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Parameterising User Uptake in Economic Evaluations: The role of discrete choice experiments

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  • Fern Terris‐Prestholt
  • Matthew Quaife
  • Peter Vickerman

Abstract

Model‐based economic evaluations of new interventions have shown that user behaviour (uptake) is a critical driver of overall impact achieved. However, early economic evaluations, prior to introduction, often rely on assumed levels of uptake based on expert opinion or uptake of similar interventions. In addition to the likely uncertainty surrounding these uptake assumptions, they also do not allow for uptake to be a function of product, intervention, or user characteristics. This letter proposes using uptake projections from discrete choice experiments (DCE) to better parameterize uptake and substitution in cost‐effectiveness models. A simple impact model is developed and illustrated using an example from the HIV prevention field in South Africa. Comparison between the conventional approach and the DCE‐based approach shows that, in our example, DCE‐based impact predictions varied by up to 50% from conventional estimates and provided far more nuanced projections. In the absence of observed uptake data and to model the effect of variations in intervention characteristics, DCE‐based uptake predictions are likely to greatly improve models parameterizing uptake solely based on expert opinion. This is particularly important for global and national level decision making around introducing new and probably more expensive interventions, particularly where resources are most constrained.

Suggested Citation

  • Fern Terris‐Prestholt & Matthew Quaife & Peter Vickerman, 2016. "Parameterising User Uptake in Economic Evaluations: The role of discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 25(S1), pages 116-123, February.
  • Handle: RePEc:wly:hlthec:v:25:y:2016:i:s1:p:116-123
    DOI: 10.1002/hec.3297
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    References listed on IDEAS

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    Cited by:

    1. Chandoevwit, Worawan & Wasi, Nada, 2020. "Incorporating discrete choice experiments into policy decisions: Case of designing public long-term care insurance," Social Science & Medicine, Elsevier, vol. 258(C).
    2. Catherine Pitt & Anna Vassall & Yot Teerawattananon & Ulla K. Griffiths & Lorna Guinness & Damian Walker & Nicola Foster & Kara Hanson, 2016. "Foreword: Health Economic Evaluations in Low‐ and Middle‐income Countries: Methodological Issues and Challenges for Priority Setting," Health Economics, John Wiley & Sons, Ltd., vol. 25(S1), pages 1-5, February.
    3. Anna Vassall & Lindsay Mangham‐Jefferies & Gabriela B. Gomez & Catherine Pitt & Nicola Foster, 2016. "Incorporating Demand and Supply Constraints into Economic Evaluations in Low‐Income and Middle‐Income Countries," Health Economics, John Wiley & Sons, Ltd., vol. 25(S1), pages 95-115, February.
    4. Matthew Quaife & Fern Terris-Prestholt & Gian Luca Di Tanna & Peter Vickerman, 2018. "How well do discrete choice experiments predict health choices? A systematic review and meta-analysis of external validity," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(8), pages 1053-1066, November.

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