

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pa

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De

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r ldquoN

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on

pra

ctit

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2)

Te

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Lab

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ts e

ntr

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to

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Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 23: Emergency Department Status Boards: A Case Study in Information

Discussion

These analyses demonstrate the changes in information content and usage thatcan occur as information systems shift in formmdashin this case from a manual pri-marily handwritten system to an electronic system with some automated capabili-ties We found that the set of categories and functions of information content weregenerally similar across the two technologies This was true in both the comprehen-sive analysis and the more detailed analysis of the chief complaint and dispositioncomments areas

There was an attempt to mimic the matrix form of the manual board in thedesign of the electronic display as well as to include similar fields or categories ofinformation However despite the attempt to mimic the surface feature of themanual system the nature of the two technologies differed The use of font (hand-written to typographic) color and symbols changed and there were additionalcolumns and the introduction of icons codes and color indicators that mightmake it more difficult for clinicians to find or understand the information presentAnnotations were also restricted to be entered in particular cells and in somecases they were limited to a set of prespecified options These changes reducedthe flexibility with which the system could be adapted to situational demandsAdditionally the means of interaction was fundamentally different Instead ofdirect freehand input with a marker clinicians had to find an unused terminallog in and type or select inputs

Thus despite the similarities in the surface form of the two technologies therewere differences in their underlying capabilities These differences were reflectedin the analyses performed which revealed important changes in the use of the sys-tem that have the potential to affect work in the emergency department In partic-ular the electronic system did not on the primary and most directly accessibledisplay provide a resource for clinicians to track their individual workflowPhysicians could no longer use symbols to serve as reminders to themselves and oth-ers of the status of the standard sequence of patient interactions (eg hearing abouta case from a trainee meeting and evaluating a patient and completing the patientrsquoschart) In fact as noted during an observational phase of our research (Pennathuret al 2007) some physicians started making notes to track their patient tasksafter the manual system was replaced by the electronic system Because these werepersonal notes often carried in the physiciansrsquo pockets they were not visible to otherstaff This ldquotask-tailoringrdquo (Cook amp Woods 1996) essentially reduced the poten-tial for implicit communication and task coordination among care providers becausepreviously public information was now private The use of manual ED statusboards to document this process has been noted in multiple ED settings (Wears ampPerry 2007) so this absence in the electronic system is likely to have an effect onwork across a range of EDs

Additionally we found that ED staff had exploited the flexibility inherent inthe manual whiteboard to add information outside the structured row-columnformat There were notations in the margins phantom columns added to the left

Emergency Department Status Boards in Transition 61

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 24: Emergency Department Status Boards: A Case Study in Information

of the first column and symbols drawn across multiple rows or columns Theseannotations represent adaptations of the technology to meet demands that werenot anticipated at the time the original display was constructed

The shift to electronic technology has fundamentally limited practitionersrsquo abil-ity to change the functionality of the information system in response to moment-to-moment or more general shifts in circumstances The electronic system did allowsome customization Providers could sort rows or individually shuffle hide or dis-play columns however desires for new columns could be met only through oftencostly and time-consuming software changes (if approved at all) and ad hoc nota-tions outside of the matrix format were impossible

A third overall change was the ability of the electronic system to automaticallyhighlight or fill in information Small colored bars cell color and font were usedto indicate or call attention to a variety of situations including prolonged lengthof stay or high-risk chief complaints Providing automatic alerts or indicators canimprove workload and safety if the indicators are meaningful and are carefullychosen to correspond to critical situations However the ease with which colorcoding symbols and font changes can be added to software may result in a prolif-eration of these alerts screen clutter and confusion

For instance on the studied displays a small vertical green bar on the edge of acell could indicate that a comment regarding patient transport is the most recentlyadded comment that the chief complaint requires special attention because aspectsare tracked to measure quality or that a specific detail screen has been accesseddepending on the column Note also that in addition to the one-to-many mappingof color to meaning the color coding did not correspond to known populationstereotypes (eg green to indicate ldquostartrdquo ldquosaferdquo or ldquoacceptable valuerdquo) Additionallycolor was not consistently used to indicate critical information or events (egcolor bars indicating a patient transport comment)

