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J Ambul Care Manage. 2004 Jul-Sep;27(3):281-95.

Comorbidity assessments based on patient report: results from the Veterans Health Study.

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  • 1From the Centerfor Health Quality, Outcomes, and Economic Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Mass, USA. Alfredo_J@Boston.VA.gov

Abstract

The objective of the study was to develop a self-reported measure of patients' comorbid illnesses that could be readily administered in ambulatory care settings and that would improve assessment of their health-related quality of life and utilization of health services. Data were analyzed from the Veterans Health Study, an observational study of health outcomes in patients receiving Veterans Administration (VA) ambulatory care. Patients who received ambulatory care services in 4 VA outpatient clinics in the greater Boston area between August 1993 and March 1996 were eligible for inclusion. Among the 4137 patients recruited, 2425 participated in the Veterans Health Study, representing a response rate of 59%. Participants were mailed a health-related quality of life questionnaire, the Medical Outcomes Study Short Form Health Survey (SF-36). They were also scheduled for an in-person interview at which time they completed a medical history questionnaire. We developed a comorbidity index (CI) that included 30 self-reported medical conditions (physical CI) and 6 self-reported mental conditions (mental CI). The physical CI and the mental CI were significantly associated with all SF-36 scales and explained 24% and 36%, respectively, of the variance in the physical component summary and the mental component summary of the SF-36. Both indexes were also significant predictors of future outpatient visits and mortality. The CI is an independent predictor of health status, outpatient visits, and mortality. Its use appears to be a practical approach to case-mix adjustment to account for differences in comorbid illnesses in observational studies of the quality of healthcare. It can be administered to large patient populations at relatively low cost. This method may be particularly valuable for clinicians and researchers interested in population-based studies, case-mix adjustment, and clinical trials.

PMID:
15287217
[PubMed - indexed for MEDLINE]
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