Secondary diagnoses as predictive factors for survival or mortality in Medicare patients with acute pneumonia

We wished to determine if a claims-based method for severity adjustment would predict mortality or survival in pneumonia based on age, gender, and secondary diagnoses. We used a discriminant analysis model of severity of illness developed from Medicare Part A claims data. Our data base was taken from a hospitalized population age 65 years or older coded as DRG 89 (pneumonia with complications/comorbidities). There were 35,677 cases with a mortality = 11.2% in the derivation cohort from 1989 to 1990, and 19,915 cases with a mortality = 9.8% in the validation cohort from 1991. In the derivation cohort, 98% of patients predicted to live, lived, whereas 18% of patients predicted to die, died. Of the three variables, secondary diagnoses had greatest explanatory power. Receiver operating characteristic curves showed that the model performed best at 40% survival. Results were confirmed with the 1991 validation cohort. The model could be applied to hospitals with as few as 172 discharges. This simple, claims-based method can predict survival in pneumonia. It may be useful in selecting medical records for intensified review of medical quality.