COMORBIDITY MEASURES FOR USE WITH ADMINISTRATIVE DATA

OBJECTIVES. This study attempts to develop a comprehensive set of como rbidity measures for use with large administrative inpatient datasets. METHODS. The study involved clinical and empirical review of comorbid ity measures, development of a framework that attempts to segregate co morbidities from other aspects of the patient's condition, development of a comorbidity algorithm, and testing on heterogeneous and homogene ous patient groups. Data were drawn from all adult, nonmaternal inpati ents from 438 acute care hospitals in California in 1992 (n = 1,779,16 7). Outcome measures were those commonly available in administrative d ata: length of stay, hospital charges, and in-hospital death. RESULTS. A comprehensive set of 30 comorbidity measures was developed. The com orbidities were associated with substantial increases in length of sta y, hospital charges, and mortality both for heterogeneous and homogene ous disease groups. Several comorbidities are described that are impor tant predictors of outcomes, yet commonly are not measured. These incl ude mental disorders, drug and alcohol abuse, obesity, coagulopathy, w eight loss, and fluid and electrolyte disorders. CONCLUSIONS. The como rbidities had independent effects on outcomes and probably should not be simplified as an index because they affect outcomes differently amo ng different patient groups. The present method addresses some of the limitations of previous measures. It is based on a comprehensive appro ach to identifying comorbidities and separates them from the primary r eason for hospitalization, resulting in an expanded set of comorbiditi es that easily is applied without further refinement to administrative data for a wide range of diseases.