a systematic review of emergency department technology-based behavioral health interventions

CONSENSUS CONFERENCE FOLLOW-UP

A Systematic Review of EmergencyDepartment Technology-based BehavioralHealth InterventionsEsther K. Choo, MD, MPH, Megan L. Ranney, MD, MPH, Nitin Aggarwal, MD,and Edwin D. Boudreaux, PhD

AbstractObjectives: This systematic review evaluated the evidence for use of computer technologies to assessand reduce high-risk health behaviors in emergency department (ED) patients.

Methods: A systematic search was conducted of electronic databases, references, key journals, andconference proceedings. Studies were included if they evaluated the use of computer-based technologiesfor ED-based screening, interventions, or referrals for high-risk health behaviors (e.g., unsafe sex, part-ner violence, substance abuse, depression); were published since 1990; and were in English, French, orSpanish. Study selection and assessment of methodologic quality were performed by two independentreviewers. Data extraction was performed by one reviewer and then independently checked forcompleteness and accuracy by a second reviewer.

Results: Of 17,744 unique articles identified by database search, 66 underwent full-text review, and 20met inclusion criteria. The greatest number of studies targeted alcohol ⁄ substance use (n = 8, 40%), fol-lowed by intentional or unintentional injury (n = 7, 35%) and then mental health (n = 4, 20%). Ten of thestudies (50%) were randomized controlled trials; the remainder were observational or feasibility studies.Overall, studies showed high acceptability and feasibility of individual computer innovations, althoughstudy quality varied greatly. Evidence for clinical efficacy across health behaviors was modest, with fewstudies addressing meaningful clinical outcomes. Future research should aim to establish the efficacy ofcomputer-based technology for meaningful health outcomes and to ensure that effective interventionsare both disseminable and sustainable.

Conclusions: The number of studies identified in this review reflects recent enthusiasm about the poten-tial of computers to overcome barriers to behavioral health screening, interventions, and referrals totreatment in the ED. The available literature suggests that these types of tools will be feasible andacceptable to patients and staff.

ACADEMIC EMERGENCY MEDICINE 2012; 19:318–328 ª 2012 by the Society for Academic EmergencyMedicine

T he emergency department (ED) is well situated toplay a central role in identifying and addressingcritical high-risk health behaviors. ED patients

are more likely than the general U.S. population to reportrisky health behaviors, such as use of alcohol, drugs, andtobacco; involvement in violence; and unsafe sexual

ISSN 1069-6563 ª 2012 by the Society for Academic Emergency Medicine318 PII ISSN 1069-6563583 doi: 10.1111/j.1553-2712.2012.01299.x

From the Injury Prevention Center, Department of Emergency Medicine, Rhode Island Hospital, Warren Alpert Medical Schoolof Brown University (EKC, MLR), Providence, RI; the Department of Emergency Medicine, Vanderbilt University Medical Center(NA), Nashville, TN; and the Departments of Emergency Medicine, Psychiatry and Quantitative Health Science, University ofMassachusetts Medical School (EDB), Worcester, MA.Received September 6, 2011; revision received September 28, 2011; accepted September 28, 2011.The authors have no relevant financial information or potential conflicts of interest to disclose.Supervising Editor: Shariar Zehtabchi, MD.Address for correspondence and reprints: Esther K. Choo, MD, MPH; e-mail: [email protected]’s note: Academic Emergency Medicine (AEM) highlights articles that follow up on the research agendas created at the Jour-nal’s annual consensus conferences. This article relates to the 2009 AEM consensus conference, ‘‘Public Health in the EmergencyDepartment: Surveillance, Screening, and Intervention.’’ All prior consensus conference proceedings issues are available open-access at http://www.aemj.org, and authors interested in submitting a consensus conference follow-up paper should consult theauthor guidelines.

behavior.1–3 Many ED patients endorse more than one ofthese risky behaviors, placing them at even higher risk ofsubsequent illness and injury.4

The Society for Academic Emergency Medicine(SAEM) has recognized that emergency care ‘‘includespreventive and educational, as well as curative, medicalservice.’’5 However, there are attitudinal, cultural,administrative, educational, technological, and systemsbarriers to integrating behavioral health measures sothat they become a routine part of emergency care.6

Emergency physicians receive little training in theassessment of patients’ psychosocial or behavioralhealth risks or in the skills needed to address theseproblems.7 Many EDs struggle with long wait times,high acuity, limited budgets, and insufficient staff andare challenged to add preventive programs to theirscope of practice.8

