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Calculating and Interpreting ICERs and Net Benefit

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  • Mike Paulden

    (University of Alberta)

Abstract

For several decades, the incremental cost-effectiveness ratio has been routinely used by health technology assessment agencies around the world to summarise the results of economic evaluations of health interventions. Yet reporting and considering incremental cost-effectiveness ratios is unnecessary. Alternative summary measures exist, based on the concept of ‘net benefit’. The incremental cost-effectiveness ratio and measures of net benefit share several commonalities but some important distinctions. As a result, different methods are required to calculate and interpret incremental cost-effectiveness ratios compared to measures of net benefit. The aim of this practical application is to introduce readers to these methods, using a hypothetical example to illustrate key issues. First, the methods used to calculate each measure are described. Next, for each measure, consideration is made of whether and how each measure may be interpreted to perform the following tasks, each of which may be of interest to health technology assessment agencies: (1) identifying the single most cost-effective strategy; (2) ranking strategies from ‘most’ to ‘least’ cost-effective (on an ordinal scale); (3) determining the magnitude to which a strategy is more or less cost-effective than another strategy (on a cardinal scale); and (4) determining whether a strategy is more or less cost-effective following a sensitivity or scenario analysis. This practical application also introduces a novel approach for visually interpreting measures of net benefit using the cost-effectiveness plane, which addresses a number of limitations of the conventional cost-effectiveness ‘efficiency frontier’. By the end of this practical application, readers should have an understanding of how to calculate and interpret each measure, as well as the relative strengths and limitations of each.

Suggested Citation

  • Mike Paulden, 2020. "Calculating and Interpreting ICERs and Net Benefit," PharmacoEconomics, Springer, vol. 38(8), pages 785-807, August.
    • Handle: RePEc:spr:pharme:v:38:y:2020:i:8:d:10.1007_s40273-020-00914-6
    DOI: 10.1007/s40273-020-00914-6
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    References listed on IDEAS

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    1. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits: A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis," NBER Technical Working Papers 0227, National Bureau of Economic Research, Inc.
    2. Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
    3. Daniel Polsky & Henry A. Glick & Richard Willke & Kevin Schulman, 1997. "Confidence Intervals for Cost–Effectiveness Ratios: A Comparison of Four Methods," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 243-252, May.
    4. 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.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Chris Sampson’s journal round-up for 3rd August 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-08-03 11:00:00

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    Cited by:

    1. James F. O’Mahony, 2020. "Does Cost-Effectiveness Analysis Really Need to Abandon the Incremental Cost-Effectiveness Ratio to Embrace Net Benefit?," PharmacoEconomics, Springer, vol. 38(8), pages 777-779, August.
    2. Toni Bakhtiar & Ihza Rizkia Fitri & Farida Hanum & Ali Kusnanto, 2022. "Mathematical Model of Pest Control Using Different Release Rates of Sterile Insects and Natural Enemies," Mathematics, MDPI, vol. 10(6), pages 1-18, March.
    3. Mike Paulden, 2020. "Why it’s Time to Abandon the ICER," PharmacoEconomics, Springer, vol. 38(8), pages 781-784, August.
    4. Baines, Darrin & Disegna, Marta & Hartwell, Christopher A., 2021. "Portfolio frontier analysis: Applying mean-variance analysis to health technology assessment for health systems under pressure," Social Science & Medicine, Elsevier, vol. 276(C).
    5. Rick A. Vreman & Joost W. Geenen & Saskia Knies & Aukje K. Mantel-Teeuwisse & Hubert G. M. Leufkens & Wim G. Goettsch, 2021. "The Application and Implications of Novel Deterministic Sensitivity Analysis Methods," PharmacoEconomics, Springer, vol. 39(1), pages 1-17, January.

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