Journal of Clinical Epidemiology
Volume 54, Issue 7 , Pages 694-701, July 2001

Risk adjustment for older hospitalized persons:

A comparison of two methods of data collection for the Charlson index

  • Carol van Doorn

      Affiliations

    • Yale University School of Medicine, Department of Internal Medicine, 20 York Street, TMP 15, New Haven, CT 06504, USA
  • ,
  • Sidney T Bogardus

      Affiliations

    • Yale University School of Medicine, Department of Internal Medicine, 20 York Street, TMP 15, New Haven, CT 06504, USA
  • ,
  • Christianna S Williams

      Affiliations

    • Department of Epidemiology and Public Health, 20 York Street, TMP 15, New Haven, CT 06504, USA
  • ,
  • John Concato

      Affiliations

    • Yale University School of Medicine, Department of Internal Medicine, 20 York Street, TMP 15, New Haven, CT 06504, USA
    • West Haven Veterans Affairs Medical Center (VAMC), Clinical Epidemiology Unit, 950 Campbell Avenue, West Haven, CT 06516, USA
  • ,
  • Virginia R Towle

      Affiliations

    • Yale University School of Medicine, Department of Internal Medicine, 20 York Street, TMP 15, New Haven, CT 06504, USA
  • ,
  • Sharon K Inouye

      Affiliations

    • Yale University School of Medicine, Department of Internal Medicine, 20 York Street, TMP 15, New Haven, CT 06504, USA
    • Corresponding Author InformationCorresponding author. Tel.: 203-688-7302; fax: 203-688-4209.(S.K. Inouye)

Received 15 October 1999; received in revised form 8 November 2000; accepted 10 November 2000.

Abstract 

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.

Keywords:  Comorbidity index, Charlson, ICD-9, Mortality, Risk adjustment, Aged

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PII: S0895-4356(00)00367-X

Journal of Clinical Epidemiology
Volume 54, Issue 7 , Pages 694-701, July 2001