What attributes should be included in a discrete choice experiment related to health technologies? A systematic literature review

• Published in: PloS one Vol. 14; no. 7; p. e0219905
• Main Authors: Trapero-Bertran, Marta, Rodríguez-Martín, Beatriz, López-Bastida, Julio
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.07.2019; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Biomedical Technology; Choice Behavior; Conjoint analysis; Databases, Factual; Decision Making; Economic models; Health; Humans; Immunization; Literature reviews; Medical research; Medical technology; Medical treatment; Medicine and Health Sciences; Methods; Personal preferences (Social sciences); Research and Analysis Methods; Reviews; Side effects; Social Sciences; Technology; Technology assessment; Technology Assessment, Biomedical; Workflow; Spain
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0219905

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.