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Eliciting societal preferences of reimbursement decision criteria for anti cancer drugs in South Korea

  • Sungkyunkwan University

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: In order to look beyond the cost-effectiveness analysis, this study used a multi-criteria decision analysis (MCDA), which reflects societal values with regard to reimbursement decisions. This study aims to elicit societal preferences of the reimbursement decision criteria for anti cancer drugs from public and healthcare professionals. Methods: Eight criteria were defined based on a literature review and focus group sessions: disease severity, disease population size, pediatrics targets, unmet needs, innovation, clinical benefits, cost-effectiveness, and budget impacts. Using quota sampling and purposive sampling, 300 participants from the Korean public and 30 healthcare professionals were selected for the survey. Preferences were elicited using an analytic hierarchy process. Results: Both groups rated clinical benefits the highest, followed by cost-effectiveness and disease severity, but differed with regard to disease population size and unmet needs. Innovation was the least preferred criteria. Conclusions: Clinical benefits and other social values should be reflected appropriately with cost-effectiveness in healthcare coverage. MCDA can be used to assess decision priorities for complicated health policy decisions, including reimbursement decisions. It is a promising method for making logical and transparent drug reimbursement decisions that consider a broad range of factors, which are perceived as important by relevant stakeholders.

Original languageEnglish
Pages (from-to)411-419
Number of pages9
JournalExpert Review of Pharmacoeconomics and Outcomes Research
Volume17
Issue number4
DOIs
StatePublished - 4 Jul 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Analytic Hierarchy process (AHP)
  • cancer
  • Multi-Criteria Decision Analysis (MCDA)
  • preference
  • reimbursement

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