Designing and undertaking a health economics study of digital health interventions
Designing and undertaking a health economics study of digital health interventions
This paper introduces and discusses key issues in the economic evaluation of digital health interventions. The purpose is to stimulate debate so that existing economic techniques may be refined or new methods developed. The paper does not seek to provide definitive guidance on appropriate methods of economic analysis for digital health interventions.
We describe existing guides and analytical frameworks that have been suggested for the economic evaluation of health care interventions. Using selected examples of digital health interventions, we assess how well existing guides and frameworks align to digital health interventions. We show that digital health interventions may be best characterised as complex interventions in complex systems. Key features of complexity relate to intervention complexity, outcome complexity and causal pathway complexity, with much of this driven by iterative intervention development over time and uncertainty regarding likely reach of the interventions amongst the relevant population. These characteristics imply that more complex methods of economic evaluation are likely to be better able to capture fully the impact of the intervention on costs and benefits over the appropriate time horizon. This complexity includes wider measurement of costs and benefits, and a modelling framework that is able to capture dynamic interactions between the intervention, the population of interest and the environment. We recommend that future research should develop and apply more flexible modelling techniques, to allow better prediction of the inter-dependency between interventions and important environmental influences.
852-860
McNamee, Paul
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Murray, Elizabeth
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Kelly, Michael P.
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Bojke, Laura
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Chilcott, Jim
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Fischer, Alastair
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West, Robert
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Yardley, Lucy
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November 2016
McNamee, Paul
ebb7a998-46dd-42e1-9579-53e48cf3350b
Murray, Elizabeth
cb300780-9041-44af-9ae5-e13531eb23b8
Kelly, Michael P.
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Bojke, Laura
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Chilcott, Jim
82da7d41-8f4a-492f-b640-daa5da81dafb
Fischer, Alastair
950dc5e7-0e15-49b6-ac29-91ff5bc5a059
West, Robert
de79ca55-bbe3-415f-bec6-a78f6ebb3d9f
Yardley, Lucy
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McNamee, Paul, Murray, Elizabeth, Kelly, Michael P., Bojke, Laura, Chilcott, Jim, Fischer, Alastair, West, Robert and Yardley, Lucy
(2016)
Designing and undertaking a health economics study of digital health interventions.
American Journal of Preventive Medicine, 51 (5), .
(doi:10.1016/j.amepre.2016.05.007).
Abstract
This paper introduces and discusses key issues in the economic evaluation of digital health interventions. The purpose is to stimulate debate so that existing economic techniques may be refined or new methods developed. The paper does not seek to provide definitive guidance on appropriate methods of economic analysis for digital health interventions.
We describe existing guides and analytical frameworks that have been suggested for the economic evaluation of health care interventions. Using selected examples of digital health interventions, we assess how well existing guides and frameworks align to digital health interventions. We show that digital health interventions may be best characterised as complex interventions in complex systems. Key features of complexity relate to intervention complexity, outcome complexity and causal pathway complexity, with much of this driven by iterative intervention development over time and uncertainty regarding likely reach of the interventions amongst the relevant population. These characteristics imply that more complex methods of economic evaluation are likely to be better able to capture fully the impact of the intervention on costs and benefits over the appropriate time horizon. This complexity includes wider measurement of costs and benefits, and a modelling framework that is able to capture dynamic interactions between the intervention, the population of interest and the environment. We recommend that future research should develop and apply more flexible modelling techniques, to allow better prediction of the inter-dependency between interventions and important environmental influences.
Text
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Accepted/In Press date: 18 April 2016
e-pub ahead of print date: 13 October 2016
Published date: November 2016
Identifiers
Local EPrints ID: 393472
URI: http://eprints.soton.ac.uk/id/eprint/393472
ISSN: 0749-3797
PURE UUID: 44828723-ed1d-43fe-a64d-96248cf72d74
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Date deposited: 27 Apr 2016 10:50
Last modified: 15 Mar 2024 05:32
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Contributors
Author:
Paul McNamee
Author:
Elizabeth Murray
Author:
Michael P. Kelly
Author:
Laura Bojke
Author:
Jim Chilcott
Author:
Alastair Fischer
Author:
Robert West
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