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Valuation of preference-based measures: can existing preference data be used to select a smaller sample of health states?

Author

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  • Samer A. Kharroubi

    (American University of Beirut)

  • Donna Rowen

    (The University of Sheffield)

Abstract

Background Different countries have different preferences regarding health, and there are different value sets for popular preference-based measures across different countries. However, the cost of collecting data to generate country-specific value sets can be prohibitive for countries with smaller population size or low- and middle-income countries (LMIC). This paper explores whether existing preference weights could be modelled alongside a small own country valuation study to generate representative estimates. This is explored using a case study modelling UK data alongside smaller US samples to generate US estimates. Methods We analyse EQ-5D valuation data derived from representative samples of the US and UK populations using time trade-off to value 42 health states. A nonparametric Bayesian model was applied to estimate a US value set using the full UK dataset and subsets of the US dataset for 10, 15, 20 and 25 health states. Estimates are compared to a US value set estimated using US values alone using mean predictions and root mean square error. Results The results suggest that using US data elicited for 20 health states alongside the existing UK data produces similar predicted mean valuations and RMSE as the US value set, while 25 health states produce the exact features. Conclusions The promising results suggest that existing preference data could be combined with a small valuation study in a new country to generate preference weights, making own country value sets more achievable for LMIC. Further research is encouraged.

Suggested Citation

  • Samer A. Kharroubi & Donna Rowen, 2019. "Valuation of preference-based measures: can existing preference data be used to select a smaller sample of health states?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(2), pages 245-255, March.
    • Handle: RePEc:spr:eujhec:v:20:y:2019:i:2:d:10.1007_s10198-018-0991-1
    DOI: 10.1007/s10198-018-0991-1
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    References listed on IDEAS

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    1. Brazier, John & Ratcliffe, Julie & Salomon, Joshua & Tsuchiya, Aki, 2016. "Measuring and Valuing Health Benefits for Economic Evaluation," OUP Catalogue, Oxford University Press, edition 2, number 9780198725923, Decembrie.
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    4. Donna Rowen & John Brazier & Roberta Ara & Ismail Azzabi Zouraq, 2017. "The Role of Condition-Specific Preference-Based Measures in Health Technology Assessment," PharmacoEconomics, Springer, vol. 35(1), pages 33-41, December.
    5. Xavier Badia & Montserrat Roset & Michael Herdman & Paul Kind, 2001. "A Comparison of United Kingdom and Spanish General Population Time Trade-off Values for EQ-5D Health States," Medical Decision Making, , vol. 21(1), pages 7-16, February.
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    Cited by:

    1. Samer A. Kharroubi & Yara Beyh & Marwa Diab El Harake & Dalia Dawoud & Donna Rowen & John Brazier, 2020. "Examining the Feasibility and Acceptability of Valuing the Arabic Version of SF-6D in a Lebanese Population," IJERPH, MDPI, vol. 17(3), pages 1-15, February.
    2. Samer A. Kharroubi, 2021. "Modeling SF-6D Health Utilities: Is Bayesian Approach Appropriate?," IJERPH, MDPI, vol. 18(16), pages 1-14, August.

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    More about this item

    Keywords

    Preference-based health measures; Nonparametric Bayesian methods; Time trade-off; EQ-5D;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • I1 - Health, Education, and Welfare - - Health

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