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A structural equation model of adverse events and length of stay in hospitals

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  • Katharina Hauck

    ()

  • Xueyan Zhao

    ()

Abstract

Adverse events in hospitals cause significant morbidity and mortality, and considerable effort has been invested into analysing their incidence and preventability. An unresolved issue in models of medical adverse events is potential endogeneity of length of stay (LOS): whilst the probability of suffering a medical adverse event during the episode is likely to increase as a patient stays longer, there are a range of unobservable patient and hospital factors affecting both the occurrence of adverse events and LOS, such as unobserved patient complexity and hospital management. Therefore, statistical models of adverse events which do not account for the potential endogeneity of LOS may generate biased estimates. Our objective is to examine the effects of risk factors on the incidence of adverse events using structural equation models and accounting for endogeneity of LOS. We estimate separate models for three of the most common and serious types of medical adverse events: adverse drug reactions, hospital acquired infections, and pressure ulcers. We use episode level administrative hospital data from public hospitals in the state of Victoria, Australia, for the years 2004/05 and 2005/06 with detailed information on patients, in particular medical complexity and adverse events suffered during admission. We use days and months of discharge as instruments for LOS. Our research helps assessing the costs and benefits of additional days spent in hospital. For example, it can contribute to identifying the ideal time of discharge of patients, or inform whether 'hospital at home' programs reduce rates of hospital acquired infections.

Suggested Citation

  • Katharina Hauck & Xueyan Zhao, 2010. "A structural equation model of adverse events and length of stay in hospitals," Monash Econometrics and Business Statistics Working Papers 4/10, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:2010-4
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2010/wp4-10.pdf
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    References listed on IDEAS

    as
    1. Schwierz, Christoph & Augurzky, Boris & Wasem, Jürgen, 2009. "Does the Quality of Hospital Treatment Vary by Days of the Week?," Ruhr Economic Papers 105, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    2. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    3. Rivers, Douglas & Vuong, Quang H., 1988. "Limited information estimators and exogeneity tests for simultaneous probit models," Journal of Econometrics, Elsevier, vol. 39(3), pages 347-366, November.
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    Cited by:

    1. Katharina Hauck & Xueyan Zhao & Terri Jackson, 2010. "Adverse events in surgical inpatients: A comparative analysis of public hospitals in Victoria," Monash Econometrics and Business Statistics Working Papers 5/10, Monash University, Department of Econometrics and Business Statistics.

    More about this item

    Keywords

    Medical errors; complications of care; adverse drug reactions; infections; ulcers; hospital quality;

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • H4 - Public Economics - - Publicly Provided Goods
    • L3 - Industrial Organization - - Nonprofit Organizations and Public Enterprise

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