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. 2016 Dec;34(12):1195-1209.
doi: 10.1007/s40273-016-0429-5.

Using Best-Worst Scaling to Investigate Preferences in Health Care

Kei Long Cheung  1 , Ben F M Wijnen  2   3 , Ilene L Hollin  4 , Ellen M Janssen  4 , John F Bridges  4 , Silvia M A A Evers  2 , Mickael Hiligsmann  2
Affiliations

Using Best-Worst Scaling to Investigate Preferences in Health Care

Kei Long Cheung et al. Pharmacoeconomics. 2016 Dec.

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.

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Conflict of interest statement

All authors (Kei Long Cheung, Ben Wijnen, Ilene Hollin, Ellen Janssen, John Bridges, Silvia Evers and Mickael Hiligsmann) declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Examples of a best–worst scaling (BWS) object case, b BWS profile case and c BWS multi-profile case
Fig. 2
Fig. 2
Flow chart of the study identification process. BWS best–worst scaling
Fig. 3
Fig. 3
Cumulative numbers of best–worst scaling (BWS) studies by year and by BWS case type
Fig. 4
Fig. 4
Analytical methods used per year: a best–worst scaling (BWS) object case, b BWS profile case and c BWS multi-profile case. Max diff maximum difference scaling, MNL multinomial logistic regression, NR not reported
Fig. 4
Fig. 4
Analytical methods used per year: a best–worst scaling (BWS) object case, b BWS profile case and c BWS multi-profile case. Max diff maximum difference scaling, MNL multinomial logistic regression, NR not reported
See this image and copyright information in PMC

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