The Vermont Diabetes Information System: A Cluster Randomized Trial of a Population Based Decision Support System

Optimal care for patients with diabetes is difficult to achieve in clinical practice. To evaluate the impact of a registry and decision support system on processes of care, and physiologic control. Randomized trial with clustering at the practice level, involving 7,412 adults with diabetes in 64 primary care practices in the Northeast. Provider decision support (reminders for overdue diabetes tests, alerts regarding abnormal results, and quarterly population reports with peer comparisons) and patient decision support (reminders and alerts). Process and physiologic outcomes were evaluated in all subjects. Functional status was evaluated in a random patient sample via questionnaire. We used multiple logistic regression to quantify the effect, adjusting for clustering and potential confounders. Intervention subjects were significantly more likely to receive guideline-appropriate testing for cholesterol (OR = 1.39; [95%CI 1.07, 1.80] P = 0.012), creatinine (OR = 1.40; [95%CI 1.06, 1.84] P = 0.018), and proteinuria (OR = 1.74; [95%CI 1.13, 1.69] P = 0.012), but not A1C (OR = 1.17; [95% CI 0.80, 1.72] P = 0.43). Rates of control of A1C and LDL cholesterol were similar in the two groups. There were no differences in blood pressure, body mass index, or functional status. A chronic disease registry and decision support system based on easily obtainable laboratory data was feasible and acceptable to patients and providers. This system improved the process of laboratory monitoring in primary care, but not physiologic control.