Improving Efficacy of Diabetes Management Using Treatment Algorithms in a Mainly Hispanic Population

Abstract

OBJECTIVE—To compare clinical outcomes obtained using treatment algorithms versus standard “usual care” to treat patients with type 2 diabetes in a community setting. RESEARCH DESIGN AND METHODS—An observational group comparison was implemented in three community-based clinics in San Antonio, Texas: 1) a community clinic following treatment algorithms (CC-TA), 2) university clinic following treatment algorithms (UC-TA), and 3) a community clinic following standard “usual care” practices (CC-SC). Three hundred fifty-eight recently diagnosed type 2 diabetic patients (90% Mexican American, from low-income neighborhoods) who were consecutively identified at the three clinics were recruited. Following medical and laboratory evaluation, participants were started on treatment for hyperglycemia, hypertension, and dyslipidemia and followed for 12 months. RESULTS—Decrements in HbA1c at 12 months in the CC-TA and UC-TA were 3.1 and 3.3%, respectively, compared to 1.3% in the CC-SC (P < 0.0001). Corresponding decrements in fasting plasma glucose at 12 months were 94 and 99 mg/dl, respectively, versus 38 mg/dl in CC-SC (P < 0.0001). Reductions in total cholesterol, LDL cholesterol, and triglycerides at 12 months were greater in both algorithm-managed clinics compared to standard care–managed clinics (P < 0.0001). In algorithm-managed clinics, there were 30% more documented eye exams and 24% more documented foot exams than in standard care–managed patients. CONCLUSIONS—Adherence to the treatment algorithms improved metabolic outcomes in type 2 diabetic patients to a greater extent than standard care practices. These results have important clinical implications for the treatment of type 2 diabetic patients.