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Estimating the marginal cost of a life year in Sweden’s public healthcare sector

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  • Jonathan Siverskog

    (Linköping University)

  • Martin Henriksson

    (Linköping University)

Abstract

Although cost-effectiveness analysis has a long tradition of supporting healthcare decision-making in Sweden, there are no clear criteria for when an intervention is considered too expensive. In particular, the opportunity cost of healthcare resource use in terms of health forgone has not been investigated empirically. In this work, we therefore seek to estimate the marginal cost of a life year in Sweden’s public healthcare sector using time series and panel data at the national and regional levels, respectively. We find that estimation using time series is unfeasible due to reversed causality. However, through panel instrumental variable estimation we are able to derive a marginal cost per life year of about SEK 370,000 (EUR 39,000). Although this estimate is in line with emerging evidence from other healthcare systems, it is associated with uncertainty, primarily due to the inherent difficulties of causal inference using aggregate observational data. The implications of these difficulties and related methodological issues are discussed.

Suggested Citation

  • Jonathan Siverskog & Martin Henriksson, 2019. "Estimating the marginal cost of a life year in Sweden’s public healthcare sector," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(5), pages 751-762, July.
    • Handle: RePEc:spr:eujhec:v:20:y:2019:i:5:d:10.1007_s10198-019-01039-0
    DOI: 10.1007/s10198-019-01039-0
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Opportunity costs, marginal productivity, and cost-effectiveness thresholds: what are they and how are they related?
      by Rita Faria, Jessica Ochalek, jameslomas88 in The Academic Health Economists' Blog on 2020-09-23 06:00:00

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    Cited by:

    1. Francesco Longo & Karl Claxton & Stephen Martin & James Lomas, 2023. "More long‐term care for better healthcare and vice versa: investigating the mortality effects of interactions between these public sectors," Fiscal Studies, John Wiley & Sons, vol. 44(2), pages 189-216, June.
    2. Persson, Emil & Tinghög, Gustav, 2020. "Opportunity cost neglect in public policy," Journal of Economic Behavior & Organization, Elsevier, vol. 170(C), pages 301-312.
    3. Francesco Longo & Karl Claxton & James Lomas & Stephen Martin, 2020. "Does public long-term care expenditure improve care-related quality of life in England?," Working Papers 172cherp, Centre for Health Economics, University of York.
    4. Siverskog, Jonathan & Henriksson, Martin, 2022. "The health cost of reducing hospital bed capacity," Social Science & Medicine, Elsevier, vol. 313(C).
    5. Chris Sampson & Bernarda Zamora & Sam Watson & John Cairns & Kalipso Chalkidou & Patricia Cubi-Molla & Nancy Devlin & Borja García-Lorenzo & Dyfrig A. Hughes & Ashley A. Leech & Adrian Towse, 2022. "Supply-Side Cost-Effectiveness Thresholds: Questions for Evidence-Based Policy," Applied Health Economics and Health Policy, Springer, vol. 20(5), pages 651-667, September.
    6. Francesco Longo & Karl Claxton & James Lomas & Stephen Martin, 2021. "Does public long‐term care expenditure improve care‐related quality of life of service users in England?," Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2561-2581, September.

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    More about this item

    Keywords

    Opportunity cost; Threshold; Healthcare expenditure; Mortality; Life expectancy; Cost-effectiveness analysis;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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