The analysis of chief complaint entry syntax indicated that there was not agreat deal of difference in the variability with which chief complaints were repre-sented in both systems variability was driven both by the presenting conditionsof the patients and differences in how those conditions were entered This issomewhat surprising because the electronic system included an autocompletefeature for the chief complaint field but only 45 of entries could have resultedfrom use of this feature Although standardizing entries may be an administrativegoal (eg to measure time for certain conditions to be treated) the staff did notuse the system in this way perhaps because they needed more flexibility than theautocomplete provided because of the cognitive effort to switch from typing tomonitoring and selecting the autocomplete entry (Higginbotham Bisantz SunmAdams amp Yik 2009 Koester amp Levine 1998) or because completion of auto-complete required using the mouse

For both areas we studied similar information categories were represented inboth technologies but with different frequencies For the chief complaint fieldthere was less variety in entry types in the electronic system For example entriesin the electronic system focused more on patient-reported symptoms (perhaps

62 Journal of Cognitive Engineering and Decision Making Spring 2010

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 25: Emergency Department Status Boards: A Case Study in Information

because autoentry data are almost exclusively symptoms) and less on other cate-gories of information such as potential diagnoses or mechanisms of injury Someimportant information was missing on the electronic displays For instance in themanual system nurses would signify allergies (particularly those that wouldlikely affect care for the condition being treated) in the chief complaint columnAllergy alerts were not shown on the primary electronic display but instead werelisted as part of a different patient information screen Thus critical informationrelevant to the patient condition at hand was no longer presented

Additionally we noted that the chief complaint information was changed moreoften in the manual compared with the electronic system Perhaps this was because itwas straightforward for staff to add or change information about the patientrsquos statuson the manual board as their understanding of the problem evolved whereas thefunction to change this field in the electronic system is easily accessed only during thetriage phase These results point to a reduction in the ability of the new system torepresent a range of informationmdashincluding critical safety informationmdashregardingpatient states including situations when more information is obtained

The differences in the dispositioncomments category frequencies as well asthe change to how physicians tracked their own work point to a dramatic changein the nature of the use of the status board In particular our results suggest thatthere was a shift from the board serving as a primary tool for clinical staff to com-municate coordinate and track aspects of medical care (eg the care plan planstatus admission status) to a tool used by other staff to communicate and tracksupport functions (eg transporting patients or delivering meals)

Importantly these changes were not driven by a wholesale change in the func-tions that were available in the new technology as we documented generally simi-lar capabilities in the two technologies Instead the changes in use seem to haveresulted from a combination of more subtle factors including the means of inter-action level of flexibility changes in information display format and loss of a fewkey functions For instance limited space was available for free-text entry in theelectronic system (only the three most recent comments could be displayed on themain display older comments had to be accessed on a different view) Entries onthe electronic system were restricted to text and keyboard symbols compared withthe ability to create customized lists figures and check boxes on the manualboard These changes combined with the loss of provider workflow-tracking capa-bility and the time it took to log in and enter text compared with freehand writingcould have shifted the use away from clinical planning and communication

Design ImplicationsThe results from this analysis point to a number of implications for the design of

information systems particularly those which are replacing existing technologiesFirst it is not sufficient to simply match the information fields available or the

overall format of the existing technology Having similar columns to or the samematrix formats as in the manual board was not sufficient to sustain current workpractices or to prevent unanticipated shifts in use

Emergency Department Status Boards in Transition 63

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 26: Emergency Department Status Boards: A Case Study in Information

Additionally support for tailorable andor flexible use that allows users toadapt the system as needs change in response to moment-by-moment demands orlonger-term changes is necessary In the case of the manual status boards the factthat information could be developed on the fly directly entered and flexibly dis-played supported the work Continued redesign of the manual artifact by theusers was supported by the fact that the manual whiteboard like the paper docu-ments described by Sellen and Harper (2003) afforded annotation and ldquotailorabil-ityrdquo Staff could write wherever they chose annotate the margins write acrosscolumns or rows or create new matrix elements (eg new columns) (For exam-ple in other observations of manual status board use we noted the invention andwidespread adoption of a new symbol indicating orders had been entered over arelatively short period)

