Hospital Diagnostic Aggregation and Risk‐Adjusted Quality

Objective

To demonstrate the importance of diagnostic aggregation when assessing hospitals.

Data Sources

Patient data from the Victorian Admitted Episodes Database (), 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 /Tobit model by Wilson and Simar (2006).

Data Collection

Selected variables from the 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.