Evaluation of comorbidity indices for inpatient mortality prediction models

Background and ObjectivesThe objectives of the current study were: to compare the predictive capacity of the original Charlson comorbidity index (CCI), the CCI with new assigned diagnostic codes and estimated weights, and a new developed comorbidity index in a Brazilian population; and to study the effect of the number of comorbidity diseases recorded on the predictive capacity of the comorbidity indices.Materials and MethodsThe study was limited to the Ribeirão Preto region in the State of São Paulo, Brazil, from January 1996 to December 1998. We included only admissions in which the principal diagnoses were respiratory and circulatory diseases.ResultsEvaluation of the CCI indicates that revision of the clinical conditions studied by Charlson, as well as their weights, increased mortality model predictive capacity. The C statistic was 0.72 for the original CCI, and increased to 0.74 for the CCI with new weights and 0.76 for the new index. The C statistic increases in all the comorbidity indices with the utilization of more diagnostic information. This impact is greater when a second secondary diagnosis is added.ConclusionsThe results of the validity analysis for comorbidity indices favor the utilization of empirically developed indices. However, the increase in predictive capacity was weak. In addition, age and principal diagnosis are the most important predictors of inpatient mortality.