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Article

Pharmaceutical Expenditure Forecast Model to Support Health Policy Decision Making

by
Cécile Rémuzat
1,*,
Duccio Urbinati
1,
Åsa Kornfeld
1,
Anne-Lise Vataire
1,
Laurent Cetinsoy
1,
Samuel Aballéa
1,
Olfa Mzoughi
1 and
Mondher Toumi
2,†
1
Creativ-Ceutical, 215 Rue du Faubourg Saint-Honoré, 75008 Paris, France
2
University Claude Bernard Lyon I, UFR d’Odontologie, 11 rue Guillaume Paradin, 69372 Lyon, Cedex 08, France
*
Author to whom correspondence should be addressed.
Mondher Toumi, the chief editor, has not had any part in the review and decision process for this paper.
J. Mark. Access Health Policy 2014, 2(1), 23740; https://doi.org/10.3402/jmahp.v2.23740
Submission received: 3 January 2014 / Revised: 11 April 2014 / Accepted: 4 May 2014 / Published: 4 June 2014

Abstract

Background and objective: With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project ‘European Union (EU) Pharmaceutical expenditure forecast’ – http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods: A model was built to assess policy scenarios’ impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Results: Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Conclusions: Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate, and distribution. Reducing, even slightly, the prices of generics had a major impact on savings. However, very aggressive pricing of generic and biosimilar products might make this market unattractive and can be counterproductive. Worth noting, delaying time to access innovative products was also identified as an effective leverage to increase savings but might not be a desirable policy for breakthrough products. Increasing patient financial contributions, either directly or indirectly via their private insurances, is a more likely scenario rather than expanding the national pharmaceutical expenditure coverage.
Keywords: forecast model; pharmaceutical expenditure; health policy; generic; biosimilar; innovative medicine forecast model; pharmaceutical expenditure; health policy; generic; biosimilar; innovative medicine

Share and Cite

MDPI and ACS Style

Rémuzat, C.; Urbinati, D.; Kornfeld, Å.; Vataire, A.-L.; Cetinsoy, L.; Aballéa, S.; Mzoughi, O.; Toumi, M. Pharmaceutical Expenditure Forecast Model to Support Health Policy Decision Making. J. Mark. Access Health Policy 2014, 2, 23740. https://doi.org/10.3402/jmahp.v2.23740

AMA Style

Rémuzat C, Urbinati D, Kornfeld Å, Vataire A-L, Cetinsoy L, Aballéa S, Mzoughi O, Toumi M. Pharmaceutical Expenditure Forecast Model to Support Health Policy Decision Making. Journal of Market Access & Health Policy. 2014; 2(1):23740. https://doi.org/10.3402/jmahp.v2.23740

Chicago/Turabian Style

Rémuzat, Cécile, Duccio Urbinati, Åsa Kornfeld, Anne-Lise Vataire, Laurent Cetinsoy, Samuel Aballéa, Olfa Mzoughi, and Mondher Toumi. 2014. "Pharmaceutical Expenditure Forecast Model to Support Health Policy Decision Making" Journal of Market Access & Health Policy 2, no. 1: 23740. https://doi.org/10.3402/jmahp.v2.23740

APA Style

Rémuzat, C., Urbinati, D., Kornfeld, Å., Vataire, A. -L., Cetinsoy, L., Aballéa, S., Mzoughi, O., & Toumi, M. (2014). Pharmaceutical Expenditure Forecast Model to Support Health Policy Decision Making. Journal of Market Access & Health Policy, 2(1), 23740. https://doi.org/10.3402/jmahp.v2.23740

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