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A two‐stage estimation of hospital quality using mortality outcome measures: an application using hospital administrative data

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  • Chew Lian Chua
  • Alfons Palangkaraya
  • Jongsay Yong

Abstract

This paper proposes a method of deriving a quality indicator for hospitals using mortality outcome measures. The method aggregates any number of mortality outcomes into a single indicator via a two‐stage procedure. In the first stage, mortality outcomes are risk‐adjusted using a system of seemingly unrelated regression equations. These risk‐adjusted mortality rates are then aggregated into a single quality indicator in the second stage via weighted least squares. This method addresses the dimensionality problem in measuring hospital quality, which is multifaceted in nature. In addition, our method also facilitates further analyses of determinants of hospital quality by allowing the resulting quality estimates be associated with hospital characteristics. The method is applied to a sample of heart‐disease episodes extracted from hospital administrative data from the state of Victoria, Australia. Using the quality estimates, we show that teaching hospitals and large regional hospitals provide higher quality of care than other hospitals and this superior performance is related to hospital case‐load volume. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Chew Lian Chua & Alfons Palangkaraya & Jongsay Yong, 2010. "A two‐stage estimation of hospital quality using mortality outcome measures: an application using hospital administrative data," Health Economics, John Wiley & Sons, Ltd., vol. 19(12), pages 1404-1424, December.
    • Handle: RePEc:wly:hlthec:v:19:y:2010:i:12:p:1404-1424
    DOI: 10.1002/hec.1560
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    Cited by:

    1. Domenico Lisi & Luigi Siciliani & Odd Rune Straume, 2020. "Hospital competition under pay‐for‐performance: Quality, mortality, and readmissions," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 29(2), pages 289-314, April.
    2. Zhichao Wang & Valentin Zelenyuk, 2021. "Performance Analysis of Hospitals in Australia and its Peers: A Systematic Review," CEPA Working Papers Series WP012021, School of Economics, University of Queensland, Australia.
    3. Valentin Zelenyuk & Zhichao Wang, 2023. "Random vs. Explained Inefficiency in Stochastic Frontier Analysis: The Case of Queensland Hospitals," CEPA Working Papers Series WP052023, School of Economics, University of Queensland, Australia.
    4. Angela Meggiolaro & Carl Rudolf Blankart & Tom Stargardt & Jonas Schreyögg, 2023. "An econometric approach to aggregating multiple cardiovascular outcomes in German hospitals," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(5), pages 785-802, July.
    5. Nils Gutacker & Andrew Street, 2015. "Multidimensional performance assessment using dominance criteria," Working Papers 115cherp, Centre for Health Economics, University of York.
    6. Nils Gutacker & Andrew Street, 2018. "Multidimensional performance assessment of public sector organisations using dominance criteria," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 13-27, February.
    7. 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.
    8. 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.
    9. Jonathan Karnon & Orla Caffrey & Clarabelle Pham & Richard Grieve & David Ben‐Tovim & Paul Hakendorf & Maria Crotty, 2013. "Applying Risk Adjusted Cost‐Effectiveness (Rac‐E) Analysis To Hospitals: Estimating The Costs And Consequences Of Variation In Clinical Practice," Health Economics, John Wiley & Sons, Ltd., vol. 22(6), pages 631-642, June.

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