One proposed solution to these relatively fixed barri-ers to ED behavioral health interventions is the use ofcomputer technology. Computers offer the potential ofdelivering cost-effective, individually tailored, evidence-based interventions for an array of health behaviors;reducing the time and resources needed for implemen-tation of behavioral health measures; and allowing theED to provide such measures consistently and with uni-form quality. Importantly, computer-based screeningand interventions are likely to be highly acceptable topatients. In national samples, over three-fourths ofAmerican Internet users report using the Internet toaccess health information.9 A recent study showed thatmany ED patients show interest in and even preferencefor technology-based interventions for a wide variety ofbehavioral health topics.10 A meta-analysis evaluatingthe efficacy of computer-delivered interventions to pro-mote healthy behaviors in outpatient (non-ED) settingsconcluded that participants who received these inter-ventions improved their knowledge, attitudes, andintentions toward changing their high-risk healthbehavior.11

A growing number of studies are examining the use ofcomputers for behavioral health screening or interven-tions in the ED setting. However, this emerging litera-ture has not been synthesized to allow recommendationsfor use of technology for targeted health issues or to for-mulate recommendations for future directions inresearch. The objectives of this systematic review wereto evaluate the existing evidence for use of computertechnologies in addressing health behaviors in EDs, toassess the quality of the existing literature, and to iden-tify notable gaps in research on computer technologyfor behavioral health efforts in the ED.

METHODS

Search StrategyFor this systematic review, the research team workedin conjunction with a medical research librarian todevelop and implement a systematic search strategy.The search was conducted in 14 databases: AcademicSearch Premier, CINAHL, Cochrane Central Register ofControlled Trials, Cochrane Reviews, Cochrane, Data-base of Abstracts of Reviews of Effects, EMBASE, GreyLiterature Report, Health Technology Assessments

Database, Nursing at OVID, ProQuest Theses and Dis-sertations, PsychInfo, PubMed, and SocIndex. We alsosearched ClinicalTrials.gov for ongoing studies andcontacted investigators of pertinent studies to deter-mine if there were studies pending publication. Last,we hand-searched the reference sections of all includedarticles and related review articles to identify otherpotentially relevant studies. An initial search was per-formed in December 2010. A final search was per-formed in February 2011 to capture any newlypublished articles. Data extraction and synthesis wereconducted from March to June 2011.

Search terms included emergencies, emergency ser-vice, emergency medicine, accident and emergency,casualty, electronic mail, Internet, computers, software,technology, wireless, mobile, laptop, and social net-work. The full list of search terms and a detailed searchstrategy can be found in Data Supplement S1 (availableas supporting information in the online version of thispaper). Articles selected were limited to those publishedin English, Spanish, or French language and thosepublished in or after 1990.

Study SelectionStudies were included if they employed computer tech-nology for behavioral screening, interventions, and ⁄ orreferrals for patients presenting to the ED and if theyused computers to address risky behaviors (e.g., unsafesex, partner violence, substance abuse, depression). Wedid not use standard or uniform definitions of the indi-vidual high-risk behaviors, but accepted the authors’definition of these behaviors. Studies were excluded ifthey used computers solely to improve documentation,for follow-up after general ED care, or for detection orcare of chronic medical illnesses. Studies were alsoexcluded if they used research assistants, social work-ers, or nurses to improve ED-based behavioral screen-ing, interventions, or referrals, unless the keycomponent of the intervention involved computers.Both observational and experimental studies wereincluded. If multiple articles were published analyzingthe results of a single study (e.g., a preliminary analysisfollowed by a final analysis), the most comprehensiveor final article was retained.

One study investigator (NA) performed an initialscreen of all titles to identify potentially eligible articlesand to eliminate duplicates across databases. Two studyinvestigators (EKC and MLR) repeated the screen witha sample (200 articles) from the full list of titles to verifythe quality of the initial screen. EKC and MLR thenindependently reviewed the abstracts of each retainedarticle. If at least one investigator felt a study waspotentially eligible based on abstract review, the fullmanuscript was obtained. The same two study investi-gators (EKC and MLR) then independently performed areview of the full manuscripts to determine if the studymet all of the inclusion criteria. Any discrepancies inopinion were resolved by discussion with a fourthstudy investigator (EDB).

