Department of Nursing, Physiotherapy and Occupational Therapy, University of Castilla La-Mancha (UCLM), Talavera de la Reina (Toledo), Spain.
Research Institute for Evaluation and Public Policies (IRAPP), Universitat Internacional de Catalunya (UIC), Barcelona, Spain.
PLoS One. 2019 Jul 18;14(7):e0219905. doi: 10.1371/journal.pone.0219905. eCollection 2019.
Discrete choice experiments (DCEs) are a way to assess priority-setting in health care provision. This approach allows for the evaluation of individuals' preferences as a means of adding criteria to traditional quality-adjusted life year analysis. The aim of this systematic literature review was to identify attributes for designing a DCE in order to then develop and validate a framework that supports decision-making on health technologies. Our systematic literature review replicated the methods and search terms used by de Bekker-Grob et al. 2012 and Clark et al. 2014. The Medline database was searched for articles dated between 2008 and 2015. The search was limited to studies in English that reflected general preferences and were choice-based, published as full-text articles and related to health technologies. This study included 72 papers, 52% of which focused on DCEs on drug treatments. The average number of attributes used in all included DCE studies was 5.74 (SD 1.98). The most frequently used attributes in these DCEs were improvements in health (78%), side effects (57%) and cost of treatment (53%). Other, less frequently used attributes included waiting time for treatment or duration of treatment (25%), severity of disease (7%) and value for money (4%). The attributes identified might inform future DCE surveys designed to study societal preferences regarding health technologies in order to better inform decisions in health technology assessment.
离散选择实验（DCEs）是评估医疗保健提供中的优先顺序的一种方法。这种方法允许评估个人的偏好，作为对传统质量调整生命年分析添加标准的一种手段。本系统文献综述的目的是确定设计 DCE 的属性，以便随后开发和验证一个支持健康技术决策的框架。我们的系统文献综述复制了 de Bekker-Grob 等人在 2012 年和 Clark 等人在 2014 年使用的方法和搜索词。在 2008 年至 2015 年期间，对 Medline 数据库进行了搜索，以获取文章。搜索仅限于反映一般偏好且基于选择的、以全文发表并与健康技术相关的英语研究。本研究包括 72 篇论文，其中 52%的论文集中在药物治疗的 DCE 上。所有纳入的 DCE 研究中使用的平均属性数为 5.74（SD 1.98）。在这些 DCE 中使用最频繁的属性是健康状况的改善（78%）、副作用（57%）和治疗费用（53%）。其他不太常用的属性包括治疗等待时间或治疗持续时间（25%）、疾病严重程度（7%）和物有所值（4%）。确定的属性可能会为未来旨在研究社会对健康技术偏好的 DCE 调查提供信息，以便更好地为健康技术评估中的决策提供信息。
