Article

Hospital performance reports based on severity adjusted mortality rates in patients with cirrhosis depend on the method of risk adjustment

Liver Unit, Division of Gastroenterology and Hepatology, Department of Medicine, University of Calgary, Alberta, Canada.
Annals of hepatology: official journal of the Mexican Association of Hepatology (Impact Factor: 2.19). 07/2012; 11(4):526-35.
Source: PubMed

ABSTRACT Hospital outcome report cards are used to judge provider performance, including for liver transplantation. We aimed to determine the impact of the choice of risk adjustment method on hospital rankings based on mortality rates in cirrhotic patients.
We identified 68,426 cirrhotic patients hospitalized in the Nationwide Inpatient Sample database. Four risk adjustment methods (the Charlson/Deyo and Elixhauser algorithms, Disease Staging, and All Patient Refined Diagnosis Related Groups) were used in logistic regression models for mortality. Observed to expected (O/E) death rates were calculated for each method and hospital. Statistical outliers with higher or lower than expected mortality were identified and rankings compared across methods.
Unadjusted mortality rates for the 553 hospitals ranged from 1.4 to 30% (overall, 10.6%). For 163 hospitals (29.5%), observed mortality differed significantly from expected when judged by one or more, but not all four, risk adjustment methods (25.9% higher than expected mortality and 3.6% lower than expected mortality). Only 28% of poor performers and 10% of superior performers were consistently ranked as such by all methods. Agreement between methods as to whether hospitals were flagged as outliers was moderate (kappa 0.51-0.59), except the Charlson/Deyo and Elixhauser algorithms which demonstrated excellent agreement (kappa 0.75).
Hospital performance reports for patients with cirrhosis require sensitivity to the method of risk adjustment. Depending upon the method, up to 30% of hospitals may be flagged as outliers by one, but not all methods. These discrepancies could have important implications for centers erroneously labeled as high mortality outliers.

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