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Is Best–Worst Scaling Suitable for Health State Valuation? A Comparison with Discrete Choice Experiments

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  • Nicolas Krucien
  • Verity Watson
  • Mandy Ryan

Abstract

Health utility indices (HUIs) are widely used in economic evaluation. The best–worst scaling (BWS) method is being used to value dimensions of HUIs. However, little is known about the properties of this method. This paper investigates the validity of the BWS method to develop HUI, comparing it to another ordinal valuation method, the discrete choice experiment (DCE). Using a parametric approach, we find a low level of concordance between the two methods, with evidence of preference reversals. BWS responses are subject to decision biases, with significant effects on individuals' preferences. Non parametric tests indicate that BWS data has lower stability, monotonicity and continuity compared to DCE data, suggesting that the BWS provides lower quality data. As a consequence, for both theoretical and technical reasons, practitioners should be cautious both about using the BWS method to measure health‐related preferences, and using HUI based on BWS data. Given existing evidence, it seems that the DCE method is a better method, at least because its limitations (and measurement properties) have been extensively researched. Copyright © 2016 John Wiley & Sons, Ltd.

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  • Nicolas Krucien & Verity Watson & Mandy Ryan, 2017. "Is Best–Worst Scaling Suitable for Health State Valuation? A Comparison with Discrete Choice Experiments," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1-16, December.
    • Handle: RePEc:wly:hlthec:v:26:y:2017:i:12:p:e1-e16
    DOI: 10.1002/hec.3459
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    Cited by:

    1. Nicolet, Anna & Perraudin, Clémence & Krucien, Nicolas & Wagner, Joël & Peytremann-Bridevaux, Isabelle & Marti, Joachim, 2023. "Preferences of older adults for healthcare models designed to improve care coordination: Evidence from Western Switzerland," Health Policy, Elsevier, vol. 132(C).
    2. Ivan Sever & Miroslav Verbič & Eva Klaric Sever, 2020. "Estimating Attribute-Specific Willingness-to-Pay Values from a Health Care Contingent Valuation Study: A Best–Worst Choice Approach," Applied Health Economics and Health Policy, Springer, vol. 18(1), pages 97-107, February.
    3. Brendan Mulhern & Richard Norman & Deborah J. Street & Rosalie Viney, 2019. "One Method, Many Methodological Choices: A Structured Review of Discrete-Choice Experiments for Health State Valuation," PharmacoEconomics, Springer, vol. 37(1), pages 29-43, January.
    4. Kim Dalziel & Max Catchpool & Borja García-Lorenzo & Inigo Gorostiza & Richard Norman & Oliver Rivero-Arias, 2020. "Feasibility, Validity and Differences in Adolescent and Adult EQ-5D-Y Health State Valuation in Australia and Spain: An Application of Best–Worst Scaling," PharmacoEconomics, Springer, vol. 38(5), pages 499-513, May.
    5. Aizaki, Hideo & Fogarty, James, 2019. "An R package and tutorial for case 2 best–worst scaling," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    6. Soekhai, V. & Donkers, B. & Levitan, B. & de Bekker-Grob, E.W., 2021. "Case 2 best-worst scaling: For good or for bad but not for both," Journal of choice modelling, Elsevier, vol. 41(C).

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