developing policy: simulating a year of care for people with long term conditions

Developing Policy: Simulating a Year of Care for People with

Long Term Conditions

Claire Cordeaux

Executive Director, Healthcare

SIMUL8 Corporation | SIMUL8.com | [email protected] 1 800 547 6024 | +44 141 552 6888

We know the problem…

• 15m people with Long Term Conditions• Increasing each year with ageing population• Responsible for 70% of NHS costs• Significant cause of ED attendance and urgent

admission


Driving Policy through Funding Instruments

• A year of care capitation fund for a person living with multiple conditions

• Incentivizing providers and commissioners to work effectively together

• Aligning funding flows and patient need for support

• Improving outcomes and efficiency• Reducing emergency care activity


The underlying research base

Scottish School of Primary Care• More people have 2 or more long term conditions


Long Term Conditions

• Only 18% of patients with COPD have just COPD

• Only 14% of patients with diabetes have just diabetes

• Only 5% of patients with dementia have just dementia

Scottish School of Primary Care


Silo treatment vs. whole person

Sir John Oldham, DH


What if?

• We plan care for people rather than disease?

• Are there common patterns of service use?

• Can we differentiate groups of patients by need and costs to create an annual tariff?

• Can we work within that tariff to reduce emergencies and manage care out of hospital?


Where does simulation help?

• Modelling uncertainty

• Testing assumptions and their consistency when no historic data

• Considering variability

• Driving thinking

• Sharing models


Our task

• Create a simulation model

• 7 pilot sites

• 1 national model to be used locally

Looking for common parameters


Starting to simulate a new approach

Exacerbation


Using Scenario Generator

PathwaysScenarios

Wholesystemmodel

Simulationresults

Service points, flows

& waits

Servicemodels

Referral patternsCapacityDuration

PopulationDemographyPrevalence

Prevalence/Influencing

factors

Demographicweighting

Population

Constrainedresources

Mental Health

Social Care

Urgent

Planned

Maternity

Urgent


Patient identification and assessment


Services by level of need


Validation

3 sites to datePathway Step Actual data Simulated data %Risk Stratification and Assessment Low Need Assessment 792 812 0.98

Risk Stratification and AssessmentMedium Need Assessment 118 118 1.00

Risk Stratification and Assessment High Need Assessment 9 9 0.96High Need Acute admission 8 8 1.06High Need A&E 11 10 1.10High Need Elective admission 3 3 1.05High Need First Outpatients 5 6 0.78Low Need Acute admission 214 203 1.05Low Need Exacerbation 454 445 1.02

Low Need First Outpatient appointment 451 442 1.02

Low Need Elective inpatient 232 244 0.95Low Need Outpatient Follow up 713 717 0.99Medium Need Acute admission 64 64 1.00Medium Need Exacerbation 94 94 1.00Medium Need Elective admissions 20 20 0.99Medium Need First Outpatient 56 56 1.00Medium Need Outpatient Follow up 85 87 0.98Medium Need Reablement 1 0


Some findings

ProbabilityLow Need

Medium Need

High Need

First Outpatient 17% 12% 12.5%Outpatient Follow-Up 27% 18% 15%ED 17% 25% 19.3%Admission 46% 68% 73%Death in ED 4.60% 0% 0%Death in inpatient 7.50% 17% 0Social care 0% 10% 100%


But……

• No real correlation between risk score and level of need


And………..

Average number and cost of emergency admissions

Year Number Cost of admissions

2009/10 1.5 £ 2,698 2010/11 3.2 £ 6,594 2011/12 1.6 £ 2,956

Dr. Abraham George

A crisis curve?


Meanwhile End of Life – modelling death

Highest number of deaths = organ failure (32%)Same group of patients with long term conditions


So where are we now? .. Year 2

• A new model• Predict demand by

– risk score– numbers of long term conditions


So where are we now ctd? .. Year 2

• Consistent definitions of services being accessed• Able to calculate probability of access to services

by long term condition groups

%%

%

%

Death

New LTC Group

%

%


So where are we now ctd? .. Year 2

• Include changing state of patients– Numbers of long term conditions– Low to very high


What the simulation does…

• Informs question development and data collection

• Allows experimentation and hypothesis testing where no historic data available

• Enables research evidence to be applied to policy and practice development

• Shares national assumptions meaningfully at local level

• Reduces risks in policy development by generating evidence for decisions


Questions?

[email protected] Director, Healthcare, SIMUL8 Corporation

developing policy: simulating a year of care for people with long term conditions

Documents

low need outpatient

low need exacerbation4544451

outpatient followup27

medium needoutpatient

medium needexacerbation94941

risk stratification

long term conditionsincreasing

long term conditionschart10