IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v37y2017i8p930-941.html
   My bibliography  Save this article

New Metrics for Economic Evaluation in the Presence of Heterogeneity: Focusing on Evaluating Policy Alternatives Rather than Treatment Alternatives

Author

Listed:
  • David D. Kim
  • Anirban Basu

Abstract

Background. Cost-effectiveness analysis (CEA) methods fail to acknowledge that where cost-effectiveness differs across subgroups, there may be differential adoption of technology. Also, current CEA methods are not amenable to incorporating the impact of policy alternatives that potentially influence the adoption behavior. Unless CEA methods are extended to allow for a comparison of policies rather than simply treatments, their usefulness to decision makers may be limited. Methods. We conceptualize new metrics, which estimate the realized value of technology from policy alternatives, through introducing subgroup-specific adoption parameters into existing metrics, incremental cost-effectiveness ratios (ICERs) and Incremental Net Monetary Benefits (NMBs). We also provide the Loss with respect to Efficient Diffusion (LED) metrics, which link with existing value of information metrics but take a policy evaluation perspective. We illustrate these metrics using policies on treatment with combination therapy with a statin plus a fibrate v. statin monotherapy for patients with diabetes and mixed dyslipidemia. Results. Under the traditional approach, the population-level ICER of combination v. monotherapy was $46,000/QALY. However, after accounting for differential rates of adoption of the combination therapy (7.2% among males and 4.3% among females), the modified ICER was $41,733/QALY, due to the higher rate of adoption in the more cost-effective subgroup (male). The LED metrics showed that an education program to increase the uptake of combination therapy among males would provide the largest economic returns due to the significant underutilization of the combination therapy among males under the current policy. Conclusion. This framework may have the potential to improve the decision-making process by producing metrics that are better aligned with the specific policy decisions under consideration for a specific technology.

