Late-stage pharmaceutical R&D and pricing policies under two-stage regulation
Artikel i vetenskaplig tidskrift, 2016

© 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.

Cost-effectiveness threshold

Optimal sample size

Static and dynamic efficiency

Pharmaceutical pricing and reimbursement

Rare diseases

Författare

Sebastian Jobjörnsson

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

M. Forster

University of York

P. Pertile

Universita degli Studi di Verona

Carl-Fredrik Burman

Chalmers, Matematiska vetenskaper, matematisk statistik

Göteborgs universitet

Journal of Health Economics

0167-6296 (ISSN)

Vol. 50 298-311

Ämneskategorier

Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi

Sannolikhetsteori och statistik

Fundament

Grundläggande vetenskaper

DOI

10.1016/j.jhealeco.2016.06.002

Mer information

Senast uppdaterat

2018-03-06