PP177 Health Preference Research In Europe: A Review Of Its Use. (2019) - Marsh, Kevin; Mühlbacher, Axel; van Til, Janine; Juhnke, Christin; Choi, Yookyung Christy; Duenas, Alejandra; Greiner, Wolfgang; Haas, Kara; Hawken, Natalia; Hiligsmann, Mickael; Hockley, Kimberley; Ivlev, Ilya; et al.
Abstract : Introduction: Health Technology Assessment (HTA) and regulatory decisions involve value judgements. As patient groups, industry, and regulatory agencies conduct more preference studies to quantify these judgements, a better understanding of the methods and practices is needed. Currently, there is no systematic mapping of the use of preference data in Europe. This study aimed to identify (i) the use of quantitative preference data by all relevant HTA bodies and regulatory authorities of the European Union (EU) member states, and (ii) key standards and guidelines. Methods: This study used a mixed method approach based on a systematic literature review, survey and subsequent interviews with decision makers and experts. Results: A total of 62 survey responses were received. Many respondents reported that their agencies were responsible for supporting more than one type of decision, with 69.0 percent supporting approval decisions, 64.3 percent supporting reimbursement decisions, 61.9 percent supporting pricing decisions, and 64.2 percent supporting guideline development. Respondents reported that their agencies supported these decisions in multiple ways: 78.6 percent by assessing health technologies; 54.8 percent by appraising health technologies; 45.2 percent by compiling an HTA report; 7.1 percent by conducting primary research; 9.5 percent by conducting secondary research. More than 40 percent (42.9 percent) of agencies had the final say on one of the decisions of interest – approval, reimbursement, or pricing. Of the 31 countries studied, 71 percent (n = 22) used quantitative preference data in their reimbursement and pricing decisions. Of those, 86 percent (n = 19) used general population preferences to inform the estimation of quality-adjusted life years (QALY) as part of cost utility analysis. Conclusions: Much of this use of preference data can be understood within the standard framework of economic analysis adopted by many HTA agencies; either in in the form of: standard ways to estimate QALYs; ways to broaden the impacts of technologies captured in the QALY; or ways to weigh health gain with other decision-making criteria, such as disease severity or innovativeness.