Cargando…

Pharmaceutical expenditure forecast model to support health policy decision making

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 Co...

Descripción completa

Detalles Bibliográficos
Autores principales: Rémuzat, Cécile, Urbinati, Duccio, Kornfeld, Åsa, Vataire, Anne-Lise, Cetinsoy, Laurent, Aballéa, Samuel, Mzoughi, Olfa, Toumi, Mondher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Co-Action Publishing 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865740/
https://www.ncbi.nlm.nih.gov/pubmed/27226830
http://dx.doi.org/10.3402/jmahp.v2.23740
_version_ 1782431826757812224
author Rémuzat, Cécile
Urbinati, Duccio
Kornfeld, Åsa
Vataire, Anne-Lise
Cetinsoy, Laurent
Aballéa, Samuel
Mzoughi, Olfa
Toumi, Mondher
author_facet Rémuzat, Cécile
Urbinati, Duccio
Kornfeld, Åsa
Vataire, Anne-Lise
Cetinsoy, Laurent
Aballéa, Samuel
Mzoughi, Olfa
Toumi, Mondher
author_sort Rémuzat, Cécile
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4865740
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Co-Action Publishing
record_format MEDLINE/PubMed
spelling pubmed-48657402016-05-25 Pharmaceutical expenditure forecast model to support health policy decision making Rémuzat, Cécile Urbinati, Duccio Kornfeld, Åsa Vataire, Anne-Lise Cetinsoy, Laurent Aballéa, Samuel Mzoughi, Olfa Toumi, Mondher J Mark Access Health Policy Original Research Article 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. Co-Action Publishing 2014-06-04 /pmc/articles/PMC4865740/ /pubmed/27226830 http://dx.doi.org/10.3402/jmahp.v2.23740 Text en © 2014 Cécile Rémuzat et al. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.
spellingShingle Original Research Article
Rémuzat, Cécile
Urbinati, Duccio
Kornfeld, Åsa
Vataire, Anne-Lise
Cetinsoy, Laurent
Aballéa, Samuel
Mzoughi, Olfa
Toumi, Mondher
Pharmaceutical expenditure forecast model to support health policy decision making
title Pharmaceutical expenditure forecast model to support health policy decision making
title_full Pharmaceutical expenditure forecast model to support health policy decision making
title_fullStr Pharmaceutical expenditure forecast model to support health policy decision making
title_full_unstemmed Pharmaceutical expenditure forecast model to support health policy decision making
title_short Pharmaceutical expenditure forecast model to support health policy decision making
title_sort pharmaceutical expenditure forecast model to support health policy decision making
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865740/
https://www.ncbi.nlm.nih.gov/pubmed/27226830
http://dx.doi.org/10.3402/jmahp.v2.23740
work_keys_str_mv AT remuzatcecile pharmaceuticalexpenditureforecastmodeltosupporthealthpolicydecisionmaking
AT urbinatiduccio pharmaceuticalexpenditureforecastmodeltosupporthealthpolicydecisionmaking
AT kornfeldasa pharmaceuticalexpenditureforecastmodeltosupporthealthpolicydecisionmaking
AT vataireannelise pharmaceuticalexpenditureforecastmodeltosupporthealthpolicydecisionmaking
AT cetinsoylaurent pharmaceuticalexpenditureforecastmodeltosupporthealthpolicydecisionmaking
AT aballeasamuel pharmaceuticalexpenditureforecastmodeltosupporthealthpolicydecisionmaking
AT mzoughiolfa pharmaceuticalexpenditureforecastmodeltosupporthealthpolicydecisionmaking
AT toumimondher pharmaceuticalexpenditureforecastmodeltosupporthealthpolicydecisionmaking