Modelling changes in healthcare demand through geographic data extrapolation

Palmer, Geraint Ian ORCID: https://orcid.org/0000-0001-7865-6964, Harper, Paul ORCID: https://orcid.org/0000-0001-7894-4907, Knight, Vincent ORCID: https://orcid.org/0000-0002-4245-0638 and Brooks, Cathy 2022. Modelling changes in healthcare demand through geographic data extrapolation. Health Systems 11 (2) , pp. 109-125. 10.1080/20476965.2021.1906764

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Abstract

Stay Well Plans are a new programme of care offered to frail and elderly people in Newport. In 2016 there were plans to roll out the programme so that it would be of- fered in all five counties of Gwent, a region of South East Wales serviced by Aneurin Bevan University Health Board. This paper presents the data analysis and mod- elling used to determine the effects of the programme on the demand of the wider system, and the effects of a Gwent-wide roll out. The analysis involves extrapolat- ing information from data from a geographical subset of the model domain to a larger geographical area, adjusting for population sizes, deprivation, and distances to healthcare facilities. These are then used to parametrise a Markov model and a Monte Carlo simulation to predict changes in demand due to different levels of roll out of the Stay Well Plans. Future population projections are also included in the analysis to examine the programme’s effect in conjunction with population growth. One of the main conclusions of the case study is that a roll out of the programme may result in a large reduction on demand at residential care services, however at the expense of an increase in demand at community care services.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Publisher:	Taylor & Francis
ISSN:	2047-6965
Date of First Compliant Deposit:	22 March 2021
Date of Acceptance:	10 March 2021
Last Modified:	26 Nov 2024 10:15
URI:	https://orca.cardiff.ac.uk/id/eprint/139952

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