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Identifying Hypertension-Related Comorbidities From Administrative Data: What's the Optimal Approach?

Department of Health Services, Boston University School of Public Health, Boston, Mass, Center for Health Quality, Outcomes and Economic Re-search, Bedford VAMC, Bedford, Mass, amb{at}bu.edu

Ashley T. Wong, MA

Department of Health Services, Boston University School of Public Health, Bos-ton, Mass, Center for Health Quality, Outcomes and Economic Re-search, Bedford VAMC, Bedford, Mass

Elaine C. Hickey, RN, MS

Center for Health Quality, Outcomes and Economic Re-search, Bedford VAMC, Bedford, Mass

Arlene S. Ash, PhD

Section of General Internal Medicine, Boston Medical Center, and Boston University School of Medicine, Boston, Mass

Dan R. Berlowitz, MD, MPH

Department of Health Services, Boston University School of Public Health, Bos-ton, Mass, Center for Health Quality, Outcomes and Economic Re-search, Bedford VAMC, Bedford, Mass, Section of General Internal Medicine, Boston Medical Center, and Boston University School of Medicine, Boston, Mass

The objective was to determine the best strategy for identifying outpatients with hypertension-related diagnoses using Veterans Affairs (VA) administrative databases. We reviewed 1176 outpatient charts from 10 VA sites in 1999, taking the presence of 11 diagnoses relevant to hypertension management as the "gold standard" for identifying the comorbidity. We calculated agreement, sensitivity, and specificity for the chart versus several administrative data-based algorithms. Using 1999 data and requiring 1 administrative diagnosis, observed agreement ranged from 0.98 (atrial fibrillation) to 0.85 (hyperlipidemia), and kappas were generally high. Sensitivity varied from 38% (tobacco use) to 97% (diabetes); specificity exceeded 91% for 10 of 11 diagnoses. Requiring 2 years of data and 2 diagnoses improved most measures, with minimal sensitivity decrease. Agreement between the database and charts was good. Administrative data varied in its ability to identify all patients with a given diagnosis but identified accurately those without. The best strategy for case-finding required 2 diagnoses in a 2-year period.

Key Words: Administrative data • hypertension • sensitivity • specificity

American Journal of Medical Quality, Vol. 19, No. 5, 201-206 (2004)
DOI: 10.1177/106286060401900504


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