dr james lind & brett sellars, gold coast university hospital - the impact of hospital targets...

Impact of Hospital targets such as NEAT on Discharge

Planning

Discharge Planning Conference 24-25 July 2014 | Novotel on Collins Melbourne

Brett Sellars: Service Director Division of Medicine and Integrated care.

James Lind: Emergency Department FACEM

Content

• Introduction

• Impact of early discharge & Data to

forecast discharge

• Strategies for early discharge: 11am

discharge

• One stop shop for discharge

• The EDDI nurse in ED

• The stranded patient

Where are we

Gold Coast

Southport

70,000 presentation

Carrara

Hospital

Gold Coast Robina

55,000 presentations

Who are we?

• James Lind

• FACEM GCUH

Emergency

• Brett Sellars

• Service Director

Division of

Medicine

So why do we care about Early

Discharge…..

So what is it really about?

Optimise hospital capacity

Early discharge

Hospital avoidance

Better scheduling of elective patients

Predictive modeling

Aberrant monitoring

Bed demand modeling

Frequent flyer

Readmission

Smart bed configuration

And if we Overcrowding a system it is related to

adverse outcomes

Source GCH data 2013

The regression curve show

that once you reach a

critical capacity, SAC

events dramatically

increase

Occupancy 1=100%

Insight

Over occupancy of

a system is

associated with

increased SAC

events

The How: The science behind early

discharge

• Early discharge is probably the most

tangible way of creating capacity

• There needs to be an understanding of

Neat

ED

Bed management

Early discharge

Occupancy

Math's of patient flow

NEAT is strongly related to cases per hour ie the more

cases, the more likely the breach. Therefore, any

potential solution must effect this parameter.

Access block is minimally effected by cases per hour,

but more strongly effected by occupancy of the hospital

An interesting relationship appears to exist between

occupancy and NEAT breaches.

Any increase or decrease in hospital occupancy outside

the shaded zone will worsen breaches, ie if the system

is too busy or quiet, NEAT will get worse not better. It

suggests activity needs to be tightly regulated to

achieve optimal NEAT compliance

Data from AEHRC 2012

Science of NEAT Insight

Access block is

related to occupancy

The when: Time of of initial presentation

to ED set the time of discharge

2014

2013

Source EDDIS

1200

600

0

V

o

L

u

m

e

Time of day

ED surge occurs at 0900-1100

Ie beds needed from 11am.

Elective surgery need beds form 10am

Key insight

Bed needed

at 11am

Science of bed management

Key insights

Occupancy typically runs over

90% making it difficult to flex in

periods of high demand

Day time occupancy levels are

impacted by both elective and

emergency patients presenting

to the system

High occupancy adds complexity

to the management of patient

flow and beds

Source: QEII Key Activity and HBCIS

Hospital Occupancy

peaks at 102% at

9am

Hospital Occupancy

nadir at 82%% at

16:00

Hospital Occupancy per hour

100%

0%

Occupancy

Hour of day

Midnight

=90%

The science of Occupancy and

capacity

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

0

200

400

600

800

1000

1200

Occ

upan

cy (%

)

Cap

acit

y (N

umbe

r of

Bed

s)

Capacity

Occupancy

The science of Occupancy and

capacity

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

0

200

400

600

800

1000

1200

Occ

upan

cy (%

)

Cap

acit

y (N

umbe

r of

Bed

s)

Capacity

Occupancy

But our “big hospital are least

occupied and have the worst NEAT

Insight

More complex

than

number of beds

Mathematics of access block

051015202530354045500102030405060708090

71%

80%

89%

98%

107%

116%

OCCUPANCY

Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) ED Presentations (patients/hr) (Y1 axis)

ED Discharges (patients/hr) (Y1 axis) Inpatient Admissions from ED (patients/hr) (Y1 axis) Inpatient Length of Stay (days) (Y2 axis)

ED Length of Stay (inpatients) (hours) (Y2 axis) ED Length of Stay (others) (hours) (Y2 axis) ED Access Block Cases (inpatients) (patients/hr) (Y2 axis)

0

5

10

15

20

25

30

35

40

45

0

10

20

30

40

50

60

70

80

90

75%

80%

85%

90%

95%

100%

105%

110%

115%

OCCUPANCY

GROUP 3

A

B

C

300 >= Beds

0

5

10

15

20

25

30

35

40

45

0

10

20

30

40

50

60

70

80

90

75%

80%

85%

90%

95%

100%

105%

110%

OCCUPANCY

GROUP 2

A

B

C900 >= Beds > 300

0

5

10

15

20

25

30

35

40

45

0

10

20

30

40

50

60

70

80

90

70%

75%

80%

85%

90%

95%

100%

OCCUPANCY

GROUP 1

A

B

C

Beds > 900

What is the relationship between access

block and occupancy

Occupancy

A

“capacity

strategies”

B

ED over

flow

C

Hospital

Overflow

Ad

mis

sio

n/d

isch

arg

e

pro

ce

sse

s

90% 95% 105%

What is the relationship between access

block and LOS?

5 hours

Admissions

Discharges‘d1’

5 hours

Discharges‘d2’

Category 1 Category 2 Category 4 Category 5

Category 3

Hour of Day

Num

ber

of P

atie

nts

So what does it mean?

