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How profitable is risk selection? A comparison of four risk adjustment models

Author

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  • Yujing Shen
  • Randall P. Ellis

    (Department of Economics, Boston University, USA)

Abstract

To mitigate selection triggered by capitation payments, risk-adjustment models bring capitation payments closer on average to individuals' expected expenditure. We examine the maximum potential profit that plans could hypothetically gain by using their own private information to select low-cost enrollees when payments are made using four commonly used risk adjustment models. Simulations using a privately insured sample suggest that risk selection profits remain substantial. The magnitude of potential profit varies according to the risk adjustment model and the private information plans can employ to identify profitable enrollees. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Yujing Shen & Randall P. Ellis, 2002. "How profitable is risk selection? A comparison of four risk adjustment models," Health Economics, John Wiley & Sons, Ltd., vol. 11(2), pages 165-174.
  • Handle: RePEc:wly:hlthec:v:11:y:2002:i:2:p:165-174
    DOI: 10.1002/hec.661
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    References listed on IDEAS

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    1. Selden, Thomas M, 1998. "Risk Adjustment for Health Insurance: Theory and Implications," Journal of Risk and Uncertainty, Springer, vol. 17(2), pages 167-179, November.
    2. Thomas G. McGuire & Jacob Glazer, 2000. "Optimal Risk Adjustment in Markets with Adverse Selection: An Application to Managed Care," American Economic Review, American Economic Association, vol. 90(4), pages 1055-1071, September.
    3. Mullahy, John, 1998. "Much ado about two: reconsidering retransformation and the two-part model in health econometrics," Journal of Health Economics, Elsevier, vol. 17(3), pages 247-281, June.
    4. Van de ven, Wynand P.M.M. & Ellis, Randall P., 2000. "Risk adjustment in competitive health plan markets," Handbook of Health Economics,in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 14, pages 755-845 Elsevier.
    5. Erik van Barneveld & Leida Lamers & René van Vliet & Wynand van de Ven, 2000. "Ignoring small predictable profits and losses: a new approach for measuring incentives for cream skimming," Health Care Management Science, Springer, vol. 3(2), pages 131-140, February.
    6. Arlene Ash & Randall P. Ellis & Gregory Pope & John Ayanian & David Bates & Helen Burstin & Lisa Iezzoni & Elizabeth McKay & Wei Yu, 2000. "Using Diagnoses to Describe Populations and Predict Costs," Papers 0099, Boston University - Industry Studies Programme.
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    Citations

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    Cited by:

    1. Mario Jametti & Thomas von Ungern-Sternberg, 2006. "Risk Selection in Natural Disaster Insurance – the Case of France," CESifo Working Paper Series 1683, CESifo Group Munich.
    2. Keane, Michael, 2004. "Modeling Health Insurance Choices in “Competitive” Markets," MPRA Paper 55198, University Library of Munich, Germany.
    3. Kathryn Antioch & Michael Walsh, 2004. "The risk-adjusted vision beyond casemix (DRG) funding in Australia," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 5(2), pages 95-109, May.
    4. Normann Lorenz, 2014. "Using quantile regression for optimal risk adjustment," Research Papers in Economics 2014-11, University of Trier, Department of Economics.
    5. Álvaro Riascos & Eduardo Alfonso & Mauricio Romero, 2014. "The Performance of Risk Adjustment Models in Colombian Competitive Health Insurance Market," DOCUMENTOS CEDE 012062, UNIVERSIDAD DE LOS ANDES-CEDE.
    6. Karen Eggleston & Anupa Bir, 2009. "Measuring Selection Incentives in Managed Care: Evidence From the Massachusetts State Employee Insurance Program," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(1), pages 159-175.
    7. Pieter Bakx & Frederik Schut & Eddy Doorslaer, 2015. "Can universal access and competition in long-term care insurance be combined?," International Journal of Health Economics and Management, Springer, vol. 15(2), pages 185-213, June.
    8. Bauhoff, Sebastian, 2012. "Do health plans risk-select? An audit study on Germany's Social Health Insurance," Journal of Public Economics, Elsevier, vol. 96(9-10), pages 750-759.
    9. Normann Lorenz, 2014. "The interaction of direct and indirect risk selection," Research Papers in Economics 2014-12, University of Trier, Department of Economics.
    10. Beck, Konstantin & Trottmann, Maria & Zweifel, Peter, 2010. "Risk adjustment in health insurance and its long-term effectiveness," Journal of Health Economics, Elsevier, vol. 29(4), pages 489-498, July.
    11. Jan Brosse & Mathias Kifmann, 2013. "Competition in Health Insurance and Premium Regulation," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 11(1), pages 21-26, 04.
    12. Karen Eggleston & Randall P. Ellis & Mingshan Lu, 2007. "Prevention and Dynamic Risk Adjustment," Boston University - Department of Economics - Working Papers Series WP2007-023, Boston University - Department of Economics.
    13. Mario Jametti & Thomas von Ungern-Sternberg, 2010. "Risk Selection in Natural-Disaster Insurance," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 166(2), pages 344-364, June.
    14. repec:ces:ifodic:v:11:y:2013:i:1:p:19083487 is not listed on IDEAS
    15. Lorenz, Normann, 2015. "The interaction of direct and indirect risk selection," Journal of Health Economics, Elsevier, vol. 42(C), pages 81-89.
    16. Ellis, Randall P. & McGuire, Thomas G., 2007. "Predictability and predictiveness in health care spending," Journal of Health Economics, Elsevier, vol. 26(1), pages 25-48, January.
    17. Wynand P. M. M. Ven & René C. J. A. Vliet & Richard C. Kleef, 2017. "How can the regulator show evidence of (no) risk selection in health insurance markets? Conceptual framework and empirical evidence," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(2), pages 167-180, March.

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