OBJECTIVES:

Policy makers increasingly have to make complex reimbursement decisions involving making trade-offs between multiple potentially conflicting criteria. This study aims to assess the general public’s preferences for reimbursement criteria for two expensive drugs by means of multi criteria decision analysis (MCDA).

METHODS:

MCDA was conducted for rituximab in rheumatoid arthritis (RA) and non-Hodgkin lymphoma (NHL) and bevacizumab in metastatic breast cancer (MBC) and non-small cell lung cancer (NSCLC). Criteria selection was based on a literature review and included health economic-related criteria (costs per patient per year, quality of life, budget impact, life prolongation and side-effects) and other criteria (availability of alternatives, disease severity, and disease rarity). Preferences were elicited using the swing weighting method. Respondents were recruited through social media and our personal network. Overall scores (0-1 scale) were calculated per alternative by multiplying standardized performance scores with standardized criteria preferences.

RESULTS:

Based on the respondent’s (n=143) criteria preferences, the reimbursement criterion quality of life ranked highest (0.81), followed by life prolongation (0.69), disease severity (0.68), availability of alternatives (0.67), and side-effects (0.59). Costs per patient per year (0.58), budget impact (0.49) and disease rarity (0.45) ranked lowest. Rituximab in RA and NHL attained the highest overall score (0.60 and 0.52 respectively) and bevacizumab in MBC and NSCLC the lowest (0.46 and 0.40 respectively). The overall score of rituximab in RA was mainly attributable to high performance scores for disease severity, side-effects, and costs per patient per year.

CONCLUSIONS:

MCDA can facilitate reimbursement decision making as it quantifies both an overall score of each alternative and the relative importance of multiple criteria. This study shows that disease burden and unmet need were valued more importantly than cost-criteria. This information may support policy makers in making trade-offs between potentially conflicting criteria in reimbursement decision making for expensive drugs