The Ispor Scientific Presentations Database

ISPOR 20th Annual European Congress
Glasgow, Scotland
November, 2017
PHP190
Multiple Diseases/No Specific Disease
Patient-Reported Outcomes & Patient Preference Studies (PRO)
Patient/Social Preference (PP)
COMPENDIUM OF METHODS FOR MEASURING PATIENT PREFERENCES IN MEDICAL TREATMENT
Soekhai V1, Whichello C2, Levitan B3, Veldwijk J4, Hammad T5, Kihlbom U4, van Overbeeke E6, Russo S7, Mohamed A8, Hermann R9, Huys I6, Patadia V10, Juhaeri J10, de Bekker-Grob E2
1Erasmus University Medical Centre, Rotterdam, The Netherlands, 2Erasmus University Rotterdam, Rotterdam, The Netherlands, 3Janssen R&D, Titusville, NJ, USA, 4Uppsala University, Uppsala, Sweden, 5Merck & Co., North Wales, PA, USA, 6KU Leuven, Leuven, Belgium, 7European Institute of Oncology, Milan, Italy, 8Bayer, Whippany, NJ, USA, 9AstraZeneca, Wilmington, DE, USA, 10Sanofi, Bridgewater, NJ, USA
OBJECTIVES: Patient preference studies are taking on an increasingly important role in the medical product lifecycle. While there are numerous industry, academic, regulatory and patient group efforts addressing standards, quality and proper application of preference studies, there is limited understanding of the range of methods to assess preferences and the trade-offs between them. To develop evidence-based recommendations to guide different stakeholders on how and when patient preference studies should be performed, we developed a comprehensive overview of patient preference exploration and elicitation methods.

METHODS: We used a three-step approach to identify existing preference exploration (qualitative) and elicitation (quantitative) methods: 1) listing methods identified in previous preference method reviews; 2) conducting a systematic literature review on 4,572 unique papers identified through multiple scientific databases, using English full-text papers published between 1980 and 2016; and 3) having discussions with international experts (N=14) in the field of health preferences and/or medical decision making to validate the methods found.

RESULTS: We identified 32 unique preference methods: 10 exploration and 22 elicitation methods. Consensus was reached among the experts interviewed to cluster exploration methods in three main groups: “Individual techniques”, “Group techniques” and methods that were both “Individual and Group techniques”. Elicitation methods were clustered in four groups: “Discrete Choice Based related techniques”, “Indifference Choice Based related techniques”, “Rating related techniques” and “Ranking related techniques”.

CONCLUSIONS: This study identified 32 unique methods for exploring and measuring patient preferences, and reached consensus in clustering the methods. This compendium is a resource for researchers in the patient preference field and also serves as the basis to conduct additional studies that appraise the methods and determine which methods are most appropriate for measuring patient preferences in which phase of the medical product lifecycle to support patient-centric decision making.