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

  • Katharina Hauck

    ()

  • Xueyan Zhao

    ()

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.

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File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2010/wp4-10.pdf
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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 4/10.

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Length: 26 pages
Date of creation: Feb 2010
Date of revision:
Handle: RePEc:msh:ebswps:2010-4
Contact details of provider: Postal: PO Box 11E, Monash University, Victoria 3800, Australia
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Web page: http://www.buseco.monash.edu.au/depts/ebs/
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  1. 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.
  2. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
  3. Christoph Schwierz & Boris Augurzky & Jürgen Wasem, 2009. "Does the Quality of Hospital Treatment Vary by Days of the Week?," Ruhr Economic Papers 0105, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
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