Data Abstraction and AnalysisInformation on each eligible study was collected usinga standardized data abstraction form that captured

ACADEMIC EMERGENCY MEDICINE • March 2012, Vol. 19, No. 3 • www.aemj.org 319

study design, study characteristics, patient population,target behavior, description of the innovation or inter-vention, outcomes, and results. One reviewer (EKCor MLR) extracted data for each study, with accuracy ofinformation confirmed by a second reviewer (EKCor MLR). Given the broad range of topics included inour search, meta-analysis of the data was not possible;studies were analyzed descriptively only.

Quality AssessmentEligible studies were assessed for methodologic qualityand risk of bias using a modification of the criteriadeveloped by Downs and Black.12 The Downs and Blackinstrument uses 27 criteria assessing the quality ofreporting, power, and internal and external validity of aresearch study. To optimize the uniformity of scoring,we simplified the two subscales with multicategoricalanswer options to dichotomous answer options, makingthe maximum score possible 27. We divided the totalscore into tertiles and considered scores of 19 to 27‘‘high quality,’’ scores of 10–18 ‘‘moderate quality,’’ andscores 9 or below ‘‘low quality.’’13,14 Two investigators(EKC and MLR) independently completed quality scor-ing of each study; in case of discrepancy, a third inves-tigator (EB) was involved and disagreements wereresolved through consensus. Inter-rater reliability wasdetermined by calculating a r statistic.

RESULTS

The study selection process is outlined in Figure 1. Of685 studies retained after review of titles, 66 full-textarticles were evaluated, and 20 met inclusion criteriafor the review. Although the search included studiespublished from 1990 to the present, the eligible studieswere all published since 2001. Eight (40%) of the eligi-ble studies were federally funded; the remaining 12studies were supported by state or provincial govern-ments or by private corporations or foundations. Thegreatest number of ED-based computer studies tar-geted alcohol ⁄ substance use (n = 8, 40%), followed byinjury (intentional or unintentional; n = 7, 35%) and

then mental health (n = 4, 20%). One study15 addressedboth alcohol use and violence and was counted in bothcategories. Most (n = 19, 95%) were conducted at a sin-gle center. Two studies (10%) included non–English-speaking populations. Table 1 summarizes the reviewedstudies’ characteristics, including the behavioral targetand the function or functions of the computer innova-tion tested.16–34

Tables 2 through 5 provide further details of individ-ual studies by topic, including data on key variables andquality assessment scores. The single paper addressingboth violence and alcohol use15 is listed in Table 2.Inter-rater reliability for the quality scores was high,with 24 discrepancies out of 540 data points (96% con-currence, j = 0.67).

Computer-based ED Alcohol and Substance UseInnovationsAmong the eight studies addressing alcohol and sub-stance use (Table 2),15–22 four (50%) were randomizedcontrolled trials (RCTs) that employed computer tech-nology to deliver interventions aimed at reducing riskydrinking,15,19–21 with measured outcomes of alcoholconsumption. The remaining studies’ outcomes mea-sured intervention feasibility and acceptability forpatients and ⁄ or providers. Many of these studies usedthe standard ED care as a control group (30%) or hadno comparison condition (25%). Clinical outcomes forthe four RCTs included alcohol use; one study15 addi-tionally measured negative social consequences of alco-hol use (e.g., missed school, trouble getting along withfriends). Overall, the studies showed acceptability andfeasibility and some evidence of efficacy in reducinghigh-risk alcohol use.

Computer-based ED Violence and UnintentionalInjury InterventionsOf the seven studies that addressed violence or unin-tentional injury in the ED23–28 (Table 3 and Waltonet al.15), five23–27 targeted intimate partner violence(IPV). The IPV studies largely focused on screening,with limited interventions. Most of the outcomesmeasured were proximal, occurring within the initialED visit, such as detected prevalence of IPV, physiciandocumentation, and provision of referrals to services.Only Houry et al.23 measured occurrence of IPV afterthe ED visit. The study by MacMillan et al.24 was theonly one to provide a comparison with an alternative,nontechnological means of identifying IPV. Overall,these studies showed high feasibility and accept-ability of computerized screening and few negativeconsequences.

