Validation of case-mix measures derived from self-reports of diagnoses and health

J Clin Epidemiol. 2002 Apr;55(4):371-80. doi: 10.1016/s0895-4356(01)00493-0.


Self-reported chronic diseases and health status are associated with resource use. However, few data exist regarding their ability to predict mortality or hospitalizations. We sought to determine whether self-reported chronic medical conditions and the SF-36 could be used individually or in combination to assess co-morbidity in the outpatient setting. The study was designed as a prospective cohort study. Patients were enrolled in the primary care clinics at seven Veterans Affairs (VA) medical centers participating in the Ambulatory Care Quality Improvement Project (ACQUIP). 10,947 patients, > or = 50 years of age, enrolled in general internal medicine clinics who returned both a baseline health inventory checklist and the baseline SF-36 who were followed for a mean of 722.5 (+/-84.3) days. The primary outcome was all-cause mortality, with a secondary outcome of hospitalization within the VA system. Using a Cox proportional hazards model in a development set of 5,469 patients, a co-morbidity index [Seattle Index of Co-morbidity (SIC)] was constructed using information about age, smoking status and seven of 25 self-reported medical conditions that were associated with increased mortality. In the validation set of 5,478 patients, the SIC was predictive of both mortality and hospitalizations within the VA system. A separate model was constructed in which only age and the PCS and MCS scores of the SF-36 were entered to predict mortality. The SF-36 component scores and the SIC had comparable discriminatory ability (AUC for discrimination of death within 2 y 0.71 for both models). When combined, the SIC and SF-36 together had improved discrimination for mortality (AUC = 0.74, p-value for difference in AUC < 0.005). A new outpatient co-morbidity score developed using self-identified chronic medical conditions on a baseline health inventory checklist was predictive of 2-y mortality and hospitalization within the VA system in general internal medicine patients.

Publication types

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

MeSH terms

  • Aged
  • Ambulatory Care
  • Analysis of Variance
  • Chronic Disease / epidemiology*
  • Comorbidity*
  • Confounding Factors, Epidemiologic
  • Female
  • Health Status*
  • Hospitalization
  • Humans
  • Male
  • Middle Aged
  • Mortality
  • Predictive Value of Tests
  • Proportional Hazards Models
  • Prospective Studies
  • Quality of Life*
  • ROC Curve
  • Reproducibility of Results
  • Risk
  • Risk Adjustment*
  • Surveys and Questionnaires
  • United States
  • Washington