ArticleJournal of market access & health policy2014
EU pharmaceutical expenditure forecast.
Article in Journal of market access & health policy, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Projections of Public Spending on Pharmaceuticals: A Review of Methods.PharmacoEconomics · 2025Pooled it
- Horizon scanning and drug expenditure for rare diseases: three-year predictive model in Italy 2025-2027.Health economics review · 2025Article
- Estimating Potential for Drug Budget Reallocation Following Expiration of Exclusivity of Pharmaceutical Products.Journal of health economics and outcomes research · 2022Article
- Forecasting drug utilization and expenditure: ten years of experience in Stockholm.BMC health services research · 2020Article
- Biosimilars: Considerations for Payers.P & T : a peer-reviewed journal for formulary management · 2019Article
- The Rituximab Biosimilar CT-P10 in Rheumatology and Cancer: A Budget Impact Analysis in 28 European Countries.Advances in therapy · 2017Article
- Key drivers for market penetration of biosimilars in Europe.Journal of market access & health policy · 2017Article
- Novel methodology for pharmaceutical expenditure forecast.Journal of market access & health policy · 2014Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesWith constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States' pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm).
methodIn order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012-2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out.
resultsAccording to the model, all countries experienced drug budget reductions except Poland (+€41 million). Savings were expected to be the highest in the United Kingdom (-€9,367 million), France (-€5,589 million), and, far behind them, Germany (-€831 million), Greece (-€808 million), Portugal (-€243 million), and Hungary (-€84 million). The main source of savings came from the cardiovascular, central nervous system, and respiratory areas and from biosimilar entries. Oncology, immunology, and inflammation, in contrast, lead to additional expenditure. The model was particularly sensitive to the time to market of branded products, generic prices, generic penetration, and the distribution of biosimilars.
conclusionsThe results of this forecast suggested a decrease in pharmaceutical expenditure in the studied period. The model was sensitive to pharmaceutical policy decisions.
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