Use of a self-report-generated Charlson Comorbidity Index for predicting mortality

Med Care. 2005 Jun;43(6):607-15. doi: 10.1097/


Background: The Charlson Comorbidity Index, a popular tool for risk adjustment, often is constructed from medical record abstracts or administrative data. Limitations in both sources have fueled interest in using patient self-report as an alternative. However, little data exist on whether self-reported Charlson Indices predict mortality.

Objectives: We sought to determine whether a self-reported Charlson Index predicts mortality, its performance relative to indices derived from administrative data, and whether using study-specific weights instead of Charlson's original weights enhances model fit.

Methods: We surveyed 7761 patients admitted to a university medical service over the course of 4 years and extracted their administrative data. We constructed 6 different Charlson indices by using 2 weighting schemes (original Charlson weights and study-specific weights) and 3 different datasources (ICD-9CM data for index hospitalization, ICD-9CM data with a 1-year look-back period, and patient self-report of comorbidities.) Multivariate models were constructed predicting 1-year mortality, log total costs, and log length of stay.

Results: The 6 measures of the Charlson index all predicted 1-year mortality. Models with age and gender, with or without diagnosis-related group, had approximately the same predictive power regardless of which of the 6 Charlson indices were used. Nevertheless, there were small improvements in model fit using administrative data versus self-report, or study-specific versus original weights. All models obtained areas under the receiver operating curve of 0.70 to 0.77.

Conclusions: Overall, self-reported Charlson indices predict 1-year mortality comparably with indices based on administrative data. Administrative data may offer some small improvements in predictive ability and may be preferred when readily available.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.
  • Validation Study

MeSH terms

  • Adult
  • Chicago / epidemiology
  • Comorbidity*
  • Diagnosis-Related Groups
  • Female
  • Forecasting
  • Hospitalization
  • Hospitals, University / statistics & numerical data
  • Humans
  • International Classification of Diseases
  • Interviews as Topic
  • Male
  • Middle Aged
  • Mortality*
  • Regression Analysis
  • Risk Adjustment / methods*
  • Self Disclosure*
  • Surveys and Questionnaires / standards*