Literature DB >> 27776744

Late-stage pharmaceutical R&D and pricing policies under two-stage regulation.

Sebastian Jobjörnsson1, Martin Forster2, Paolo Pertile3, Carl-Fredrik Burman4.   

Abstract

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. Copyright Â
© 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cost-effectiveness threshold; Optimal sample size; Pharmaceutical pricing and reimbursement; Rare diseases; Static and dynamic efficiency

Mesh:

Year:  2016        PMID: 27776744     DOI: 10.1016/j.jhealeco.2016.06.002

Source DB:  PubMed          Journal:  J Health Econ        ISSN: 0167-6296            Impact factor:   3.883


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