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

Sebastian Jobjörnsson (Institutionen för matematiska vetenskaper, Tillämpad matematik och statistik) ; M. Forster ; P. Pertile ; Carl-Fredrik Burman (Institutionen för matematiska vetenskaper, matematisk statistik)
Journal of Health Economics (0167-6296). Vol. 50 (2016), p. 298-311.
[Artikel, refereegranskad vetenskaplig]

© 2016 Elsevier B.V.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.

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



Denna post skapades 2017-01-05. Senast ändrad 2017-07-03.
CPL Pubid: 246672

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, Tillämpad matematik och statistikInstitutionen för matematiska vetenskaper, Tillämpad matematik och statistik (GU)
Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)

Ämnesområden

Matematisk statistik
Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi

Chalmers infrastruktur