Gc, Vijay (2018) Cost-effectiveness of very brief interventions promoting physical activity: an application of the iterative approach in decision making. Doctoral thesis, University of East Anglia.
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Abstract
Economic evaluations are increasingly used in healthcare decision-making. An iterative approach to economic evaluation has been proposed as good practice in which economic evaluations are re-performed as new evidence becomes available throughout the lifecycle of health technology. Decision analytical models play a key role within this process as they provide a structure in which evidence from a range of sources can be synthesised along with Bayesian updating in order to answer the cost-effectiveness problems. This allows the use of the value of information (VoI) methods that help inform further research priority setting.
Physical activity (PA) interventions, in general, are considered good value for money however little is known about the cost-effectiveness of very brief interventions (VBIs) in PA promotion. The thesis aims to explore the feasibility of using an iterative approach to decision-making in the context of the cost-effectiveness of VBIs to promote PA. Using VBI as a case study, this thesis explores the practical and methodological issues of applying an iterative approach to economic evaluation and considers potential reasons as to why the framework has not been widely implemented to date.
Using VBI as a case study provided the opportunity to examine the challenges involved in undertaking an economic evaluation of very brief PA interventions in real time. This thesis explored the feasibility of applying the iterative process to evaluate the cost-effectiveness of VBIs in PA promotion in a time-constrained setting. A decision analytic model was developed at the outset of the thesis and employed iteratively to handle the evolving evidence base of VBIs in PA promotion. Although there are several merits of applying such a framework in real life economic evaluation, in the case of the VBI study, it was not viable to fully exploit VoI analyses and follow the process iteratively.
Item Type: | Thesis (Doctoral) |
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Faculty \ School: | Faculty of Medicine and Health Sciences > Norwich Medical School |
Depositing User: | Zoe White |
Date Deposited: | 22 May 2019 13:24 |
Last Modified: | 31 Dec 2020 01:38 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/71096 |
DOI: |
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