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Budget impact analysis: principles of good practice. Report of the ISPOR Working Group on Good Practices for Budget Impact Analysis II, 2012

Abstract

Background. Budget impact analyses (BIAs) are an essential part of a comprehensive economic assessment of a health care intervention and are increasingly required by reimbursement authorities as part of a listing or reimbursement submission. Objectives: The objective of this report was to present updated guidance on methods for those undertaking such analyses or for those reviewing the results of such analyses. This update was needed, in part, because of developments in BIA methods as well as a growing interest, particularly in emerging markets, in matters related to affordability and population health impacts of health care interventions. Methods. The Task Force was approved by the International Society for Pharmacoeconomics and Outcomes Research Health Sciences Policy Council and appointed by its Board of Directors. Members were experienced developers or users of BIAs; worked in academia and industry and as advisors to governments; and came from several countries in North America and South America, Oceania, Asia, and Europe. The Task Force solicited comments on the drafts from a core group of external reviewers and, more broadly, from the membership of the International Society for Pharmacoeconomics and Outcomes Research. Results. The Task Force recommends that the design of a BIA for a new health care intervention should take into account relevant features of the health care system, possible access restrictions, the anticipated uptake of the new intervention, and the use and effects of the current and new interventions. The key elements of a BIA include estimating the size of the eligible population, the current mix of treatments and the expected mix after the introduction of the new intervention, the cost of the treatment mixes, and any changes expected in condition-related costs. Where possible, the BIA calculations should be performed by using a simple cost calculator approach because of its ease of use for budget holders. In instances, however, in which the changes in eligible population size, disease severity mix, or treatment patterns cannot be credibly captured by using the cost calculator approach, a cohort or patient-level condition-specific model may be used to estimate the budget impact of the new intervention, accounting appropriately for those entering and leaving the eligible population over time. In either case, the BIA should use data that reflect values specific to a particular decision maker’s population. Sensitivity analysis should be of alternative scenarios chosen from the perspective of the decision maker. The validation of the model should include at least face validity with decision makers and verification of the calculations. Data sources for the BIA should include published clinical trial estimates and comparator studies for the efficacy and safety of the current and new interventions as well as the decision maker’s own population for the other parameter estimates, where possible. Other data sources include the use of published data, well-recognized local or national statistical information, and, in special circumstances, expert opinion. Reporting of the BIA should provide detailed information about the input parameter values and calculations at a level of detail that would allow another modeler to replicate the analysis. The outcomes of the BIA should be presented in the format of interest to health care decision makers. In a computer program, options should be provided for different categories of costs to be included or excluded from the analysis. Conclusions. We recommend a framework for the BIA, provide guidance on the acquisition and use of data, and offer a common reporting format that will promote standardization and transparency. Adherence to these good research practice principles would not necessarily supersede jurisdiction-specific BIA guidelines but may support and enhance local recommendations or serve as a starting point for payers wishing to promulgate methodology guidelines.

About the Authors

Sean D. Sullivan
Pharmaceutical Outcomes Research and Policy Program, University of Washington
United States


Josephine A. Mauskopf
RTI Health Solutions, Research Triangle Park
United States


Federico Augustovski
Health Economic Evaluation and Technology Assessment, Institute for Clinical Effectiveness and Health Policy
Argentina


J. Jaime Caro
Evidera
United States


Karen M. Lee
Health Economics, Canadian Agency for Drugs and Technologies in Health
Canada


Mark Minchin
PASLU, National Institute for Health and Care Excellence
United Kingdom


Ewa Orlewska
Centre for Pharmacoeconomics, Warsaw; The Jan Kochanowski University
Poland


Pete Penna
Formulary Resources, LLC
United States


Jose-Manuel Rodriguez Barrios
Stryker
Spain


Wen-Yi Shau
Center for Drug Evaluation
Taiwan, Province of China


T. L. Galankin
First Pavlov State Medical University of Saint Petersburg, Saint Petersburg, Russia
Russian Federation

к.м.н.. ассистент, 

Санкт-Петербург



A. A. Mosikyan
Federal Almazov North West Medical Research Centre
Russian Federation

студентка 4 курса, лечебный факультет, 

Санкт-Петербург



A. S. Kolbin
First Pavlov State Medical University of Saint Petersburg, Saint Petersburg, Russia; Saint Petersburg State University, Saint Petersburg, Russia
Russian Federation

д.м.н., профессор, 

Санкт-Петербург



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Review

For citations:


Sullivan S.D., Mauskopf J.A., Augustovski F., Caro J.J., Lee K.M., Minchin M., Orlewska E., Penna P., Barrios J.R., Shau W., Galankin T.L., Mosikyan A.A., Kolbin A.S. Budget impact analysis: principles of good practice. Report of the ISPOR Working Group on Good Practices for Budget Impact Analysis II, 2012. Kachestvennaya Klinicheskaya Praktika = Good Clinical Practice. 2015;(2):104-118. (In Russ.)

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ISSN 2588-0519 (Print)
ISSN 2618-8473 (Online)