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Why Are Health Care Report Cards So Bad (Good)?

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  • Yijuan Chen

Abstract

This paper provides a signaling-game theoretical foundation for empirically testing the effects of quality report cards in the U.S. health care industry. It shows that, when health care providers face an identical distribution of patient illness severities, a trade-off between multidimensional measures in the existing report cards renders them a mechanism that reveals the providers' qualities without causing them to select patients. However, non-identical patient type distributions between providers, attributed to the referring physician, may force the high-quality provider to shun patients in order to signal himself. Despite this imperfection, the existing report cards cause the minimum provider selection compared with alternative report mechanisms. Since the report cards not only may cause providers to select patients, but also cause patients to select providers, the single difference-in-differences estimates used in previous studies are not su� cient to indicate providers' selection behavior, and cannot capture the report cards' long-run welfare effect with short-run data. In an updated empirical framework, a treatment effect will be estimated once every period.

Suggested Citation

  • Yijuan Chen, 2009. "Why Are Health Care Report Cards So Bad (Good)?," ANU Working Papers in Economics and Econometrics 2009-511, Australian National University, College of Business and Economics, School of Economics.
  • Handle: RePEc:acb:cbeeco:2009-511
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    File URL: https://www.cbe.anu.edu.au/researchpapers/econ/wp511.pdf
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    1. is not listed on IDEAS
    2. Cao, Vi, 2025. "Disseminating healthcare providers’ performance ratings," Economics Letters, Elsevier, vol. 249(C).
    3. Yijuan Chen & Juergen Meinecke, 2012. "Do Healthcare Report Cards Cause Providers To Select Patients And Raise Quality Of Care?," Health Economics, John Wiley & Sons, Ltd., vol. 21(S1), pages 33-55, June.
    4. Katz, Michael L., 2013. "Provider competition and healthcare quality: More bang for the buck?," International Journal of Industrial Organization, Elsevier, vol. 31(5), pages 612-625.
    5. Eunhae Shin, 2023. "Physician Connectedness and Referral Choice," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(6), pages 1238-1261, December.
    6. Yijuan Chen & Juergen Meinecke & Peter Sivey, 2013. "Can hospital waiting times be reduced by being published?," ANU Working Papers in Economics and Econometrics 2013-614, Australian National University, College of Business and Economics, School of Economics.
    7. Chou, Shin-Yi & Deily, Mary E. & Li, Suhui & Lu, Yi, 2014. "Competition and the impact of online hospital report cards," Journal of Health Economics, Elsevier, vol. 34(C), pages 42-58.
    8. Chen, Yijuan & Sivey, Peter, 2021. "Hospital report cards: Quality competition and patient selection," Journal of Health Economics, Elsevier, vol. 78(C).
    9. Ngai, Steven Sek-yum & Cheung, Chau-kiu & Ng, Yuen-hang & Tang, Hon-yin & Ngai, Hui-lam & Wong, Kenix Hok-ching, 2020. "Development and validation of the chronic illness self-management (CISM) scale: Data from a young patient sample in Hong Kong," Children and Youth Services Review, Elsevier, vol. 114(C).
    10. Yaping Wu & Yijuan Chen & Sanxi Li, 2018. "Optimal compensation rule under provider adverse selection and moral hazard," Health Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 509-524, March.
    11. Olivella, Pau & Siciliani, Luigi, 2017. "Reputational concerns with altruistic providers," Journal of Health Economics, Elsevier, vol. 55(C), pages 1-13.
    12. Yijuan Chen & Juergen Meinecke & Peter Sivey, 2016. "A Theory of Waiting Time Reporting and Quality Signaling," Health Economics, John Wiley & Sons, Ltd., vol. 25(11), pages 1355-1371, November.

    More about this item

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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