Hospital diagnostic aggregation and risk-adjusted quality
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1Faculty of Business and Economics, The University of Melbourne, Melbourne, Vic., Australia.
Objective:
To demonstrate the importance of diagnostic aggregation when assessing hospitals.
Data Sources:
Patient data from the Victorian Admitted Episodes Database (VAED), 1999/2000 to 2004/2005. Financial statements from public hospitals, 2002/2003 to 2004/2005.
Study Design:
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).
Data Collection:
Selected variables from the VAED were obtained from the Department of Health in Victoria, then linked anonymously with financial statements.
Principal Findings:
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.
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