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Estimating Downstream Budget Impacts in Implementation Research

Author

Listed:
  • Todd H. Wagner

    (Health Economics Resource Center, US Department of Veterans Affairs (VA) Palo Alto Health Care System, Menlo Park, CA, USA
    Department of Surgery, Stanford University, Stanford, CA)

  • Alex R. Dopp

    (RAND Corporation, Santa Monica, CA, USA)

  • Heather T. Gold

    (Departments of Population Health and Orthopedic Surgery, New York University (NYU) Langone Health, NY, USA)

Abstract

Health care decision makers often request information showing how a new treatment or intervention will affect their budget (i.e., a budget impact analysis; BIA). In this article, we present key topics for considering how to measure downstream health care costs, a key component of the BIA, when implementing an evidence-based program designed to reduce a quality gap. Tracking health care utilization can be done with administrative or self-reported data, but estimating costs for these utilization data raises 2 issues that are often overlooked in implementation science. The first issue has to do with applicability: are the cost estimates applicable to the health care system that is implementing the quality improvement program? We often use national cost estimates or average payments, without considering whether these cost estimates are appropriate. Second, we need to determine the decision maker’s time horizon to identify the costs that vary in that time horizon. If the BIA takes a short-term time horizon, then we should focus on costs that vary in the short run and exclude costs that are fixed over this time. BIA is an increasingly popular tool for health care decision makers interested in understanding the financial effect of implementing an evidence-based program. Without careful consideration of some key conceptual issues, we run the risk of misleading decision makers when presenting results from implementation studies.

Suggested Citation

  • Todd H. Wagner & Alex R. Dopp & Heather T. Gold, 2020. "Estimating Downstream Budget Impacts in Implementation Research," Medical Decision Making, , vol. 40(8), pages 968-977, November.
  • Handle: RePEc:sae:medema:v:40:y:2020:i:8:p:968-977
    DOI: 10.1177/0272989X20954387
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    References listed on IDEAS

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    1. Jeffrey S. Hoch & Andrew H. Briggs & Andrew R. Willan, 2002. "Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 415-430, July.
    2. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.
    3. Todd H. Wagner & Jean Yoon & Josephine C. Jacobs & Angela So & Amy M. Kilbourne & Wei Yu & David E. Goodrich, 2020. "Estimating Costs of an Implementation Intervention," Medical Decision Making, , vol. 40(8), pages 959-967, November.
    4. Clinton P. McCully & Brian C. Moyer & Kenneth J. Stewart, 2007. "A Reconciliation between the Consumer Price Index and the Personal Consumption Expenditures Price Index," BEA Papers 0079, Bureau of Economic Analysis.
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