Care outside hospital final

Simulating CareOutside Hospital

Claire Cordeaux: Executive Director, Healthcare

SIMUL8 Corporation | SIMUL8.com | [email protected]

Presenter

Claire Cordeaux

Executive Director, Healthcare SIMUL8 SIMUL8 Corporation

[email protected]

mailto:[email protected]



Housekeeping

• Audio

• Q and A

• Recording available on SIMUL8healthcare.com


Agenda

• Healthcare outside hospital – the policy agenda

• How simulation can help:• Prevention• Chronic Disease• Emergency Care Flow• Managing Community Workload

• Questions and our offer to you


• Supporting people outside hospital:

– Provides more accessible care

– Prevents exacerbation– Saves unnecessary visits (and

expense)– Speeds up hospital discharge– Reduces Length of Stay– Improves patient outcomes

Health Policy


Health Policy


• International studies

• But what does that mean for us?

• Hospital at home• Intermediate care• Early discharge

• Admission avoidance• Transfer of care• Telemedicine

The Evidence


Why simulation?

• A service and system redesign• Understanding the impact of changing service

utilization on:– Flow– Cost– Capacity/Resource

• No historic data• Different impacts on organizations, costs and

patients


Health and Care System Flow

Lack of capacity?

Rural/urban

population?

Lack of access? Vulnerable

groups?

Not 24/7?


Case Study 1: Chronic Diseases

Using risk stratification to identify and manage patients with multiple conditions and test:

• What if they are proactive managed or unmanaged?

• What if we applied an annual tariff?


Starting to simulate a new approach

Services “consumed”

Assessment of Need

Patients at Risk

Exacerbation


• No real correlation between risk score and level of need

But…

Assessment of Need

Patients at Risk

Click to edit Master title styleClick to edit Master title style


WHAT THE DATA IS TELLING US

SIMUL8 Corporation | SIMUL8.com | [email protected] Kent whole population data

Over 30% of people over 75 years have multimorbidity


Multimorbidity is more common than single morbidity

Kent whole population data


The total health and social care cost is strongly related to multimorbidity



The main contributors to total health & social care cost are acute non-elective admissions



People with complex health & social care needs appear to demonstrate a ‘crisis curve’



More community, mental health and social care services are delivered to people following a ‘crisis’ than before the ‘crisis’



Some indications that an integrated care plan changes the pattern of services delivered to people

BHR Costing Data


• Use local data to test assumptions

• Ability to update and review

Simulation


• Level of acuity

• Increasing numbers of long term conditions

Current Simulation

• Likelihood of patients accessing services by changing state of patients (state transition)


• Patients in each “state” have– A likelihood of accessing certain types of service

(Acute, Community, Mental Health, Social Care), including accessing services more than once

• Costs associated with those services

How it works


Data builds an underlying discrete event simulation model


• Number of patients in each “state” by year

• Average cost per patient

Results


• Cost by each area of service/organisation

Results


• Costs by state per year• Average cost per patient

• Comparison with tariff

Results


• Select population• Select

percentage of population

• Predict incidence• Predict incidence

by “state”

Simulating Demand


Start up Known Unknown 2012-13

Managed vs Unmanaged


Yearly Transitions


• Trial = multiple runs sampling from distributions in the model

• More robust results• Allow 20-30 minutes

Running a Scenario


Results Comparison

Trial results


• Known to integrated care team or not?• Test against proposed tariff?• Change variation in cost for services?• Decrease transitions through states?

Scenarios


• Planning for demand• Testing an improvement scenario• Negotiation between healthcare providers

How is this helping?


Case Study 2: Improving the emergency care flow with Martin Ware

• Impact of increasing out of hospital services on cost and capacity


• What does current unscheduled care flow look like?

• What will it look like in 5 years taking into account population change?

• What is the impact of increasing referrals to domiciliary care direct from hospital?

Initially to answer following questions


Initial Model


Area NHS data

Scenario Generator

%

A+E 108,472125,302 (17,026 out-of-area)A&E out of area (5% S Staffs) 17,000

0.99864512

Total NEL Admissions 84,297 84,4701.00205227

Elective admissions 12,674 12,7101.00284046

Daycase 49,983 49,8950.9982394

Discharges to Community Hospital

4560 4507

0.98837719

Discharge to social care teams (Stoke)

2183 2203

1.0091617

Discharges from Community Hospital

4347 4430

1.01909363

Intermediate Care (admission avoidance)

590 581

0.98474576

• Ran the model through with the received population data

• Set routing percentages so model matches activity data.

Baseline Results – 10 run trial


Item £ LOS

Hospital Bed £500 a day AMU/SAU/CDU Inpatient

Community Hospital Bed

£263 per day 21 days

Intermediate care £47 per hour 30 hours

A&E £105.5

Cost and Length of Stay Assumptions


With population increase

In 5 years

+ £11.3m (£1m domiciliary care)(1% annual inflation)

Increase in A&E and admissions over 9 years


Potential Domiciliary Care Scenario

• Average 6 week package for rehabilitation• Other packages average 48 weeks

Scenario: • Increase direct referrals from hospital – 30% of community

hospital referrals• Average 2 additional days in hospital• Referrals 10% to complex, 38% maintenance, 51% re-ablement


Cost per hour

Hours pw (normal)

LOS wks

Capacity (hrs pw)

Packages pw

Discharges to reablement from community 2.50% £20.98 11 6 1400 127Discharges to reablement from acute 10.10% £20.98 11 6 1400 127Discharges to maintenance care from community 4.50% £13.20 7 48 4100 586Discharges to maintenance care from acute 7.60% £13.20 7 48 4100 586Discharge from reablement to maintenance 15% £13.20 7 48 4100 586

Discharge to complex £13.20 22 48 4100 186All discharges from acute (stoke) 2183All discharges from community (stoke) 876

Domiciliary Care Assumptions


• £2.6m savings overall– Plus £4m social care– Plus 1.3m additional LOS, max bed occupancy +

10, +1% utilization– £7.6m savings community hospital, utilisation

reduced by 25%, max bed occupancy minus 90

Domiciliary care scenario results


Impacts

• Understanding the financial impacts

• Allows negotiation across providers and between payers and providers


• What is the impact of improvement interventions on a community team workload?

• For example: what is the impact of faster healing wounds on workload (60%)?– More time to care?– More time to see other patients?

• Engaging with community team – what are the pain points?

Project 3- Impact on Community team capacity


CommunityTeam

Patients

Daily allocation to staff matching patient need to competencies

Referrals

Visits

Discharge or Death

Ageing Population

Clinical Assessment

Wound care only

Multi-morbidity

Not wound

care


Simulation Concept


Invitation to co-develop and test the community model

• You get to influence the design• You get to use the model

Contact: [email protected]

Join us?


QUESTIONS

• Please forward any topics you would like to see covered to [email protected]

• Continue the discussion on SIMUL8 in Health – LinkedIn Group

• August Workshop – Improving Patient Care Pathways


Care outside hospital final

Healthcare

Transcript of Care outside hospital final