卫生技术
多项式logistic回归
任务(项目管理)
偏爱
人口
公共卫生
心理学
精算学
营销
社会心理学
医学
业务
经济
医疗保健
环境卫生
计算机科学
微观经济学
护理部
经济增长
管理
机器学习
作者
Jennifer A. Whitty,Julie Ratcliffe,Gang Chen,Paul Scuffham
标识
DOI:10.1177/0272989x14526640
摘要
Background. Ethical, economic, political, and legitimacy arguments support the consideration of public preferences in health technology decision making. The objective was to assess public preferences for funding new health technologies and to compare a profile case best-worst scaling (BWS) and traditional discrete choice experiment (DCE) method. Methods. An online survey consisting of a DCE and BWS task was completed by 930 adults recruited via an Internet panel. Respondents traded between 7 technology attributes. Participation quotas broadly reflected the population of Queensland, Australia, by gender and age. Choice data were analyzed using a generalized multinomial logit model. Results. The findings from both the BWS and DCE were generally consistent in that respondents exhibited stronger preferences for technologies offering prevention or early diagnosis over other benefit types. Respondents also prioritized technologies that benefit younger people, larger numbers of people, those in rural areas, or indigenous Australians; that provide value for money; that have no available alternative; or that upgrade an existing technology. However, the relative preference weights and consequent preference orderings differed between the DCE and BWS models. Further, poor correlation between the DCE and BWS weights was observed. While only a minority of respondents reported difficulty completing either task (22.2% DCE, 31.9% BWS), the majority (72.6%) preferred the DCE over BWS task. Conclusions. This study provides reassurance that many criteria routinely used for technology decision making are considered to be relevant by the public. The findings clearly indicate the perceived importance of prevention and early diagnosis. The dissimilarity observed between DCE and profile case BWS weights is contrary to the findings of previous comparisons and raises uncertainty regarding the comparative merits of these stated preference methods in a priority-setting context.
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