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Budget-Impact Analyses: A Critical Review of Published Studies

Authors
Disciplines
  • Medicine
  • Pharmacology

Abstract

This article reviews budget-impact analyses (BIAs) published to date in peer-reviewed bio-medical journals with reference to current best practice, and discusses where future research needs to be directed. Published BIAs were identified by conducting a computerized search on PubMed using the search term 'budget impact analysis'. The years covered by the search included January 2000 through November 2008. Only studies (i) named by authors as BIAs and (ii) predicting financial consequences of adoption and diffusion of a new health intervention(s) within a specific healthcare setting were included. Relevant studies were evaluated according to the checklist that focuses on issues unique to BIA, highlighting areas of agreement or dissent between published studies and methodological guidelines. A total of 34 studies met the inclusion criteria, the majority published in 2007-8. Of these, 41% were from the US, 54% were prepared for pharmaceuticals and 65% had BIA as their main aim. The published BIAs were heterogeneous in respect of methods for deriving budget-impact estimates, time horizon and population. There is fairly good agreement between published studies and methodological guidelines within the scope of perspective, comparator, cost included and data sources. Specific issues that need to be addressed and/or improved are reporting format, sensitivity analysis and discounting. The results indicate that, recently, BIAs have appeared more frequently in peer-reviewed journals, providing stimulus to development, validation and dissemination of methods. Many published studies fail to reach the desired quality, but this situation should change with good research practice principles that will help codify and clarify important issues and promote standardization and transparency. Future research needs to be directed to quality assurance of published BIAs and investment in data collection for parameters specific to BIAs.

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