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Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues

Author

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  • Axel C. Mühlbacher

    (Hochschule Neubrandenburg)

  • Peter Zweifel

    (University of Zürich)

  • Anika Kaczynski

    (Hochschule Neubrandenburg)

  • F. Reed Johnson

    (Duke Clinical Research Institute, Duke University)

Abstract

For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multi-attribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and worst items in each choice set. While a companion paper describes the different types of BWS, application and their advantages and downsides, this contribution expounds their relationships with microeconomic theory, which also have implications for statistical inference. This article devotes to the microeconomic foundations of preference measurement, also addressing issues such as scale invariance and scale heterogeneity. Furthermore the paper discusses the basics of preference measurement using rating, ranking and stated choice data in the light of the findings of the preceding section. Moreover the paper gives an introduction to the use of stated choice data and juxtaposes BWS with the microeconomic foundations.

Suggested Citation

  • Axel C. Mühlbacher & Peter Zweifel & Anika Kaczynski & F. Reed Johnson, 2016. "Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues," Health Economics Review, Springer, vol. 6(1), pages 1-12, December.
    • Handle: RePEc:spr:hecrev:v:6:y:2016:i:1:d:10.1186_s13561-015-0077-z
    DOI: 10.1186/s13561-015-0077-z
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    References listed on IDEAS

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    1. Louviere, Jordan J. & Islam, Towhidul, 2008. "A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling," Journal of Business Research, Elsevier, vol. 61(9), pages 903-911, September.
    2. Marti, Joachim, 2012. "A best–worst scaling survey of adolescents' level of concern for health and non-health consequences of smoking," Social Science & Medicine, Elsevier, vol. 75(1), pages 87-97.
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    4. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    5. F. Reed Johnson & Ateesha F. Mohamed & Semra Özdemir & Deborah A. Marshall & Kathryn A. Phillips, 2011. "How does cost matter in health‐care discrete‐choice experiments?," Health Economics, John Wiley & Sons, Ltd., vol. 20(3), pages 323-330, March.
    6. Harry Telser & Peter Zweifel, 2007. "Validity of discrete-choice experiments evidence for health risk reduction," Applied Economics, Taylor & Francis Journals, vol. 39(1), pages 69-78.
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    Cited by:

    1. Axel Mühlbacher & Anika Kaczynski & Peter Zweifel & F. Johnson, 2015. "Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview," Health Economics Review, Springer, vol. 6(1), pages 1-14, December.
    2. Tatenda T Yemeke & Elizabeth E Kiracho & Aloysius Mutebi & Rebecca R Apolot & Anthony Ssebagereka & Daniel R Evans & Sachiko Ozawa, 2020. "Health versus other sectors: Multisectoral resource allocation preferences in Mukono district, Uganda," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-15, July.
    3. Axel C. Mühlbacher & Anika Kaczynski & Peter Zweifel & F. Reed Johnson, 2016. "Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview," Health Economics Review, Springer, vol. 6(1), pages 1-14, December.
    4. Xuan, Bui Bich & Ngoc, Quach Thi Khanh & Börger, Tobias, 2022. "Fisher preferences for marine litter interventions in Vietnam," Ecological Economics, Elsevier, vol. 200(C).
    5. 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).
    6. Peter Zweifel, 2022. "Preference measurement in health using experiments," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(1), pages 49-66, March.

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