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A Systematic Review Comparing the Acceptability, Validity and Concordance of Discrete Choice Experiments and Best–Worst Scaling for Eliciting Preferences in Healthcare

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  • Jennifer A. Whitty

    (University of East Anglia)

  • Ana Sofia Oliveira Gonçalves

    (University of East Anglia)

Abstract

Objective The aim of this study was to compare the acceptability, validity and concordance of discrete choice experiment (DCE) and best–worst scaling (BWS) stated preference approaches in health. Methods A systematic search of EMBASE, Medline, AMED, PubMed, CINAHL, Cochrane Library and EconLit databases was undertaken in October to December 2016 without date restriction. Studies were included if they were published in English, presented empirical data related to the administration or findings of traditional format DCE and object-, profile- or multiprofile-case BWS, and were related to health. Study quality was assessed using the PREFS checklist. Results Fourteen articles describing 12 studies were included, comparing DCE with profile-case BWS (9 studies), DCE and multiprofile-case BWS (1 study), and profile- and multiprofile-case BWS (2 studies). Although limited and inconsistent, the balance of evidence suggests that preferences derived from DCE and profile-case BWS may not be concordant, regardless of the decision context. Preferences estimated from DCE and multiprofile-case BWS may be concordant (single study). Profile- and multiprofile-case BWS appear more statistically efficient than DCE, but no evidence is available to suggest they have a greater response efficiency. Little evidence suggests superior validity for one format over another. Participant acceptability may favour DCE, which had a lower self-reported task difficulty and was preferred over profile-case BWS in a priority setting but not necessarily in other decision contexts. Conclusion DCE and profile-case BWS may be of equal validity but give different preference estimates regardless of the health context; thus, they may be measuring different constructs. Therefore, choice between methods is likely to be based on normative considerations related to coherence with theoretical frameworks and on pragmatic considerations related to ease of data collection.

Suggested Citation

  • Jennifer A. Whitty & Ana Sofia Oliveira Gonçalves, 2018. "A Systematic Review Comparing the Acceptability, Validity and Concordance of Discrete Choice Experiments and Best–Worst Scaling for Eliciting Preferences in Healthcare," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 11(3), pages 301-317, June.
    • Handle: RePEc:spr:patien:v:11:y:2018:i:3:d:10.1007_s40271-017-0288-y
    DOI: 10.1007/s40271-017-0288-y
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    References listed on IDEAS

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    1. Drummond, Michael F. & Sculpher, Mark J. & Torrance, George W. & O'Brien, Bernie J. & Stoddart, Greg L., 2005. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 3, number 9780198529453.
    2. Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680.
    3. Joanna Coast & Elisabeth Huynh & Philip Kinghorn & Terry Flynn, 2016. "Complex Valuation: Applying Ideas from the Complex Intervention Framework to Valuation of a New Measure for End-of-Life Care," PharmacoEconomics, Springer, vol. 34(5), pages 499-508, May.
    4. Mandy Ryan & Verity Watson & Vikki Entwistle, 2009. "Rationalising the ‘irrational’: a think aloud study of discrete choice experiment responses," Health Economics, John Wiley & Sons, Ltd., vol. 18(3), pages 321-336, March.
    5. Olsen, Jan Abel & Donaldson, Cam, 1998. "Helicopters, hearts and hips: Using willingness to pay to set priorities for public sector health care programmes," Social Science & Medicine, Elsevier, vol. 46(1), pages 1-12, January.
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    1. Axel C. Mühlbacher & Andrew Sadler & Yvonne Jordan, 2022. "Population preferences for non-pharmaceutical interventions to control the SARS-CoV-2 pandemic: trade-offs among public health, individual rights, and economics," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(9), pages 1483-1496, December.
    2. Harvard, Stephanie & Werker, Gregory R. & Silva, Diego S., 2020. "Social, ethical, and other value judgments in health economics modelling," Social Science & Medicine, Elsevier, vol. 253(C).
    3. Elizabeth A Asiago-Reddy & John McPeak & Riccardo Scarpa & Amy Braksmajer & Nicola Ruszkowski & James McMahon & Andrew S London, 2022. "Perceived access to PrEP as a critical step in engagement: A qualitative analysis and discrete choice experiment among young men who have sex with men," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-21, January.
    4. Shimeng Liu & Yingyao Chen & Shunping Li & Ningze Xu & Chengxiang Tang & Yan Wei, 2021. "What Are the Important Factors Influencing the Recruitment and Retention of Doctoral Students in a Public Health Setting? A Discrete Choice Experiment Survey in China," IJERPH, MDPI, vol. 18(18), pages 1-14, September.

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