Careful analyses are also required to identify all the important functions anddisplay features that must be supported as well as the effect of changing themethod of interaction with a system As noted earlier the loss or change of a fewkey functions (eg easy support of physician work flow customized lists andtracking of care plans) seemed to have shifted the use of the status board awayfrom clinical planning and communication The proliferation of automated col-ored alerts and codes also may have led to an information display that thoughdata dense did not clearly convey information supporting overall awareness ofthe ED or support planning and tracking activities related to a specific patientChanging the method of interaction from direct access to keyboard and terminal(combined with log-in requirements) also may have affected use by increasing thecost (in terms of time and effort) to enter annotate or change information

Limitations and Future ResearchAlthough the data analyzed in this study were drawn from one hospital

(potentially limiting the generalizability of the findings) the overall format infor-mation fields and typical uses of the status boards that we observed are consistentwith those documented in other EDs (Wears amp Perry 2007 Wears et al 2007)and other medical settings (Xiao 2005) To enhance generalizability data werecaptured in two different ED areas (running separate status boards) within thehospital Also the electronic status board we studied is the product of a nationalvendor of ED information systems with a large market share and is therefore rep-resentative of at least one type of commonly implemented system

In part to focus on the dynamic nature of information on the status boards(eg as seen in the changes to chief complaints) we collected data from 8-hr peri-ods rather than sampling across a longer time span It is possible that these peri-ods were idiosyncratic and thus not representative of the use of the status boardsgenerally Additionally we did not capture information about every patient treatedin the ED only those in the two largest adult treatment areas Also our data col-lection captured different numbers of patients across the two systems Howeverdata were not collected for either system during times of the year that were proneto known peak loads (eg summer trauma season or flu season) Finally data

64 Journal of Cognitive Engineering and Decision Making Spring 2010

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 27: Emergency Department Status Boards: A Case Study in Information

were collected on so-called typical days those with no unusual events (such as amass casualty incident) or unusual level of patient traffic either of which mighthave affected use of the boards

By focusing on only four periods we may have missed some instances ofinformation category use on one or the other of the systems because of the patientor care providers present Our analysis however did not indicate dramaticallydifferent uses between the two areas sampled for either the manual or the elec-tronic boards which would have indicated something out of the ordinary for oneof the periods or (given that the areas were staffed by different people) if differentstaff used the boards very differently

The analysis covered 185 patients across the two systems Future researchcould focus on changes in use of the status boards during critical incidents orcomparisons in usage of similar systems across different EDs

This analysis was limited to documenting aspects of the primary (patient list)view of the electronic status board This was chosen because it was the main overviewscreen displayed (on both desktop and large-screen monitors) and because it pro-vided the closest analogue to the manual status board Although this limited theextent to which we could evaluate all the implemented (and potential) functional-ity of the electronic system it is true that with both systems staff had access toinformation about patients through additional means such as paper charts andother hospital IT systems (eg radiology) An analysis of all these sources wasbeyond the scope of our study

We did not perform a usability evaluation of the electronic system (thoughsome of our findings are clearly related to issues that could be identified throughsuch an analysis such as the inconsistent use of color) A usability analysis of theelectronic system has been performed as part of a separate research effort (FairbanksGuarrera et al 2008 Fairbanks Karn et al 2008)

Conclusions

In conclusion this study examined in detail the type and frequency of infor-mation presented on two types on patient-tracking displays a manual whiteboardimplementation and a computerized implementation Although the format of theprimary electronic display was designed to be similar to the manual whiteboardand the categories of information that appeared in both systems were similar thefrequency with which types of information was present differed These changesrepresent a shift in use that was not explicitly anticipated or intended but thatreflects the underlying affordances of the two technologies

Designing supportive information technology goes beyond mimicking the sur-face features of current systems particularly when the affordances of those currentsystems differ substantially from those of the replacement technology (Sellen ampHarper 2003) The analysis performed here provides additional evidence thatmerely identifying the form and information fields present in a manual technologyis not sufficient input for design Cognitive engineering analyses (Bisantz amp Burns

Emergency Department Status Boards in Transition 65

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 28: Emergency Department Status Boards: A Case Study in Information

