Budget impact analysis of medicines: estimated values versus real-world evidence and the implications

Daniel Resende Faleiros*, Juliana Alvares-Teodoro, Everton Nunes da Silva, Brian B. Godman, Ramon Gonçalves Pereira, Eli Iola Gurgel Andrade, Francisco A. de Assis Acurcio, Augusto A. Guerra Júnior

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Objectives: Budget Impact Analyses (BIA) of medicines helps managers in promoting health systems’ sustainability when assessing the role and value of new medicines. However, it is not clear whether BIAs typically underestimate or overestimate the impact on real-world budgets. This retroactive analysis seeks to compare estimated values obtained by a BIA and Real-World Evidence (RWE) to guide discussions. Methods: The estimated values were obtained through a BIA concerning the incorporation of adalimumab for the treatment of Rheumatoid Arthritis into the Brazilian Unified Health System (SUS) carried out retroactively and per international guidelines. RWE data was extracted from SUS computerized systems. We subsequently compared the number of treatments, costs, and Incremental Budget Impact (IBI). Results:–The total number of treatments was underestimated by 10% (6,243) and the total expenditure was overestimated by 463% (US$ 4.7 billion). In five years, the total difference between the estimated values and real IBI reached US$ 1.1 billion. A current expenditure of US$ 1.0 was observed for every US$ 5.60 of estimated expenditure. Conclusion:–The higher estimates from the BIA might cause decision makers to be more cautious with the introduction of a new medicine to reduce the opportunity costs for other interventions.

Original languageEnglish
Pages (from-to)271-281
Number of pages11
JournalExpert Review of Pharmacoeconomics and Outcomes Research
Volume22
Issue number2
DOIs
Publication statusPublished - 2022

Keywords

  • Brazil
  • Health Technology Assessment
  • budgetary impact analyses
  • budgetary impact model
  • economic evaluation
  • medicines

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