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Modelling Health and Healthcare for an Ageing Population

Youn, Ji Hee (2016) Modelling Health and Healthcare for an Ageing Population. PhD thesis, University of Sheffield.

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Population ageing has received much attention as a contributing cause of spiralling healthcare expenditure. This study primarily aims to estimate the impact of population ageing on key diseases, and to develop a flexible modelling framework that can inform policy decisions. This research provides a proof-of-concept model where individual Discrete Event Simulation models for three diseases (heart disease, Alzheimer’s disease, and osteoporosis) were extended from existing published models to simulate the general UK population aged 45 years and older, and combined within a single model. Using external population projection data incorporating potential demographic changes, the methods for projecting future healthcare expenditures for the three diseases were demonstrated and the relative benefits of improving treatment of each of the diseases evaluated. Secondary outcomes include the development of a pragmatic literature search method which can be used for literature within diffuse topic areas, and a literature repository for future researchers to explore the existing literature on ageing and healthcare expenditure. Expenditure for the three diseases is projected to increase from £16 billion in 2012 to £28 billion in 2037. A key finding from this work is that the estimates of costs, quality-adjusted life years (QALYs), and the projected expenditure for healthcare services can differ when multiple diseases are modelled in a single model compared with the summed results from single disease models. This implies that policy decisions on the allocation and planning of healthcare resources based on the results from individual disease models can be different from those based on linked models. The novel approach of linking multiple disease models with correlations incorporated provides a new methodological option primarily for modellers who undertake research on comorbidities. It also has potential for wider applications in informing decisions on commissioning of healthcare services and long-term priority setting across diseases and healthcare programmes, hence ultimately contributing to the improvement of population health.

Item Type: Thesis (PhD)
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield)
Identification Number/EthosID: uk.bl.ethos.696005
Depositing User: Ji Hee Youn
Date Deposited: 04 Nov 2016 13:13
Last Modified: 12 Oct 2018 09:29
URI: http://etheses.whiterose.ac.uk/id/eprint/13982

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