Risk adjustment for older hospitalized persons: a comparison of two methods of data collection for the Charlson index

J Clin Epidemiol. 2001 Jul;54(7):694-701. doi: 10.1016/s0895-4356(00)00367-x.


To compare Charlson indices based on chart data and ICD-9 data for agreement overall and on rating specific comorbid conditions, and to compare mortality risks associated with these indices. Prospective cohort study. Six general medicine wards at Yale-New Haven Hospital. 524 consecutive patients who had no clinical evidence of delirium at enrollment, admitted between November 6, 1989 and July 31, 1991, aged 70 years or older. Death within 1 year of the index hospital admission date. Scores using the chart-based data were significantly higher than those using ICD-9 data. About half of the individual conditions showed fair-to-good agreement between the two scores, whereas the other half showed poor agreement. A comparison of mortality prediction indicated that the weightings assigned to individual comorbidities differed substantially from those used in Charlson's original index. While mortality prediction of each individual index was comparable, the ICD-9 and chart indices contributed independently to mortality prediction in the presence of the other. Low agreement between Charlson scores based on the two methods of data collection and their cumulative contribution to mortality prediction suggest that these indices may include different information. Our results suggest that the original Charlson index may not provide optimal risk adjustment for elderly general medicine samples. We suggest development of an empirically-derived index of comorbid conditions and weights may be warranted for older general medical patients.

Publication types

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

MeSH terms

  • Aged
  • Comorbidity*
  • Data Collection / methods
  • Female
  • Hospitalization / statistics & numerical data*
  • Humans
  • Male
  • Mortality*
  • Predictive Value of Tests
  • Prospective Studies
  • Risk Adjustment*