title: Secondary diagnoses as predictive factors for survival or mortality in Medicare patients with acute pneumonia.
abstract: 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.
authors.affiliation: Pritzker School of Medicine, University of Chicago, IL, USA.
authors.forename: S R
authors.initials: SR
authors.lastname: White
authors.forename: R
authors.initials: R
authors.lastname: Hand
authors.forename: L
authors.initials: L
authors.lastname: Klemka-Walden
authors.forename: D
authors.initials: D
authors.lastname: Inczauskis
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D015897:Comorbidity; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D008297:Male; D006278:Medicare; D011014:Pneumonia / Q000175:diagnosis / Q000401:mortality*; D012372:ROC Curve; D012720:Severity of Illness Index; D016019:Survival Analysis; D014481:United States / Q000453:epidemiology