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Direct versus indirect standaardization in risk adjustment

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  • Erik Schokkaert
  • Carine Van De Voorde

Abstract

Direct and indirect standardization procedures aim at comparing differences in health or differences in health care expenditures between subgroups of the population after controlling for observable morbidity differences. There is a close analogy between this problem and the issue of risk adjustment in health insurance. We analyse this analogy within the theoretical framework proposed in the recent social choice literature on responsibility and compensation. Traditional methods of risk adjustment are analogous to indirect standardization. They are equivalent to the so-called conditional egalitarian mechanism in social choice. In general, they do not remove incentives for risk selection, even if the effect of non-morbidity variables is correctly taken into account. A method of risk adjustment based on direct standardization (as proposed for Ireland) does remove the incentives for risk selection, but at the cost of violating a neutrality condition, stating that insurers should receive the same premium subsidy for all members of the same risk group. Direct standardization is equivalent to the egalitarianequivalent (or proportional) mechanism in social choice. The conflict between removing incentives for risk selection and neutrality is unavoidable if the health expenditure function is not additively separable in the morbidity and efficiency variables.

Suggested Citation

  • Erik Schokkaert & Carine Van De Voorde, 2007. "Direct versus indirect standaardization in risk adjustment," Working Papers of Department of Economics, Leuven ces0733, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
  • Handle: RePEc:ete:ceswps:ces0733
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    References listed on IDEAS

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    1. van de Ven, Wynand P.M.M. & Beck, Konstantin & Van de Voorde, Carine & Wasem, Jurgen & Zmora, Irit, 2007. "Risk adjustment and risk selection in Europe: 6 years later," Health Policy, Elsevier, vol. 83(2-3), pages 162-179, October.
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    2. Vincenzo Atella & Federico Belotti & Ludovico Carrino & Andrea Piano Mortari, 2017. "The future of Long Term Care in Europe. An investigation using a dynamic microsimulation model," CEIS Research Paper 405, Tor Vergata University, CEIS, revised 08 May 2017.
    3. Kristensen, Troels & Rose Olsen, Kim & Sortsø, Camilla & Ejersted, Charlotte & Thomsen, Janus Laust & Halling, Anders, 2013. "Resources allocation and health care needs in diabetes care in Danish GP clinics," Health Policy, Elsevier, vol. 113(1), pages 206-215.
    4. FLEURBAEY, Marc & SCHOKKAERT, Erik, 2011. "Equity in health and health care," LIDAM Discussion Papers CORE 2011026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. S. Veen & R. Kleef & W. Ven & R. Vliet, 2015. "Improving the prediction model used in risk equalization: cost and diagnostic information from multiple prior years," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(2), pages 201-218, March.
    6. Armstrong, John & Paolucci, Francesco & McLeod, Heather & van de Ven, Wynand P.M.M., 2010. "Risk equalisation in voluntary health insurance markets: A three country comparison," Health Policy, Elsevier, vol. 98(1), pages 39-49, November.
    7. Laura Anselmi & Yiu-Shing Lau & Matt Sutton & Anna Everton & Rob Shaw & Stephen Lorrimer, 2022. "Use of past care markers in risk-adjustment: accounting for systematic differences across providers," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(1), pages 133-151, February.

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