Suggested Citation

  • David D. Kim & Anirban Basu, 2017. "New Metrics for Economic Evaluation in the Presence of Heterogeneity: Focusing on Evaluating Policy Alternatives Rather than Treatment Alternatives," Medical Decision Making, , vol. 37(8), pages 930-941, November.
    • Handle: RePEc:sae:medema:v:37:y:2017:i:8:p:930-941
    DOI: 10.1177/0272989X17702379
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X17702379
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X17702379?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Basu, Anirban, 2011. "Economics of individualization in comparative effectiveness research and a basis for a patient-centered health care," Journal of Health Economics, Elsevier, vol. 30(3), pages 549-559, May.
    2. Douglas Coyle & Martin J. Buxton & Bernie J. O'Brien, 2003. "Stratified cost‐effectiveness analysis: a framework for establishing efficient limited use criteria," Health Economics, John Wiley & Sons, Ltd., vol. 12(5), pages 421-427, May.
    3. Anirban Basu & Anupam B. Jena & Dana P. Goldman & Tomas J. Philipson & Robert Dubois, 2014. "Heterogeneity In Action: The Role Of Passive Personalization In Comparative Effectiveness Research," Health Economics, John Wiley & Sons, Ltd., vol. 23(3), pages 359-373, March.
    4. Pauly, Mark V. & Blavin, Fredric E., 2008. "Moral hazard in insurance, value-based cost sharing, and the benefits of blissful ignorance," Journal of Health Economics, Elsevier, vol. 27(6), pages 1407-1417, December.
    5. Susan C. Griffin & Karl P. Claxton & Stephen J. Palmer & Mark J. Sculpher, 2011. "Dangerous omissions: the consequences of ignoring decision uncertainty," Health Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 212-224, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Basu, Anirban & Jena, Anupam B. & Philipson, Tomas J., 2011. "The impact of comparative effectiveness research on health and health care spending," Journal of Health Economics, Elsevier, vol. 30(4), pages 695-706, July.
    2. Basu, Anirban, 2015. "Welfare implications of learning through solicitation versus diversification in health care," Journal of Health Economics, Elsevier, vol. 42(C), pages 165-173.
    3. Mark Pauly, 2015. "Cost‐effectiveness Analysis and Insurance Coverage: Solving a Puzzle," Health Economics, John Wiley & Sons, Ltd., vol. 24(5), pages 506-515, May.
    4. Rebecca Myerson & Darius Lakdawalla & Lisandro D. Colantonio & Monika Safford & David Meltzer, 2018. "Effects of expanding health screening on treatment – What should we expect? What can we learn?," Working Papers 2018-014, Human Capital and Economic Opportunity Working Group.
    5. Rebecca Mary Myerson & Darius Lakdawalla & Lisandro D. Colantonio & Monika Safford & David Meltzer, 2018. "Effects of Expanding Health Screening on Treatment - What Should We Expect? What Can We Learn?," NBER Working Papers 24347, National Bureau of Economic Research, Inc.
    6. Manuel Antonio Espinoza & Andrea Manca & Karl Claxton & Mark Sculpher, 2018. "Social value and individual choice: The value of a choice‐based decision‐making process in a collectively funded health system," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 28-40, February.
    7. Carl Bonander & Mikael Svensson, 2021. "Using causal forests to assess heterogeneity in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1818-1832, August.
    8. Qi Cao & Erik Buskens & Hans L. Hillege & Tiny Jaarsma & Maarten Postma & Douwe Postmus, 2019. "Stratified treatment recommendation or one-size-fits-all? A health economic insight based on graphical exploration," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(3), pages 475-482, April.
    9. Amy Finkelstein & Petra Persson & Maria Polyakova & Jesse M. Shapiro, 2022. "A Taste of Their Own Medicine: Guideline Adherence and Access to Expertise," American Economic Review: Insights, American Economic Association, vol. 4(4), pages 507-526, December.
    10. Laura Levaggi & Rosella Levaggi, 2017. "Rationing in health care provision: a welfare approach," International Journal of Health Economics and Management, Springer, vol. 17(2), pages 235-249, June.
    11. Kisser, Agnes & Tüchler, Heinz & Erdös, Judit & Wild, Claudia, 2016. "Factors influencing coverage decisions on medical devices: A retrospective analysis of 78 medical device appraisals for the Austrian hospital benefit catalogue 2008–2015," Health Policy, Elsevier, vol. 120(8), pages 903-912.
    12. Campillo-Artero, Carlos, 2013. "A full-fledged overhaul is needed for a risk and value-based regulation of medical devices in Europe," Health Policy, Elsevier, vol. 113(1), pages 38-44.
    13. H. Evans & A. Basu, 2011. "Exploring comparative effect heterogeneity with instrumental variables: prehospital intubation and mortality," Health, Econometrics and Data Group (HEDG) Working Papers 11/26, HEDG, c/o Department of Economics, University of York.
    14. Katherine Baicker & Sendhil Mullainathan & Joshua Schwartzstein, 2015. "Behavioral Hazard in Health Insurance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1623-1667.
    15. Rosella Levaggi & Paolo Pertile, 2020. "Which valued‐based price when patients are heterogeneous?," Health Economics, John Wiley & Sons, Ltd., vol. 29(8), pages 923-935, August.
    16. Howard Kunreuther & Mark Pauly, 2022. "Do people have a bias for low deductible insurance?," Journal of Risk and Uncertainty, Springer, vol. 64(1), pages 1-17, February.
    17. Levaggi, Rosella, 2014. "Pricing schemes for new drugs: A welfare analysis," Social Science & Medicine, Elsevier, vol. 102(C), pages 69-73.
    18. Andrey Aistov & Ekaterina Aleksandrova & Christopher J. Gerry, 2021. "Voluntary private health insurance, health-related behaviours and health outcomes: evidence from Russia," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(2), pages 281-309, March.
    19. Gregory S. Zaric, 2008. "Optimal drug pricing, limited use conditions and stratified net benefits for Markov models of disease progression," Health Economics, John Wiley & Sons, Ltd., vol. 17(11), pages 1277-1294, November.
    20. Andrija S Grustam & Nasuh Buyukkaramikli & Ron Koymans & Hubertus J M Vrijhoef & Johan L Severens, 2019. "Value of information analysis in telehealth for chronic heart failure management," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-23, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:37:y:2017:i:8:p:930-941. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.