Evaluation of comorbidity indices for inpatient mortality prediction models.
OBJECTIVE
The 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.


METHODS
The 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.


RESULTS
Evaluation 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.


CONCLUSIONS
The 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.
Martins
Mônica
M
Departamento de Administração e Planejamento em Saúde, Escola Nacional de Saúde Pública Sérgio Arouca, Rio de Janeiro/RJ 21042-210, Brazil. martins@ensp.fiocruz.br
Blais
Régis
R
D001938:Brazil; D002318:Cardiovascular Diseases / Q000453:epidemiology; D015897:Comorbidity; D016208:Databases, Factual; D006305:Health Status Indicators; D017052:Hospital Mortality; D006801:Humans; D008171:Lung Diseases / Q000453:epidemiology; D015233:Models, Statistical; D011237:Predictive Value of Tests; D012306:Risk