0

50

100

150

200

250

300

350

400

450

55

60

65

70

75

80

85

90

95

100

105

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Dis

char

ges/

ho

ur

Occ

up

ancy

(%

)

Time of Day (hour)

2 Hours Early

1 Hour Early

Actual

1 Hour Late

2 Hours Late

2 Hour Early Discharge (all 23

Hospitals) :

Average Occupancy reduced from

93.7% to 91.6%.

Maximum Occupancy reduced from

110.8% to 106.1%.

Time spent above 95% occupancy

reduced from 34.7% to 21.5%.

2 Hour Late Discharge (all 23

Hospitals) :

Average Occupancy increased from

93.7% to 95.8%.

Maximum Occupancy increased from

110.8% to 115.6%.

Time spent above 95% occupancy

increased from 34.7% to 45%.

Is it a linear relationship?

? Evidence based

optimal early

discharge time of

2.15hrs

What is the relationship between occupancy

and early discharge

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2 Hours Early 1 Hour Early Actual 1 Hour Late 2 Hours Late

Tim

e (%

)

Discharge Timing

Occupancy > 80%

Occupancy > 85%

Occupancy > 90%

Occupancy > 95%

Occupancy > 100%

Occupancy > 105%

Insight

The more occupied

a system becomes,

The more critical

is early discharge

Occupancy and Access block

0

50

100

150

200

250

75%

80%

85%

90%

95%

100%

105%

110%

115%

1 2 3 4 5

Acc

ess

Blo

ck C

ase

s p

er

da

y

Occ

up

an

cy (

%)

Category

23 HospitalsMean Occupancy (Y1 Axis)Mean PeakOccupancy (Y1 Axis)Mean AB Cases (Y2 Axis)

5 hours

Admissions

Discharges‘d1’

5 hours

Discharges‘d2’

Category 1 Category 2 Category 4 Category 5

Category 3

Hour of Day

Num

ber

of P

atie

nts

So what about the patient?

Occupancy

Patient A

LOS 5.5hrs Patient A

LOS 8 hr.

Ad

mis

sio

n/d

isch

arg

e

pro

ce

sse

s

90% 95% 105%

The Annual plan

Winter looks bad!

Strategies to execute Early

discharge

Strategies for Early safe Discharge

• EDD

• Planned predicted discharge

• Increased scope of transit longue

• Increased scope SSU

• Use of HITH

• Use of pathways

• Nurse initiated discharge

• Advance care allied health

• Integrated care

How to monitor EDD

The EDD on a ward level

The Data To Forecast Discharge

• Use of predictive software to look at

– Discharges

– Admission

– Net variance between the 2 with respect to

the last 2 days of data

The One Stop Shop for Discharge

The EDDI Nurse In Emergency

• Emergency department Discharge Initiative Nurse

• Part of the integrated care team based in Emergency

• EDDI under 65 yr. Chip over 65 yd.

• Advanced practice emergency nurse

• Knowledge of chronic diseases, soft tissue injuries, wound

care, minor head injuries, medication advice, alcohol and drug

dependence advice and a specialist on community services and

referrals.

• Provide consultation to emergency patients and free up time for

medical staff

• Provide on going education for the patient and for clinical staff

with in the Emergency department.

• Development of data base to provide electronic and hard copy

advise and education for patients

Wallis, M., Hooper, J., Kerr, D., Lind, J. & Bost, N. (2009). Effectiveness of an advanced practice emergency nurse role on discharge processes in

a minor injuries unit. Australian Journal of Advanced Nursing 27 (1), 21-29

The Stranded Patient

• What is the stranded patient

• How to manage them

– Multidisciplinary rounds

• Is this bang for buck

– Very difficult to move

Does it work?

With a little help from other process redesign

work !!!

Access and

Flow Unit

commence

s

Access and

flow

director

appointed

Medical

Assessmen

t Unit

opens

Southport

24 hour CNC

coverage 5

days a week

BPIO

commenced full

time Robina

and Southport

ED

Restructure

of staffing to

accommodat

e early

decision

making in ED

Business

Practice

Improvement

officer role

commenced

Extra FTE

in medical,

nursing and

admin

Current

management

CNC to work

on floor to

increase

coverage

Reconfigure

of current

FTE to

accommodat

e new model

of care

Increase in

Short Stay

Unit

capacity

from 10

beds to 6

beds and 7

chairs

PIT model

commence

d at

Southport

Emergency

Process

People ADON

patient flow

and extra

bed

managers

Refinement

of ward

based care

model

Re-

deployment

of medical

staff to clinics

Rapid

access

clinics for

medicine

commence

d

Full time

BPIO

appointed

New process in

bed

management

Macro NEAT Project

•Slack box process redesign

•Early decision making

•Education to staff on NEAT

•Performance feed back

•Definition on purpose and function of ED

Appointment

of new CE

Additional nursing

resources for bed

management

• Reconfigure bed meeting

•* Additional Afternoon bed meeting

•Rescheduling of ICU radiology , cardiac

and HODU PT

•Opening of additional HDU over winter

Redesign

of bed

manage

ment

Executive

rounding in

ED

Surge plans for

all sub-

specialities and

new Capacity

alert process

Ward

based

porterage

and

refinement

of bed

cleaning

Thank you

?

dr james lind & brett sellars, gold coast university hospital - the impact of hospital targets...

Health & Medicine