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Using Best–Worst Scaling to Investigate Preferences in Health Care

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  • Kei Long Cheung

    (Maastricht University)

  • Ben F. M. Wijnen

    (Maastricht University
    Epilepsy Centre Kempenhaeghe)

  • Ilene L. Hollin

    (Johns Hopkins Bloomberg School of Public Health)

  • Ellen M. Janssen

    (Johns Hopkins Bloomberg School of Public Health)

  • John F. Bridges

    (Johns Hopkins Bloomberg School of Public Health)

  • Silvia M. A. A. Evers

    (Maastricht University)

  • Mickael Hiligsmann

    (Maastricht University)

Abstract

Introduction Best–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS. Methods A systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further. Results A total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders. Conclusion Use of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods.

Suggested Citation

  • Kei Long Cheung & Ben F. M. Wijnen & Ilene L. Hollin & Ellen M. Janssen & John F. Bridges & Silvia M. A. A. Evers & Mickael Hiligsmann, 2016. "Using Best–Worst Scaling to Investigate Preferences in Health Care," PharmacoEconomics, Springer, vol. 34(12), pages 1195-1209, December.
    • Handle: RePEc:spr:pharme:v:34:y:2016:i:12:d:10.1007_s40273-016-0429-5
    DOI: 10.1007/s40273-016-0429-5
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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. Lancsar, Emily & Louviere, Jordan & Donaldson, Cam & Currie, Gillian & Burgess, Leonie, 2013. "Best worst discrete choice experiments in health: Methods and an application," Social Science & Medicine, Elsevier, vol. 76(C), pages 74-82.
    3. 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.
    4. Peter Ghijben & Emily Lancsar & Silva Zavarsek, 2014. "Preferences for Oral Anticoagulants in Atrial Fibrillation: a Best–Best Discrete Choice Experiment," PharmacoEconomics, Springer, vol. 32(11), pages 1115-1127, November.
    5. Coast, Joanna & Flynn, Terry N. & Natarajan, Lucy & Sproston, Kerry & Lewis, Jane & Louviere, Jordan J. & Peters, Tim J., 2008. "Valuing the ICECAP capability index for older people," Social Science & Medicine, Elsevier, vol. 67(5), pages 874-882, September.
    6. Eve Wittenberg & Monica Bharel & Adrianna Saada & Emely Santiago & John Bridges & Linda Weinreb, 2015. "Measuring the Preferences of Homeless Women for Cervical Cancer Screening Interventions: Development of a Best–Worst Scaling Survey," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 8(5), pages 455-467, October.
    7. Terry N. Flynn & Elisabeth Huynh & Tim J. Peters & Hareth Al‐Janabi & Sam Clemens & Alison Moody & Joanna Coast, 2015. "Scoring the Icecap‐a Capability Instrument. Estimation of a UK General Population Tariff," Health Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 258-269, March.
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    8. Vikas Soekhai & Esther W. Bekker-Grob & Alan R. Ellis & Caroline M. Vass, 2019. "Discrete Choice Experiments in Health Economics: Past, Present and Future," PharmacoEconomics, Springer, vol. 37(2), pages 201-226, February.
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