Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues.
Date
2016-12
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Citation Stats
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.
Type
Department
Description
Provenance
Citation
Permalink
Published Version (Please cite this version)
Publication Info
Mühlbacher, Axel C, Peter Zweifel, Anika Kaczynski and F Reed Johnson (2016). Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues. Health Econ Rev, 6(1). p. 5. 10.1186/s13561-015-0077-z Retrieved from https://hdl.handle.net/10161/11718.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Collections
Scholars@Duke
F. Reed Johnson
F. Reed Johnson, PhD, has more than 40 years of academic and research experience in health and environmental economics. He has served on the faculties of several universities in the United States, Canada, and Sweden, and as Distinguished Fellow at Research Triangle Institute. He currently is Senior Research Scholar in the Duke Clinical Research Institute. As a staff member in the US Environmental Protection Agency’s environmental economics research program during the 1980s, Reed helped pioneer the development of basic non-market valuation techniques which are widely used for benefit-cost analysis in health and environmental economics. He has designed and analyzed numerous surveys for measuring preferences for and value of health outcomes, health risk reductions, and improved environmental quality.
Dr. Johnson has over 140 publications in books and peer-reviewed journals. His research has been published in various medical journals, the Review of Economics and Statistics, Journal of Health Economics, Medical Decision Making, Health Economics, Value in Health, Journal of Policy Analysis and Management, and other journals. He has coauthored a book on techniques for using existing environmental and health value estimates for policy analysis.
His current research involves quantifying patients’ willingness to accept sideeffect risks in return for therapeutic benefits and estimating general time equivalences among health states. He led the first FDA sponsored study on patients’ willingness to accept benefit-risk tradeoffs for new health technologies. The study was used to develop recent FDA guidance on submitting patient-preference data to support regulatory reviews of medical devices.
Areas of expertise: Clinical Decision Sciences, Health Measurement, Health Policy, and Health Economics
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.