Paul Walley

Associate Professor

Warwick Business Schoolpaul.walley@wbs.ac.uk

Redesigning Emergency CareLessons from the UK

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Introduction

• The UK government applies a “4 hour target” journey time for all patients attending A&E departments

• A&E departments’ performance has improved from 65% target achievement (2001) to 96% in 2005/6

• A key catalyst of the improvement was the Emergency Services Collaborative which applied “whole system process redesign” to all 200 sites in England with 24-hour A&E departments

• Work is now being done to repeat this improvement in Scotland

• This presentation summarises some of the technical lessons we have learned during the programmes

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1. Really Understand Demand1. Really Understand Demand

Don’t confuse demand with activity Activity:

is a significantly modified measure for demandoften “double-counts” demandincludes “failure demand” - for example rework

Patientis ill

No spaceat GP

PhonesNHS Direct

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Demand varies over time for a number of reasons:

Medical admissions 7-day moving average

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Year from April

Demand varies by1. Day of week2. Weather related3. Special cause events4. Random factors

BUT Healthcare is arguably one of theleast seasonal services we know

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Daily arrival pattern at A&E (all patients)

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2. Develop the Right Capacity Plans2. Develop the Right Capacity Plans

Capacity ?

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What is the relationship between capacity, demandand queue length?

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Utilisation0% 100%

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ngth

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Queue type A Queue type B

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Elective

Emergency

3. Demand variation is introduced by the system…3. Demand variation is introduced by the system…

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3. … and is amplified by supply chain effects3. … and is amplified by supply chain effects

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No. Admissions

Discharges

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4. Don’t cluster demand by symptom…4. Don’t cluster demand by symptom…

MinorPatients

“Off Legs”

Respiratory Distress

Elderly Care

Abdominal Pain

Chest Pain

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4. … instead “Think Process”4. … instead “Think Process”

Assess Treat Discharge

Assess Investigate/Observe

Transfer toMH care

Assess Admit tomedical ward

Investigate/Observe Treat Discharge

Assess Admit tosurgical ward

Investigate/Observe Theatre Discharge

Assess Investigate/Observe DischargeTreat

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Reception Triage Assess Treat DischargeWait Wait Wait Wait

ReceptionWait

Assess, treat & discharge

a) The conventional model with 4 in-process queues

b) See & Treat (one in-process queue)

5. Design to absorb variation (and eliminate waste!)5. Design to absorb variation (and eliminate waste!)

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6. Look at capacity yield losses6. Look at capacity yield losses

About half of A&E target breaches are due to lack of bed availability BUTBeds are not usually the true bottleneck

Why is this patient still in hospital?1. Responding to treatment but still poorly (60%)2. Not seen a doctor yet3. Successfully treated but given another disease4. Waiting for tests/treatment5. Waiting for results of tests6. Waiting for someone to discharge him7. Waiting for TTOs (drugs)8. Waiting to see OT/Physio9. Staying for meal (nothing at home in fridge)10.Waiting for relatives to collect (after work)11.Waiting for other transport12.Going home tomorrow13.Complex discharge (social services)

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Test Question: Has this investment worked?You have spent £2m (capital) on an new “Medical Assessment Unit. The staff costs are £2m p.a. A&E target achievement was measured1 month before opening and 1 month after:

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% Major patients admitted or discharged within 4 hours

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7. Use time series data (SPC) to measure performance7. Use time series data (SPC) to measure performance

Avoid “two-point comparisons” as they disguise system behaviourTarget achievement

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MAU opens

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Use SPC to: Monitor and Control a processMeasure the effect of changes madeLook at system behaviour

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week ending

Indi

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These peaks occur when there are more than 2 pts with fractured neck of femur on the ward

This run of seven points above the mean suggests that the process has changed – possibly due to the increased use of day surgery

Source: David Tomlinson

LOS data – 80% shorter LOS

SPC makes the impact of changes very obvious

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Summary

The improvement of emergency care is a whole system problem

The first challenge is to understand true demand

Healthcare introduces most demand variation, rather than suffers from adverse seasonality

System redesign practices can be used to reduce (sometimes eliminate) built-in delays