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Judging hospitals by severity-adjusted mortality rates: The influence of the severity-adjustment method

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Listed:
  • Iezzoni, L.I.
  • Ash, A.S.
  • Shwartz, M.
  • Daley, J.
  • Hughes, J.S.
  • Mackieman, Y.D.

Abstract

Objectives. This research examined whether judgments about a hospital's risk-adjusted mortality performance are affected by the severity-adjustment method. Methods. Data came from 100 acute care hospitals nationwide and 11 880 adults admitted in 1991 for acute myocardial infarction. Ten severity measures were used in separate multivariable logistic models predicting in- hospital death. Observed-to-expected death rates and z scores were calculated with each severity measure for each hospital. Results. Unadjusted mortality rates for the 100 hospitals ranged from 4.8% to 26.4%. For 32 hospitals, observed mortality rates differed significantly from expected rates for I or more, but not for all 10, severity measures. Agreement between pairs of severity measures on whether hospitals were flagged as statistical mortality outliers ranged from fair to good. Severity measures based on medical records frequently disagreed with measures based on discharge abstracts. Conclusions. Although the 10 severity measures agreed about relative hospital performance more often than would be expected by chance, assessments of individual hospital mortality rates varied by different severity-adjustment methods.

Suggested Citation

  • Iezzoni, L.I. & Ash, A.S. & Shwartz, M. & Daley, J. & Hughes, J.S. & Mackieman, Y.D., 1996. "Judging hospitals by severity-adjusted mortality rates: The influence of the severity-adjustment method," American Journal of Public Health, American Public Health Association, vol. 86(10), pages 1379-1387.
  • Handle: RePEc:aph:ajpbhl:1996:86:10:1379-1387_5
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    Cited by:

    1. Wang, Justin & Hockenberry, Jason & Chou, Shin-Yi & Yang, Muzhe, 2011. "Do bad report cards have consequences? Impacts of publicly reported provider quality information on the CABG market in Pennsylvania," Journal of Health Economics, Elsevier, vol. 30(2), pages 392-407, March.
    2. Paolo Berta & Gianmaria Martini & Francesco Moscone & Giorgio Vittadini, 2016. "The association between asymmetric information, hospital competition and quality of healthcare: evidence from Italy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 907-926, October.
    3. Courty, Pascal & Kim, Do Han & Marschke, Gerald, 2011. "Curbing cream-skimming: Evidence on enrolment incentives," Labour Economics, Elsevier, vol. 18(5), pages 643-655, October.
    4. Paolo Berta & Chiara Seghieri & Giorgio Vittadini, 2013. "Comparing health outcomes among hospitals: the experience of the Lombardy Region," Health Care Management Science, Springer, vol. 16(3), pages 245-257, September.
    5. Ricardo Castro & Pedro Oliveira & Conceição Silva Portela & Ana Camanho & João Queiroz e Melo, 2015. "Benchmarking clinical practice in surgery: looking beyond traditional mortality rates," Health Care Management Science, Springer, vol. 18(4), pages 431-443, December.

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