Computer-based ED Mental Health InterventionsAs with the injury studies, the mental health studies(Table 4) focused primarily on patient screening.29–32

Two studies (50%) were RCTs31,32 of a computer-basedscreening program that included physician notificationof the results of the mental health screen. Outcomesincluded rate of detection of occult psychiatric prob-lems, referrals, and receipt of services; none of thestudies measured clinical outcomes related to the psy-chiatric conditions. None of the studies compared the

Records iden�fied throughdatabase searching

(n = 20,950)

Records a�er duplicates removed(n = 17,744)

Records excluded on:Language – 46Title – 16,980Abstract – 652Total – 17,678Full-text ar�cles assessed

for eligibility(n = 66)

Studies included inqualita�ve synthesis

(n = 20)

Figure 1. Study selection.

320 Choo et al. • SYSTEMATIC REVIEW OF ED TECHNOLOGY STUDIES FOR PUBLIC HEALTH

technological innovation with a non–technology-basedprocess. Overall, these studies showed high acceptabil-ity and feasibility of screening, but limited clinicaloutcomes.

Other Computer-based ED InterventionsOf the remaining two studies (Table 5), one34 used acomputerized survey to screen for a variety of healthbehaviors, including drug and alcohol use, cardiovascu-lar health risk behaviors, high-risk sexual behaviors,depression, and other ‘‘injury-prone behaviors.’’ Thisstudy measured acceptability, feasibility, and knowledgeretention, but not actual behavior change. Merchantet al.33 used audio computer-assisted self-interviewtechnology to increase ED patient attitudes to theirown HIV risk; however, actual risk behaviors were notmeasured.

DISCUSSION

There are many barriers to implementing interventionsfor behavioral health issues in the ED setting. ED clini-cians work in a high-volume, high-acuity setting withsignificant time constraints and receive little training inproviding assessments or interventions for commonproblems such as substance abuse, smoking cessation,involvement in violence, or HIV risk. The institutionalresources available for management of these issues arehighly variable but generally insufficient for the largenumber of patients who might benefit from them.35,36

Studied behavioral interventions in the ED setting areoften performed by social workers or case managers,yet the lack of availability of these resources, especiallyin remote or small EDs,37 limits the dissemination oftreatments designed to be performed by these individu-als. At the same time, many ED patients lack a consis-

tent source of follow-up care, so failing to addressthese health issues during the visit may mean failing totake advantage of individuals’ sole point of contact withhealth care.

Computer technology-based screening, interventions,and referrals have several clinical advantages that makethem potentially advantageous for use in the ED set-ting.38 They provide a sense of anonymity and privacyand may increase reporting of unhealthy behaviors.26,39

They require little direct clinician involvement. They canbe adapted to be culturally and linguistically specific, andaudio capabilities allow them to be used among low-lit-eracy individuals. They can provide individualized healthinformation to participants immediately and in an engag-ing manner. They are able to store information so thatprogress over time can be accurately monitored andreviewed with the participant during follow-up after theED visit. They minimize the bias that can arise in clinicalrelationships. An intervention, if proven effective, maybe able to be disseminated while maintaining treatmentfidelity among clinical sites.

This review supports the promise of computer-basedtechnology as a means to filling a recognized healthcare gap in the ED. All the studies we identified werepublished within the past 10 years, reflecting the surgeof interest and investment in applying emerging tech-nologies to behavioral health problems. The broadrange of health issues studied within a relatively shorttime period speaks to the many areas ED clinicians areeager to address—and likely feel constrained fromaddressing—in their current practice. While screeningis arguably the simplest, and perhaps the most obvious,use of technology in the ED, a number of studies usedcomputers in more core patient care functions, such ascreating personalized referrals to treatment services orproviding interactive interventions.

Table 1Study Characteristics

Behavioral Target First Author (Year) Country

Project Purpose

Screening Interventions Referral

Alcohol ⁄ substance use Bendtsen (2007)16 Sweden XBoudreaux (2009)17 United States X XKarlsson (2005)18 Sweden X XMaio (2005)19 United States XNeumann (2006)20 Germany X XTrinks (2010)21 Sweden X XVaca (2010)22 United States X X X

Alcohol and youth violenceIPV

Walton (2010)15 United States XHoury (2008)23 United States X XMacMillan (2006)24 Canada XRhodes (2002)25 United States XRhodes (2006)26 United States XTrautman (2007)27 United States X X

Unintentional injuryMental health

Gielen (2007)28 United States X XClaassen (2005)29 United States XFein (2010)30 United States XSchriger (2001)31 United States XSchriger (2005)32 United States X

HIV risk behaviorsMultiple health behaviors

Merchant (2009)33 United States X XRhodes (2001)34 United States X X

IPV = intimate partner violence.


