alexa Who has diabetes? Best estimates of diabetes prevalence in the Department of Veterans Affairs based on computerized patient data.
Mathematics

Mathematics

Journal of Biometrics & Biostatistics

Author(s): Miller DR, Safford MM, Pogach LM

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Abstract OBJECTIVE: To optimize methods for identifying patients with diabetes based on computerized records and to obtain best estimates of diabetes prevalence in Department of Veterans Affairs (VA) patients. RESEARCH DESIGN AND METHODS: The VA Diabetes Epidemiology Cohort (DEpiC) is a linked national database of all VA patients since 1998 with data from VA medical visits, Medicare claims, pharmacy and laboratory records, and patient surveys. Using DEpiC, we examined concordance of diabetes indicators, including ICD-9-CM codes (250.xx), prescription drug treatment, HbA(1c) tests, and patient self-report. We determined the optimal criterion for identifying diabetes and used it in estimating diabetes prevalence in the VA. RESULTS: The best criterion was a prescription for a diabetes medication in the current year and/or 2+ diabetes codes from inpatient and/or outpatient visits (VA and Medicare) over a 24-month period. This definition had high sensitivity (93\%) and specificity (98\%) against patient self-report, and reasonable rates of HbA(1c) testing (75\%). HbA(1c) testing alone added few additional cases, and a single diagnostic code added many patients, but without confirmation (reduced specificity). However, including codes from Medicare was critical. Applying this definition for 1998-2000, we identified an average of 500,000 VA patients with diabetes per year. We also estimated high and increasing diabetes prevalence rates of 16.7\% in FY1998, 18.6\% in FY1999, and 19.6\% in FY2000 and an incidence estimated to be approximately 2\% per year. CONCLUSIONS: Development and evaluation of methodology for analyzing computerized patient data can improve the identification of patients with diabetes. The increasing high prevalence of diabetes in VA patients will present challenges for clinicians and health system management.
This article was published in Diabetes Care and referenced in Journal of Biometrics & Biostatistics

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