Best-worst scaling (BWS), also known as maximum-difference scaling, is a multiattribute approach to measuring preferences. BWS aims at the analysis of preferences regarding a set of attributes, their levels or alternatives. It is a stated-preference method based on the assumption that respondents are capable of making judgments regarding the best and the worst (or the most and least important, respectively) out of three or more elements of a choice-set. As is true of discrete choice experiments (DCE) generally, BWS avoids the known weaknesses of rating and ranking scales while holding the promise of generating additional information by making respondents choose twice, namely the best as well as the worst criteria. A systematic literature review found 53 BWS applications in health and healthcare. This article expounds possibilities of application, the underlying theoretical concepts and the implementation of BWS in its three variants: ‘object case’, ‘profile case’, ‘multiprofile case’. This paper contains a survey of BWS methods and revolves around study design, experimental design, and data analysis. Moreover the article discusses the strengths and weaknesses of the three types of BWS distinguished and offered an outlook. A companion paper focuses on special issues of theory and statistical inference confronting BWS in preference measurement.

There is growing interest in discrete-choice experiment (DCE) as a method to elicit consumers’ preferences in the health care sector. Increasingly this method is used to determine willingness to pay (WTP) for health-related goods. However, its external validity in the health care domain has not been investigated until now. This paper examines the external validity of DCE concerning the reduction of a health risk. Convergent validity is examined by comparing the value of a statistical life with other preference elicitation techniques, such as revealed preference. Criterion validity is shown by comparing WTP values derived from stated choices in the experiment with those derived from actual choices made by the same individuals. Both tests provide strong evidence in favour of external validity of the DCE method.

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.

This editorial presents a critical review of the health model pioneered by Michael Grossman (MGM) in 1972 [8]. It argues that whereas the MGM has great charm for economists, it fails to achieve acceptance by interested laypersons and policy makers. The main reasons for this failure are: (1) the assumption of a long and fixed planning horizon, (2) a fixed ratio between individuals healthcare expenditure and the cost of their own health-enhancing efforts regardless of their state of health, and (3) their presumed ability to restore the state of health deemed optimal at a speed that does not depend on their state of health. An alternative formulation emphasizing the stochastic nature of health production is sketched that conceptually provides solutions to these three problems. In addition, it permits discarding a popular medical argument that seems to undermine the very basis of welfare analysis applied to health by claiming preferences to be unstable: “As long as you are healthy, you don’t give a damn, but as soon as you are sick, you are prepared to sacrifice everything to restore your health.” The editorial concludes by outlining a research program that may help health economists break away from their MGM fixation.