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fre

ferr

als

3,0

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(in

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);1,0

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(9-1

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llfo

llo

w-

up

);131

(at

3m

on

ths)

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sig

nifi

can

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fety

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es;

red

uce

d9-1

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lls;

rela

tively

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rces

at

3-m

on

thfo

llo

w-u

p.

17

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asi

-exp

eri

men

tal

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utm

an

(2007)2

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(‡18)

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en

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om

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en

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for

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1,0

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her

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ipt

of

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n(2

006)2

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(18–6

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(on

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me)

Face

-to

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of

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od

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(18–6

5)

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ing

(on

eti

me,

mean

18

min

)

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al

care

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dis

clo

sure

toan

dd

iscu

ssio

nw

ith

pro

vid

ers

;re

ceip

to

fse

rvic

es

871

Rate

so

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iscu

ssio

n,

dis

clo

sure

,an

dre

ferr

al

tose

rvic

es.

23

Ped

iatr

icin

jury

pre

ven

tio

nG

iele

n(2

007)2

8P

are

nts

of

ped

iatr

icE

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ati

en

ts(4

–66

mo

nth

s)

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mp

ute

rize

dta

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ryp

reven

tio

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terv

en

tio

n(o

ne

tim

e)

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ort

on

un

rela

ted

child

healt

hto

pic

s

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tykn

ow

led

ge

an

db

eh

avio

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gard

ing

car

seat,

smo

keala

rm,

po

iso

nst

ora

ge

safe

ty

901

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her

safe

tykn

ow

led

ge,

hig

her

use

of

chil

dsa

fety

seats

.

23

IPV

=in

tim

ate

part

ner

vio

len

ce;

QA

S=

qu

ality

ass

ess

men

tsc

ore

.*S

am

ple

size

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ort

ed

was

that

use

din

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main

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aly

sis.

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en

era

l,sa

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leat

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al

foll

ow

-up

was

use

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less

au

tho

rsre

po

rted

inte

nti

on

-to

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at

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aly

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nd

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eart

icle

.�T

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defi

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ion

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fro

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tud

yw

as

con

du

cted

inm

ult

iple

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um

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list

ed

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size

of

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Tab

le4

Men

talH

ealt

hS

tud

ies

Stu

dy

Desi

gn

Fir

stA

uth

or

(Year)

Targ

et

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pu

lati

on

Exp

eri

men

tal

Co

nd

itio

n(L

en

gth

of

Part

icip

ati

on

)*C

om

pari

son

Co

nd

itio

n(s

)P

rim

ary

Ou

tco

me(s

)S

am

ple

Siz

e�

Main

Resu

lts

QA

S

Cro

ss-s

ect

ion

al

Cla

ass

en

(2005)2

9A

du

lt(‡

18)

pati

en

tsw

ith

no

np

sych

iatr

icch

ief

com

pla

ints

Co

mp

ute

rize

db

ilin

gu

al

men

tal

healt

hsc

reen

ing

(on

eti

me,

6m

inu

tes)

N⁄A

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bil

ity�

an

dd

ete

ctio

n1,5

90

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ble

toad

min

iste

r;h

igh

levels

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ult

suic

idali

tyco

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are

dw

ith

exis

tin

gli

tera

ture

.

9

Fein (2010)3

0A

do

lesc

en

ts(1

4–1

8)

pre

sen

tin

gto

the

ED

wit

hn

on

psy

chia

tric

com

pla

ints

Bri

ef

com

pu

teri

zed

men

tal

healt

hsc

reen

(on

eti

me,

10

min

ute

s)

Usu

al

care

,in

the

19

mo

nth

sp

rio

rto

imp

lem

en

tati

on

Feasi

bil

ity,

dete

ctio

n,

an

dso

cial

wo

rker

or

psy

chia

tris

tass

ess

men

t

11,2

01

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ble

;sm

all

bu

tsi

gn

ifica

ntl

yin

crease

did

en

tifi

cati

on

an

dass

ess

men

to

fp

ati

en

tsw

ith

psy

chia

tric

pro

ble

ms.

