title: Hospital diagnostic aggregation and risk-adjusted quality.
abstract: OBJECTIVE
  To demonstrate the importance of diagnostic aggregation when assessing hospitals.
  
  
  METHODS
  Patient data from the Victorian Admitted Episodes Database (VAED), 1999/2000 to 2004/2005. Financial statements from public hospitals, 2002/2003 to 2004/2005.
  
  
  METHODS
  Risk-adjusted quality computed for each hospital using two aggregation levels. Each is then used to estimate the relationship between hospital efficiency and quality using two-stage DEA/Tobit model by Wilson and Simar (2006).
  
  
  METHODS
  Selected variables from the VAED were obtained from the Department of Health in Victoria, then linked anonymously with financial statements.
  
  
  RESULTS
  Hospital quality and, in some cases, its relationship with efficiency differs depending on aggregations.
  
  
  CONCLUSIONS
  Patient risk adjustment should be conducted using more than one aggregation level whenever possible.
authors.affiliation: Faculty of Business and Economics, The University of Melbourne, Melbourne, Vic., Australia.
authors.forename: Chun Lok K
authors.initials: CL
authors.lastname: Li
mesh_terms: D017598:Efficiency, Organizational; D006739:Hospital Administration / Q000706:statistics & numerical data*; D006801:Humans; D007345:Insurance Claim Review; D011787:Quality of Health Care / Q000706:statistics & numerical data*; D020379:Risk Adjustment / Q000379:methods / Q000706:statistics & numerical data*; D014739:Victoria
keywords: Risk adjustment; diagnostic aggregation; hospital quality
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