OBJECTIVES: The aim of this study was to get insight in what criteria as presented in Health technology assessment (HTA) studies are important for decision makers in healthcare priority setting. METHODS: We performed a discrete choice experiment among Dutch healthcare professionals (policy makers, HTA experts, advanced HTA students). In twenty-seven choice sets, we asked respondents to elect reimbursement of one of two different healthcare interventions, which represented unlabeled, curative treatments. Both treatments were incrementally compared with usual care. The results of the interventions were normal outputs of HTA studies with a societal perspective. Results were analyzed using a multinomial logistic regression model. Upon completion of the questionnaire, we discussed the exercise with policy makers. RESULTS: Severity of disease, costs per quality-adjusted life-year gained, individual health gain, and the budget impact were the most decisive decision criteria. A program targeting more severe diseases increased the probability of reimbursement dramatically. Uncertainty related to cost-effectiveness was also important. Respondents preferred health gains that include quality of life improvements over extension of life without improved quality of life. Savings in productivity costs were not crucial in decision making, although these are to be included in Dutch reimbursement dossiers for new drugs. Regarding subgroups, we found that policy makers attached relatively more weight to disease severity than others but less to uncertainty. CONCLUSIONS: Dutch policy makers and other healthcare professionals seem to have reasonably well articulated preferences: six of seven attributes were significant. Disease severity, budget impact, and cost-effectiveness were very important. The results are comparable to international studies, but reveal a larger set of important decision criteria.
OBJECTIVES: The aim of this study was to get insight in what criteria as presented in Health technology assessment (HTA) studies are important for decision makers in healthcare priority setting. METHODS: We performed a discrete choice experiment among Dutch healthcare professionals (policy makers, HTA experts, advanced HTA students). In twenty-seven choice sets, we asked respondents to elect reimbursement of one of two different healthcare interventions, which represented unlabeled, curative treatments. Both treatments were incrementally compared with usual care. The results of the interventions were normal outputs of HTA studies with a societal perspective. Results were analyzed using a multinomial logistic regression model. Upon completion of the questionnaire, we discussed the exercise with policy makers. RESULTS: Severity of disease, costs per quality-adjusted life-year gained, individual health gain, and the budget impact were the most decisive decision criteria. A program targeting more severe diseases increased the probability of reimbursement dramatically. Uncertainty related to cost-effectiveness was also important. Respondents preferred health gains that include quality of life improvements over extension of life without improved quality of life. Savings in productivity costs were not crucial in decision making, although these are to be included in Dutch reimbursement dossiers for new drugs. Regarding subgroups, we found that policy makers attached relatively more weight to disease severity than others but less to uncertainty. CONCLUSIONS: Dutch policy makers and other healthcare professionals seem to have reasonably well articulated preferences: six of seven attributes were significant. Disease severity, budget impact, and cost-effectiveness were very important. The results are comparable to international studies, but reveal a larger set of important decision criteria.