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Abstract
Objectives Orphan drugs are increasingly available, but often do not meet cost-effectiveness criteria for reimbursement. Consequently, policymakers are regularly faced with deciding on exempting orphan drugs from these criteria, knowing that they do apply to non-orphan drugs. Our aim was to examine whether and, if so, why there would be societal support for such a waiver.
Methods We conducted a discrete choice experiment in a representative sample (n=1,172) of the public in the Netherlands. We elicited preferences for reimbursing a new drug for patients with a rare disease, whilst a similar drug would not be reimbursed for patients with a common disease for it being cost-ineffective. The circumstances were identical regarding patients’ age, disease severity, health benefits, and treatment costs, but different regarding disease type and—in relation—patient number, budget impact, and health-insurance premium increase. After completing ten choice tasks, respondents explained why they had a consistent or varying preference for reimbursement. We applied random-intercept logit regression models and the Framework Method for analysing the data.
Results Of the respondents, 22% had a consistent preference for not reimbursing the orphan drug, because ‘this was unfair to patients with a common disease’, and 33% had a consistent preference for reimbursing it, because ‘patients are entitled to access new drugs’. The remaining 45% had varying preferences and was more likely to prefer reimbursement when patients were aged >1 and <70 years, had mild disease severity, and benefited relatively well from treatment.
Conclusions Large part of the public would likely support exempting orphan drugs from standard cost-effectiveness criteria. However, our results indicate considerable preference heterogeneity and the preferences of many depend on patients, disease, and drug characteristics. The results provide insight into the circumstances in which offering a waiver to orphan drugs may receive public support and inform reimbursement decisions in healthcare.
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