Late-stage pharmaceutical R&D and pricing policies under two-stage regulation
Paolo Pertile () and
Journal of Health Economics, 2016, vol. 50, issue C, 298-311
We present a model combining the two regulatory stages relevant to the approval of a new health technology: the authorisation of its commercialisation and the insurer's decision about whether to reimburse its cost. We show that the degree of uncertainty concerning the true value of the insurer's maximum willingness to pay for a unit increase in effectiveness has a non-monotonic impact on the optimal price of the innovation, the firm's expected profit and the optimal sample size of the clinical trial. A key result is that there exists a range of values of the uncertainty parameter over which a reduction in uncertainty benefits the firm, the insurer and patients. We consider how different policy parameters may be used as incentive mechanisms, and the incentives to invest in R&D for marginal projects such as those targeting rare diseases. The model is calibrated using data on a new treatment for cystic fibrosis.
Keywords: Pharmaceutical pricing and reimbursement; Rare diseases; Optimal sample size; Static and dynamic efficiency; Cost-effectiveness threshold (search for similar items in EconPapers)
JEL-codes: L5 H51 I11 I18 (search for similar items in EconPapers)
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Working Paper: Late-Stage Pharmaceutical R & D and Pricing Policies under Two-Stage Regulation (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jhecon:v:50:y:2016:i:c:p:298-311
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