Kevin Marsh1, Janine A van Til2, Elizabeth Molsen-David3, Christine Juhnke4, Natalia Hawken5, Elisabeth M Oehrlein6, Y Christy Choi7, Alejandra Duenas8, Wolfgang Greiner9, Kara Haas10, Mickael Hiligsmann11, Kimberley S Hockley12, Ilya Ivlev13, Frank Liu14, Jan Ostermann15, Thomas Poder16, Jiat L Poon17, Axel Muehlbacher18. 1. Evidera, London, England, UK. Electronic address: kevin.marsh@evidera.com. 2. Health Technology and Services Research, University of Twente, Enschede, The Netherlands. 3. Scientific and Health Policy Initiatives, ISPOR, Lawrenceville, NJ, USA. 4. Hochschule Neubrandenburg, Neubrandenburg, Germany. 5. Modus Outcomes, Amsterdam, The Netherlands. 6. National Health Council, Washington, DC, USA. 7. University of Minnesota College of Pharmacy, Minneapolis, Minnesota. 8. ICN Business School, Nancy, France. 9. Department of Health Economics, Bielefeld University, Bielefeld, Germany. 10. Cerenovus, New Brunswick, NJ, USA. 11. Department of Health Services Research, Maastricht University, Maastricht, The Netherlands. 12. Imperial Clinical Trials Unit, Imperial College London, London, England, UK. 13. Center for Health Research, Kaiser Permanente, Portland, OR, USA. 14. Merck & Co, Kenilworth, NJ, USA. 15. Department of Health Services Policy and Management, University of South Carolina, Columbia, SC, USA. 16. CIUSSS de l'Estrie-CHUS, Sherbrooke, QC, Canada. 17. Eli Lilly and Company, Indianapolis, IN, USA. 18. Hochschule Neubrandenburg, Neubrandenburg, Germany; Department of Population Health Sciences, Duke University, Durham, NC, USA.
Abstract
OBJECTIVE: This study examines European decision makers' consideration and use of quantitative preference data. METHODS: The study reviewed quantitative preference data usage in 31 European countries to support marketing authorization, reimbursement, or pricing decisions. Use was defined as: agency guidance on preference data use, sponsor submission of preference data, or decision-maker collection of preference data. The data could be collected from any stakeholder using any method that generated quantitative estimates of preferences. Data were collected through: (1) documentary evidence identified through a literature and regulatory websites review, and via key opinion leader outreach; and (2) a survey of staff working for agencies that support or make healthcare technology decisions. RESULTS: Preference data utilization was identified in 22 countries and at a European level. The most prevalent use (19 countries) was citizen preferences, collected using time-trade off or standard gamble methods to inform health state utility estimation. Preference data was also used to: (1) value other impact on patients, (2) incorporate non-health factors into reimbursement decisions, and (3) estimate opportunity cost. Pilot projects were identified (6 countries and at a European level), with a focus on multi-criteria decision analysis methods and choice-based methods to elicit patient preferences. CONCLUSION: While quantitative preference data support reimbursement and pricing decisions in most European countries, there was no utilization evidence in European-level marketing authorization decisions. While there are commonalities, a diversity of usage was identified between jurisdictions. Pilots suggest the potential for greater use of preference data, and for alignment between decision makers.
OBJECTIVE: This study examines European decision makers' consideration and use of quantitative preference data. METHODS: The study reviewed quantitative preference data usage in 31 European countries to support marketing authorization, reimbursement, or pricing decisions. Use was defined as: agency guidance on preference data use, sponsor submission of preference data, or decision-maker collection of preference data. The data could be collected from any stakeholder using any method that generated quantitative estimates of preferences. Data were collected through: (1) documentary evidence identified through a literature and regulatory websites review, and via key opinion leader outreach; and (2) a survey of staff working for agencies that support or make healthcare technology decisions. RESULTS: Preference data utilization was identified in 22 countries and at a European level. The most prevalent use (19 countries) was citizen preferences, collected using time-trade off or standard gamble methods to inform health state utility estimation. Preference data was also used to: (1) value other impact on patients, (2) incorporate non-health factors into reimbursement decisions, and (3) estimate opportunity cost. Pilot projects were identified (6 countries and at a European level), with a focus on multi-criteria decision analysis methods and choice-based methods to elicit patient preferences. CONCLUSION: While quantitative preference data support reimbursement and pricing decisions in most European countries, there was no utilization evidence in European-level marketing authorization decisions. While there are commonalities, a diversity of usage was identified between jurisdictions. Pilots suggest the potential for greater use of preference data, and for alignment between decision makers.
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