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Hybrid simulation modelling for dementia care services planning

Hybrid simulation modelling for dementia care services planning
Hybrid simulation modelling for dementia care services planning
Dementia is an increasing problem in today’s ageing society, and meeting future demand for care is a major concern for policy-makers and planners. This paper presents a novel hybrid simulation model that simultaneously takes population-level and patient-level perspectives to calculate the numbers of patients at different stages of disease severity over time, and their associated care costs. System Dynamics is used at population level to capture ageing, dementia onset, and all-cause mortality, whereas disease progression is modelled at individual patient level using Agent-Based methods. This enables the model to account for variability between patients in the rate of cognitive decline, dementia-related mortality and response to treatment interventions. Using epidemiological data from the medical literature, disease progression is modelled via a longitudinal clustering method to identify progression type, followed by mixed-effects regression to reflect each individual’s rate of cognitive decline. Results are presented for population data from the south of England, and show that the currently available interventions have only modest effects at population level.
hybrid simulation, dementia, disease progression, healthcare
0160-5682
Evenden, Dave
5cd6f0ab-5269-447c-af32-01edac9c905d
Brailsford, Sally
634585ff-c828-46ca-b33d-7ac017dda04f
Kipps, Christopher
e43be016-2dc2-45e6-9a02-ab2a0e0208d5
Roderick, Paul
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Walsh, Bronagh
5818243e-048d-4b4b-88c5-231b0e419427
Evenden, Dave
5cd6f0ab-5269-447c-af32-01edac9c905d
Brailsford, Sally
634585ff-c828-46ca-b33d-7ac017dda04f
Kipps, Christopher
e43be016-2dc2-45e6-9a02-ab2a0e0208d5
Roderick, Paul
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Walsh, Bronagh
5818243e-048d-4b4b-88c5-231b0e419427

Evenden, Dave, Brailsford, Sally, Kipps, Christopher, Roderick, Paul and Walsh, Bronagh (2020) Hybrid simulation modelling for dementia care services planning. Journal of the Operational Research Society. (In Press)

Record type: Article

Abstract

Dementia is an increasing problem in today’s ageing society, and meeting future demand for care is a major concern for policy-makers and planners. This paper presents a novel hybrid simulation model that simultaneously takes population-level and patient-level perspectives to calculate the numbers of patients at different stages of disease severity over time, and their associated care costs. System Dynamics is used at population level to capture ageing, dementia onset, and all-cause mortality, whereas disease progression is modelled at individual patient level using Agent-Based methods. This enables the model to account for variability between patients in the rate of cognitive decline, dementia-related mortality and response to treatment interventions. Using epidemiological data from the medical literature, disease progression is modelled via a longitudinal clustering method to identify progression type, followed by mixed-effects regression to reflect each individual’s rate of cognitive decline. Results are presented for population data from the south of England, and show that the currently available interventions have only modest effects at population level.

Text
JORS resubm 2020Jan15 - Accepted Manuscript
Restricted to Repository staff only until 20 May 2021.
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More information

Accepted/In Press date: 19 May 2020
Keywords: hybrid simulation, dementia, disease progression, healthcare

Identifiers

Local EPrints ID: 440976
URI: http://eprints.soton.ac.uk/id/eprint/440976
ISSN: 0160-5682
PURE UUID: 9299243c-d167-48c5-8570-e9170538af57
ORCID for Dave Evenden: ORCID iD orcid.org/0000-0002-6798-648X
ORCID for Sally Brailsford: ORCID iD orcid.org/0000-0002-6665-8230
ORCID for Paul Roderick: ORCID iD orcid.org/0000-0001-9475-6850
ORCID for Bronagh Walsh: ORCID iD orcid.org/0000-0003-1008-0545

Catalogue record

Date deposited: 26 May 2020 16:32
Last modified: 29 Jul 2020 01:51

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