The Vermont Diabetes Information System (VDIS): study design and subject recruitment for a cluster randomized trial of a decision support system in a regional sample of primary care practices

Abstract

BACKGROUND: Despite evidence that optimal care for diabetes can result in reduced complications and improved economic outcomes, such care is often not achieved. The Vermont Diabetes Information System (VDIS) is a registry-based decision support and reminder system based on the Chronic Care Model and targeted to primary care physicians and their patients with diabetes. PURPOSE: To develop and evaluate a regional decision support system for patients with diabetes. METHODS: Randomized trial of an information system with clustering at the practice level. Ten percent random subsample of patients selected for a home interview. SUBJECT: and setting includes 10 hospitals, 121 primary care providers, and 7348 patients in 55 Vermont and New York primary care practices. RESULTS: We report on the study design and baseline characteristics of the population. Patients have a mean age of 63 years and a mean glycosolated hemoglobin A1C of 7.1 %. Sixty percent of the population has excellent glycemic control (A1 C < 7%); 45% have excellent lipid control (serum LDL-cholesterol <100 mg /dL and serum triglycerides <400 mg/dL). Twenty-five percent have excellent blood pressure control (<130/80mmHg). These results compare favorably to recent national reports. However, only 8% are in optimal control for all three of hyperglycemia, lipids and blood pressure. CONCLUSIONS: Our experience to date indicates that a low cost decision support and information system based on the Chronic Care Model is feasible in primary care practices that lack sophisticated electronic information systems. VDIS is well accepted by patients, providers and laboratory staff. If proven beneficial in a rigorous, randomized, controlled evaluation, the intervention could be widely disseminated to practices across America and the world with a substantial impact on the outcomes and costs of diabetes. It could also be adapted to other chronic conditions. We anticipate the results of the study will be available in 2006.

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