Adoption of new therapies in the treatment of Hepatitis: a verification of the accuracy of budget impact analysis to guide investment decisions

Daniel Resende Faleiros*, Everton Nunes da Silva, Andreia C. Santos, Brian B. Godman, Ramon Goncalves Pereira, Augusto A. Guerra Junior

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: While there are good Budget Impact Analysis (BIA) guidelines, studies still register potential bias. To do this, we compared the results between theoretical and real-world evidence (RWE) expenditures for medicines for Hepatitis C: boceprevir (BOC) and telaprevir (TVR). While both are not currently recommended in treatment guidelines following recent developments, this is an emblematic case because for 4 years these medicines consumed considerable resources. Methods: Theoretical results and RWE expenditures were compared regarding the incorporation of BOC and TVR in 2013–2014 into the Brazilian Public Health System. Theoretical values were extracted from Commission for Technology Incorporation Report and RWE expenditures were extracted from the administrative data records using deterministic-probabilistic linkage. Results: The estimated number of patients treated (BOC+TVR) was 13,012 versus 7,641 (real). The estimated purchase price for BOC was US$6.20 versus US$11.07 (real) and for TVR was US$42.21 versus US$84.09 (average/real). The estimated budget impact was US$285.16 million versus US$128.58 million (real). Conclusion: This study demonstrates appreciable divergence (US$156.58 million) between the theoretical budget impact and RWE expenditures due to underestimated purchase prices and overestimated populations. The greater the degree of accuracy the more reliable and usable BIAs become for decision-making.

Original languageEnglish
JournalExpert Review of Pharmacoeconomics and Outcomes Research
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Affordability
  • Brazil
  • budgetary impact analyses
  • budgetary impact model
  • economic evaluation
  • health technology assessment
  • Hepatitis C
  • medicines

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