17

RC

TS

chri

ger

(2001)3

1A

du

lt(‡

18)

pati

en

tsw

ith

dif

fuse

or

un

usu

al

com

pla

ints

⁄b

eh

avio

r

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mp

ute

rize

dp

sych

iatr

icsc

reen

ing

inte

rvie

w(o

ne

tim

e,

5–1

0m

inu

tes)

wit

hp

hysi

cian

no

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cati

on

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ysi

cian

no

tn

oti

fied

of

scre

en

ing

resu

lts

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ctio

n,

con

sult

ati

on

or

refe

rral

190

No

dif

fere

nce

betw

een

gro

up

sin

psy

chia

tric

dia

gn

osi

s,co

nsu

ltati

on

or

refe

rral.

20

Sch

rig

er

(2005)3

2A

du

lt(‡

18)

ED

pati

en

tsw

ith

‘‘n

on

speci

fic

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ati

cco

mp

lain

ts’’

Co

mp

ute

rize

dp

sych

iatr

icsc

reen

(on

eti

me,

2–3

5m

inu

tes)

wit

hp

ati

en

tan

dp

hysi

cian

no

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cati

on

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een

ing

on

ly,

or

scre

en

ing

plu

sn

oti

fica

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no

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en

tso

nly

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ep

tab

ilit

y,

dete

ctio

nan

du

seo

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95

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ep

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ilit

y;

hig

hra

tes

of

occ

ult

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tal

illn

ess

;tr

en

dto

ward

incr

ease

dre

ferr

al

wit

hp

ati

en

tan

dp

hysi

cian

no

tifi

cati

on

.

14

QA

S=

qu

ali

tyass

ess

men

tsc

ore

.*If

du

rati

on

of

inte

rven

tio

nis

no

tp

rovid

ed

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en

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ned

inth

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icle

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ple

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leat

fin

al

foll

ow

-up

was

use

d,

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less

au

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rsre

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rted

inte

nti

on

-to

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at

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aly

sis,

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hic

hca

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en

um

ber

of

all

part

icip

an

tsra

nd

om

ized

totr

eatm

en

tw

as

use

d.

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ed

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nit

ion

of

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dm

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ed

fro

mst

ud

yto

stu

dy.


However, this literature review also identifies manyareas for growth in the research on technology use forbehavioral change in the ED. First, there are notablegaps in the types of risky health behaviors addressedby studied technologies. Most of the existingstudies addressed alcohol or substance abuse; withinthis category, there was only one study examiningdrug use and no studies addressing tobacco use. Mostof the computer-based work on violence examined IPV,with little directed toward youth violence and nothingdirected toward other types of community violence,elder violence, or child abuse. Only one studyaddressed unintentional injuries, and only oneaddressed high-risk sexual behaviors. Walton’s inter-vention for alcohol use and violence among adolescentswas the sole study to acknowledge the importance ofaddressing co-occurring high-risk behaviors together.

Some studies identified clinical or behavioral out-comes: four of the substance use intervention studiesmeasured alcohol use before and after the ED interven-tion, with one measuring negative social consequencesof alcohol use. One violence-related study measuredoccurrence of IPV—not just use of resources—after theED visit. However, the majority of the studies, even theexperimental studies, lacked patient-related outcomes.Many lacked comparison against valid nontechnologicalinterventions and instead used ‘‘usual care’’ as the com-parison group, presuming that the only option to tech-nology-based interventions is no treatment at all. Insome cases, this may be attributable to the lack of cur-rent nontechnological evidence-based practices, suchas in the treatment of IPV or mental health problemsidentified in the ED setting. In other cases, this short-coming reflects the early stage of research on imple-menting computer-based technologies into the EDsetting. Feasibility and acceptability were still the pri-mary questions for many researchers, as demonstratedby the 55% of studies in our review that focused onthese topics.

Additionally, while many of the studies we reviewedreported their technological innovation to be feasibleand acceptable, and a few reported efficacy in reducingharmful behaviors, none as yet have addressed howsustainable these innovations will be. Can these tech-nologies truly be disseminated to resource-poor areas?Can they be implemented in places that do not havesignificant resources of institutional support and infor-mation technology specialization? Technology-basedinterventions may be a solution to resource and timelimitations in the ED, but they have high start-up costsand a commitment to maintenance. ED staff must betrained to use the technological program, device, orsoftware. Hardware and software can break, malfunc-tion, become outdated, or be vandalized or stolen; theymust be replaced or updated on a regular basis. Com-mercial products are rapidly becoming available thatmay allow researchers and hospitals to develop com-puter-based resources with increasing ease and afford-ability; however, few studies in our review comment onthe cost-effectiveness of their innovations or otherpractical potential limitations to long-term and wide-spread use of technologies. Most studies were single-center, making it as yet difficult to imagine how theseT

ab

le5

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er

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die

s

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gn

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et

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on

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eri

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n(L

en

gth

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icip

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on

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lts

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od

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(2001)3

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pri

nto

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of

reco

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avari

ety

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ral

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18

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on

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on

of

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rven

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,it

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totr

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tw

as

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innovations would function outside of the specific envi-ronment in which they were developed.

