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Improving Health System PerformanceImproving Health System Performance

The role of Stochastic simulation in The role of Stochastic simulation in predicting the utility of investmentspredicting the utility of investments

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Amid the entangled complexities of health Amid the entangled complexities of health services all aspects of performance are services all aspects of performance are

inter-dependentinter-dependent

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• Mike Ardagh, National Clinical Director of Emergency Department Services

• Stuart Powell and Emmanuel Jo, Service Analysis, National Health Board Business Unit, Ministry of Health

email; emmanuel_jo@moh.govt.nz• Joy Farley and Warwick Gilchrist, Taranaki

District Health Board

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Shorter stays in the Emergency Department

95% will be admitted, discharged or transferred within 6 hours

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Shorter stays in the ED

• About the whole of system

• Overlaps with;

• Elective aspirations

• Primary care considerations

• Cost containment endeavors

• Quality concerns

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Patients

1. 43 year old man with pneumonia, waiting for the medical registrar to assess.

2. 60 year old lady with a compound ankle fracture awaiting surgery.

3. A 73 year old woman with chest pain, waiting for a free ED cubicle

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Patients

1. 43 year old man with pneumonia, waiting for the medical registrar to assess.

• What if we had a separate medical assessment unit?

• Or a second medical registrar?

• Or IV antibiotics in primary care?

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Patients

2. 60 year old lady with a compound ankle fracture awaiting surgery.

• What if we had a dedicated acute theatre?

• Or another orthopaedic registrar?

• Or if elective orthopaedic activity was at another site?

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Patients

3. A 73 year old woman with chest pain, waiting for a free ED cubicle.

• Should we have more monitored cubicles?

• Or a bigger Coronary Care Unit?

• Or a low risk chest pain pathway run through the ED observation unit?

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Seeking answers

• Value stream mapping and other lean thinking techniques

• Breach analysis and other measures of variance• Street wisdom• Turning data until it catches the light• Modelling of present state compared to present

state plus an intervention

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Advantages of using simulation

•Real life experiments without implementing in the real world

•Identify how changes to variables within the system can impact other parts of the system

•Easy identification of bottle necks

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Disadvantages of using simulation

•If the data doesn’t reflect reality, the results won’t be real

•There may be unknown/unpredicted confounders the data has not taken into account

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The Simulation Tool

• Witness Simulation Software

• Used with success in a variety of industries

• 3 examples of use in Health Care and Hospitals on website (2 UK, 1 USA)

www.lanner.com

• Trialled with ADHB data*, and TDHB underway.

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Patient flow simulation for Taranaki DHB

•Aim:

To investigate the influence on patient flow, of a short stay unit next to ED.

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Model structure

Community(home)

Primary Care(9am-8pm, Mon-Fri)split into ED or home

ED(24x7)

split intoMED,SURG, PAEDS, MH,

Mat or home

Hospital inpatient serviceElective-MED

Elective-SURGAcute Inpatient-MED

Acute Paeds SurgAcute Paeds medicalAcute Inpatient-SURG

MENTALHEALTHMATERNITY

Primary queueArrival

9am-5pm, Mon-Fripull

Elective queue

ED queue-triaged

Time differential arrival24x7

(Undefined Patients)

Push to home

QueueWating in ED

Pull

Push to homePull

priority1

Pullpriority 3

Push for ASMED,ASSURGAIMED,AISURG

if there is a space in inpatient service

Push for MED, SURG, PAEDS, MH, MAT

Push to home

Push to ED queue

Short Stay Unit (23 hours)

Pullpriority2

Push MATERNITY, MENTALHEALTH

Elective-SURG stay time

Acute SURG stay time

Maternity stay time

Taranaki-Base HospitalED pathway simulaiton

1Elective referral, (Elective-Med, Elective-Surg) 3

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Timeline for a process optimisation using simulation for a DHB

Step Task Time

Required

1 Plan and identify what to optimise 1 day

2 Draw up a model structure and flow diagrams 1 week

3 Check the structure by the MOH team 1 day

4 Data gathering for the model 2-3 weeks

5 Building the model using special simulation software

2-4 weeks

6 Validate and calibrate the model for Business as Usual Scenario

1 week

7 Test different policy options in the complex virtual life environment to identify better outcome

1 week

Approximately 10 weeks !!!!

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Summary

• Achieving the Shorter Stays in the Emergency Department Target requires whole of system reforms

• Health systems are complex and interactive

• Interventions will influence many parts of the system

• Simulation has the potential to predict the influence of interventions

• The Shorter Stays Target is not competing with other priorities.