2008 Bisantz amp Roth 2008 Roth Patterson amp Mumaw 2002)mdashwhich focus onthe purposes processes and constraints of the ED work environment as well asthe goals activities and strategies of the various clinicians and staffmdashshould beperformed in order to identify the information and interactivity necessary to sup-port ED work

Acknowledgments

This study was supported in part by a grant from the Emergency MedicineFoundation of the American College of Emergency Physicians At the time of thestudy Rollin J Fairbanks was supported by a research training grant from theEmergency Medicine Patient Safety Foundation through the Society for AcademicEmergency Medicine

References

Aronsky D Jones I Lanaghan K amp Slovis C M (2008) Supporting patient care in theemergency department with a computerized whiteboard system Journal of the AmericanMedical Informatics Association 15 184ndash194

Aspden P Corrigan J M Wolcott J amp Erickson S M (Eds) (2004) Patient safety Achievinga new standard for care Washington DC National Academy Press

Berg M (1997) Rationalizing medical work Cambridge MIT PressBerg M (2004) Health information management Integrating information technology in health care

work London RoutledgeBisantz A M amp Burns C M (Eds) (2008) Applications of cognitive work analysis Boca Raton

FL CRC PressBisantz A M amp Ockerman J J (2002) Informing the evaluation and design of technology in

intentional work environments through a focus on artifacts and implicit theoriesInternational Journal of Human-Computer Studies 56 247ndash265

Bisantz A M amp Roth E M (2008) Analysis of cognitive work In D A Boehm-Davis (Ed)Reviews of human factors and ergonomics (Vol 3 pp 1ndash43) Santa Monica CA HumanFactors and Ergonomics Society

Button G amp Harper R H (1993) Taking the organization into account In G Button (Ed)Technology in working order Studies of work interaction and technology (pp 98ndash107) LondonRoutledge

Committee on Quality of Health Care in America (2001) Crossing the quality chasm A newhealth system for the 21st century Washington DC National Academy Press

Cook R I amp Woods D D (1996) Adapting to new technology in the operating room HumanFactors 38 593ndash613

Fairbanks R J Guarrera T K Karn K S Caplan S H Shah M N amp Wears R L (2008)Interface design characteristics of a popular emergency department information system InProceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp 778ndash782)Santa Monica CA Human Factors and Ergonomics Society

Fairbanks R J Karn K S Caplan S H Guarrera T K Shah M N amp Wears R L (2008)Use error hazards from a popular emergency department information system InProceedings of the Usability Professionalsrsquo Association 2008 International Conference [CD-ROM] Bloomingdale IL Usability Professionalsrsquo Association (UPA) Available fromhttpwwwupassocorgupa_storeconference_proceedings

66 Journal of Cognitive Engineering and Decision Making Spring 2010

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 29: Emergency Department Status Boards: A Case Study in Information

Glaser B amp Strauss A L (1967) The discovery of grounded theory Strategies for qualitativeresearch Chicago Aldine

Higginbotham D J Bisantz A M Sunm M Adams K amp Yik F (2009) The effect of con-text priming and task type on augmentative communication performance Augmentativeand Alternative Communication 25 19ndash31

Hutchins E (1997) Cognition in the wild Cambridge MIT PressKoester H H amp Levine S P (1998) Model simulations of user performance with word pre-

diction Augmentative and Alternative Communication 14 25ndash36Kohn L T Corrigan J M amp Donaldson M S (Eds) (1999) To err is human Building a safer

health system Washington DC National Academy PressLaxmisan A Hakimzada F Sayan O Green R amp Patel Z (2007) The multitasking clini-

cian Decision-making and cognitive demand during and after team handoffs in emergencycare International Journal of Medical Informatics 76 801ndash811

Mackay W E (1999) Is paper safer The role of paper flight strips in air traffic control ACMTransactions on Computer-Human Interaction 6 311ndash340

Nemeth C P OrsquoConnor M Nunnally M amp Cook R I (2007) Re-presenting reality Thehuman factors of heath care information In P Carayon (Ed) Handbook of human factorsand ergonomics in health care and patient safety (pp 439ndash455) Mahwah NJ Erlbaum