These are all challenges that surely accompany anymajor innovation in the systems we use to deliverhealth care. However, they bear recognition, lest ourenthusiasm for incorporating computers to fill the gapsin emergency services prevent us from anticipating andaddressing the challenges and costs specific to technol-ogy-based interventions.

Finally, most of the studies we identified used com-puters in the ED for fairly ‘‘traditional’’ functions, suchas administering patient surveys or providing statichealth information. We anticipate that upcomingresearch will examine newer computer applications,such as social networking or telehealth applications,and employ computer technology for more advancedand complex functions, including delivering interactiveand highly tailored ED-based interventions, performingpatient boosters or follow-ups after the ED visit, andproviding dynamic linkages to needed services.

LIMITATIONS

First, it is possible that we failed to include relevantstudies, whether because we missed them in the initialsearch or erroneously excluded them when reviewingstudies by title or abstract. Any studies published sinceour final review (in February 2011) would also not beincluded in this review. Our determinations of studyquality were also subject to the biases of the studyinvestigators.

We did take a number of steps to ensure that all eligi-ble studies were included and that our assessments ofquality were objective. We made our search as compre-hensive as possible by including multiple, diverse, andredundant databases. We also had two investigatorsindependently review abstracts and articles for inclu-sion and used a standardized process for achievingconsensus to avoid reviewer fatigue and subjectivityand to minimize error. Nevertheless, a systematicreview is ultimately a subjective process, and the possi-bility for error or bias remains.

Well-validated quality assessment instruments forboth randomized and nonrandomized studies are lack-ing. Therefore, the process of quality scoring adds tothe subjective nature of systematic review. AlthoughDowns and Black has come to be accepted as a standardfor assessing quality of studies and is commonly used inthe medical literature, it is an unvalidated measure, andcategorization into ‘‘high,’’ ‘‘moderate,’’ and ‘‘low’’ qual-ity categories remains an imperfect and somewhat arbi-trary process. This is all the more true given thatwe used a modified version of the scale to optimize itsprecision. We included the Downs and Black instrumentto include some objective measure of the likelihoodof bias and to put study findings in context of theirmethodologic rigor; however, judgment of the quality ofindividual studies should be moderated by an acknowl-edgement of the limitations of the scale itself.

While the studies we reviewed supported the feasibil-ity of computer-based interventions, there are twocaveats to this statement. First, there was wide varia-tion in the criteria authors used to define feasibility,

ranging from patient willingness to participate to theability to incorporate the technology into existing EDfunctions; this discrepancy is reflected in the contradic-tion between the number of studies asserting feasibilityand the lack of information provided on the technicaland financial aspects of implementing these interven-tions. Second, it is likely that some researchersattempted technological innovations for health behav-iors, but failed to initiate or completely implement themdue to some of the potential barriers discussed. Suchfailures would not be represented in the published liter-ature. Additionally, computer-based applications forbehavioral modification that are commercially or pri-vately developed are typically not formally tested in aclinical setting, so this study cannot begin to commenton their appropriateness or effectiveness for our popu-lation. While missing unpublished studies or unstudiedtechnologies is not a flaw of our research methods, it isimportant to acknowledge that our review may dispro-portionately represent the successes and thereforepaint a misleadingly rosy picture of these technologies.

CONCLUSIONS

Computerized tools hold great potential for overcomingthe multiple barriers to behavioral health screening,interventions, and referrals to treatment in the ED. Weidentified 20 studies that examined the feasibility,acceptability, or efficacy of using computer technologyin the ED to provide screening or services for awide variety of common high-risk health behaviors.While initial findings suggest that these types of toolswill be feasible and acceptable, further research isneeded to establish their efficacy for meaningful healthoutcomes and to identify approaches to overcomingbarriers to dissemination and sustainability.

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a systematic review of emergency department technology-based behavioral health interventions

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