Abstract
Background: Discrete choice experiment (DCE) as a tool that can measure medical stakeholders' preferences especially patients recently has been increasingly applied in health care.Objective: The aim of this study was to examine the hotspots and trends of the application of DCE in health care and to provide reference and direction for further development of DCE in the future.Method: A bibliometric method was implemented using the Web of Science (WoS) Core Collection for the period from the database established to December 8, 2020. The data files are imported into CiteSpace and Excel to analyze and visualize the annual volume of productive, authors, countries, cited journals, cited articles, and keywords.Results: A total of 1,811 articles were retrieved, then we read the abstract of each paper one by one, and 1,562 articles were included after screening, with an exponential increase in publication volume. John F. P. Bridges contributed to 40 publications and ranked first, followed by F. Reed Johnson (n = 37), Julie Ratcliffe (n = 36). The majority of the papers were conducted in the United States (n = 513) and the United Kingdom (n = 433). The top three cited journals were “Health Economics” (n = 981), “Value in Health” (n = 893), and “Pharmaceutical Economics” (n = 774), and the top three articles were “Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force,” “Conjoint analysis applications in health-a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force,” and “Discrete choice experiments in health economics: a review of the literature.” The research hotspots and trends included “health technology assessment,” “survival,” “preference based measure,” and “health state valuation.”Conclusion: The size of the literature about DCE studies in health care showed a noticeable increase in the past decade. The application of DCE in health care remains in an early growth phase, and “health technology assessment,” “survival,” “preference based measure,” and “health state valuation” reflected the latest research hotpots and future trends.
Highlights
Discrete choice experiment (DCE), which grew primarily in Australia in the late 1970s, was pioneered by Louviere and Woodworth and introduced into the field of health economics by Propper [1]
The results showed that lung cancer patients tended to attach more importance to curative effect and quality of life (QoL) attributes, and overall survival rate was the most important of curative effect attributes, which was consistent with the results of Khan et al [42] and Havrilesky et al [43] using DCE to evaluate the preferences of patients with Hodgkin’s lymphoma and ovarian cancer
It has been applied more and more frequently in health care, and modern people are paying more and more attention to health status and pursuing better life quality, which provides
Summary
Discrete choice experiment (DCE), which grew primarily in Australia in the late 1970s, was pioneered by Louviere and Woodworth and introduced into the field of health economics by Propper [1]. DCE has gradually become the most commonly used method to quantify patients’ health preferences [5], medical workers’ employment preferences [6,7,8], and other stakeholders’ preferences in health care, so as to provide decision-making basis for policy makers. Discrete choice experiment is one kind of method of stated preferences [10] that includes cardinal methods (time trade-off, standard gamble, and visual analog scale) and ordinal methods (DCE, ranking exercises, and ordered categorical responses) [3]. Compared with other ordinal methods, such as ranking exercises, DCE shows the advantage of simulating a real-world situation where medical treatment or nursing attributes do not appear in isolation and being closer to the choice of patients [11]. Discrete choice experiment (DCE) as a tool that can measure medical stakeholders’ preferences especially patients recently has been increasingly applied in health care
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