Pennathur P Bisantz A M Fairbanks R J Perry S Zwemer F amp Wears R L (2007)Assessing the impact of computerization on work practice Information technology in emer-gency departments In Proceedings of the Human Factors and Ergonomics Society 51st AnnualMeeting (pp 377ndash381) Santa Monica CA Human Factors and Ergonomics Society

Poon E Jha A Christino M Honour M Fernanopulle R Middleton B Newhouse JLeape L Bates D W Blumenthal D amp Kaushal R (2006) Assessing the level of healthcareinformation technology adoption in the United States A snapshot BMC Medical Informaticsand Decision Making 6 Retrieved December 23 2009 from httpwwwncbinlmnihgovpmcarticlesPMC1343543

Roth E M Patterson E S amp Mumaw R J (2002) Cognitive engineering Issues in user-centeredsystem design In J J Marciniak (Ed) Encyclopedia of software engineering (2nd ed pp163ndash179) New York Wiley

Sachs P (1995) Transforming work Collaboration learning and design Communications of theACM 38 37ndash44

Sellen A J amp Harper R H R (2003) The myth of the paperless office Cambridge MIT PressWears R L amp Perry S (2007) Status boards in accident and emergency departments Support

for shared cognition Theoretical Issues in Ergonomics Science 8 371ndash380Wears R L Perry S J Wilson S Galliers J amp Fone J (2007) Emergency department status

boards User-evolved artefacts for inter- and intra-group coordination Cognition Technologyand Work 9 163ndash170

Xiao Y (2005) Artifacts and collaborative work in healthcare Methodological theoretical andtechnological implications of the tangible Journal of Biomedical Informatics 38 26ndash33

Ann M Bisantz PhD is an associate professor of industrial and systems engineering at the

University at Buffalo The State University of New York Her research interests are in cognitive

engineering methods complex decision making and interface design in domains such as

health care and defense

Priyadarshini R Pennathur is a doctoral candidate in industrial and systems engineering at

the University at Buffalo She holds a bachelorrsquos and masterrsquos degree in computer science

and a masterrsquos in industrial engineering Her research interests are in understanding cogni-

tive artifacts and information transformation in work systems She has been involved in

Emergency Department Status Boards in Transition 67

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010

Page 30: Emergency Department Status Boards: A Case Study in Information

projects for designing and testing emergency department interfaces through simulation

techniques

Theresa K Guarrera is a doctoral student in industrial and systems engineering at the

University at Buffalo and a health project coordinator for the University of Rochester

Emergency Department Theresa has a BS degree in biomedical engineering Her research

includes evaluating patient-tracking systems used in the emergency setting for design and

usability purposes as well as considering interfaces between emergency medicine and radi-

ology imaging

Rollin J (Terry) Fairbanks MD MS is assistant professor of emergency medicine and of

community and preventive medicine at the University of Rochester He is also adjunct assis-

tant professor of industrial and systems engineering at the University at Buffalo His research

focuses on applying human factors engineering research techniques to the health care

domain His clinical practice is in the adult and pediatric emergency departments at the

University of Rochester Medical CenterStrong Memorial Hospital in Rochester New York

Shawna J Perry MD is director for Patient Safety System Engineering at Virginia

Commonwealth University Health Systems in Richmond Virginia and associate professor

associate chair for the Department of Emergency Medicine Perryrsquos primary research interest

is patient safety with an emphasis in human factorsergonomics and system failure She has

published widely on topics related to these areas as well as transitions in care the impact of

IT on clinical care and naturalistic decision-making

Frank Zwemer MD is section chief of emergency medicine at McGuire VAMC in Richmond

Virginia as well as associate chair in the Department of Emergency Medicine at Virginia

Commonwealth University He has implemented whiteboard and ED information systems

both in the private sector and in the Veterans Health Administration

Robert L Wears MD is a professor in the Department of Emergency Medicine at the

University of Florida and a visiting professor in the Clinical Safety Research Unit at Imperial

College London His interests lie in technical work studies joint cognitive systems and par-

ticularly the impact of information technology on safety and resilient performance

68 Journal of Cognitive Engineering and Decision Making Spring 2010