Presentation (CTI)

OBJECTIVES: Several psychiatric drugs with new therapeutic targets have launched in the last five years in the US, providing patients with additional treatment options, but not in Europe. One likely factor is anticipated challenging pricing and access in public payer-dominated markets for these indications. We considered whether an innovative payment model used for antibiotics could support patient access.
METHODS: Key features of subscription payment models were identified and used to develop a hypothetical scenario applied to psychiatric drugs for patients failed by standard-of-care therapies. Benefits and challenges of this scenario were explored.
RESULTS: In this hypothetical scenario, manufacturers would receive a set annual payment to supply drugs on demand, such to be commercially acceptable. Patient access would be permitted in the case that criteria for failure of standard-of-care therapy are fulfilled. Developers may be incentivized to launch, given guaranteed income, without unviable price or volume restrictions, and to not seek use beyond eligibility criteria. Health systems would benefit from access to newer alternatives to benefit patients, without financial risk of over-use. However, additional challenges are identified, over the model’s application for antibiotics. Definition of treatment failure and its application in clinical practice would be critical to avoid unanticipated volumes but is more complex and subjective than for infections. Evidence challenges specific to psychiatry indications would still impact on initial assessment of clinical benefit to inform contracting, and any subsequent real-world monitoring to inform continuation.
CONCLUSIONS: Although the key driver for model use for antibiotics (avoiding resistance) is not the case for psychiatry, a subscription model may be attractive through incentivizing launch while limiting payer risk, with both sides aligned to restrict use to when needed. However, this would not avoid uncertainty in clinical benefit (subpopulation and magnitude) that would require greater complexity in implementation.