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The Impact of Different DCE-Based Approaches When Anchoring Utility Scores

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  • Richard Norman

    (Curtin University)

  • Brendan Mulhern

    (University of Technology Sydney)

  • Rosalie Viney

    (University of Technology Sydney)

Abstract

Background Discrete choice experiments (DCEs) have been proposed as a method to estimate utility weights for health states within utility instruments. However, the most appropriate method to anchor the utility values on the full health to dead quality-adjusted life year (QALY) scale remains uncertain. We test four approaches to anchoring in which dead is valued at zero and full health at one. Methods We use data from two DCEs valuing EQ-5D-3L and EQ-5D-5L health states, which presented pairs of health profiles with an associated duration, and a dead option. The approaches to anchoring the results on the required scale were (1) using only preferences between non-dead health profiles; (2) including the dead data, treating it as a health profile with zero duration; (3) explicitly modelling both duration and dead; and (4) using the preferences regarding the dead health state as an external anchor subsequent to the estimation of approach 1. Results All approaches lead to differences in the scale of utility decrements, but not the ranking of EQ-5D health states. The models differ in their ability to predict preferences around dead health states, and the characteristics of the value sets in terms of their range and the proportion of states valued as worse than dead. Discussion Appropriate anchoring of DCEs with or without complementary time trade-off (TTO) data remains unresolved, and the method chosen will impact on health resource allocation decision making employing the value sets.

Suggested Citation

  • Richard Norman & Brendan Mulhern & Rosalie Viney, 2016. "The Impact of Different DCE-Based Approaches When Anchoring Utility Scores," PharmacoEconomics, Springer, vol. 34(8), pages 805-814, August.
  • Handle: RePEc:spr:pharme:v:34:y:2016:i:8:d:10.1007_s40273-016-0399-7
    DOI: 10.1007/s40273-016-0399-7
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    References listed on IDEAS

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    1. Richard Norman & Paula Cronin & Rosalie Viney, 2013. "A Pilot Discrete Choice Experiment to Explore Preferences for EQ-5D-5L Health States," Applied Health Economics and Health Policy, Springer, vol. 11(3), pages 287-298, June.
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    Cited by:

    1. Michał Jakubczyk & Michał Lewandowski, 2024. "How sure are you? — the properties of self-reported conviction in the elicitation of health preferences with discrete choice experiments," Theory and Decision, Springer, vol. 96(3), pages 351-368, May.
    2. Michał Jakubczyk & Dominik Golicki, 2020. "Elicitation and modelling of imprecise utility of health states," Theory and Decision, Springer, vol. 88(1), pages 51-71, February.
    3. Brendan Mulhern & Richard Norman & Koonal Shah & Nick Bansback & Louise Longworth & Rosalie Viney, 2018. "How Should Discrete Choice Experiments with Duration Choice Sets Be Presented for the Valuation of Health States?," Medical Decision Making, , vol. 38(3), pages 306-318, April.
    4. Paul F M Krabbe & Ruslan Jabrayilov & Patrick Detzel & Livia Dainelli & Karin M Vermeulen & Antoinette D I van Asselt, 2020. "A two-step procedure to generate utilities for the Infant health-related Quality of life Instrument (IQI)," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-14, April.
    5. Koonal K. Shah & Bryan Bennett & Andrew Lenny & Louise Longworth & John E. Brazier & Mark Oppe & A. Simon Pickard & James W. Shaw, 2021. "Adapting preference-based utility measures to capture the impact of cancer treatment-related symptoms," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(8), pages 1301-1309, November.
    6. Laura Vallejo-Torres & Borja García-Lorenzo & Oliver Rivero-Arias & José Luis Pinto-Prades, 2020. "The societal monetary value of a QALY associated with EQ-5D-3L health gains," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(3), pages 363-379, April.
    7. Osman, Ahmed M.Y. & Wu, Jing & He, Xiaoning & Chen, Gang, 2021. "Eliciting SF-6Dv2 health state utilities using an anchored best-worst scaling technique," Social Science & Medicine, Elsevier, vol. 279(C).

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