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Objectives: To describe prescribing patterns of metformin in low-income and Medicaid-insured patients with prediabetes and to identify common demographic characteristics and comorbid conditions of low-income and Medicaid-insured patients receiving metformin for treatment of prediabetes., Design: Retrospective observational study., Setting and Participants: Patients (18-60 years old) who were enrolled in South Carolina Medicaid and diagnosed with prediabetes between January 2009 and December 2013., Main Outcome Measures: Metformin prescribing to treat prediabetes identified from pharmacy claims., Results: Among 7102 patients who met the study criteria, 7.4% (n = 520) were prescribed metformin for prediabetes. Nearly 45% (n = 238) of eligible patients prescribed metformin initiated treatment within 30 days after diagnosis of prediabetes. Twenty-five percent of those prescribed metformin took 280 days or longer to initiate treatment after diagnosis of prediabetes. Older age, black race, managed care plan, comorbid hypertension and obesity, and longer enrollment period significantly increased the likelihood of metformin prescribing to treat prediabetes., Conclusion: Prevalence of metformin prescription to treat prediabetes is less than 8% in low-income and Medicaid-insured patients. Sociodemographic characteristics and comorbid conditions influenced metformin prescribing in the low-income population., (Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.)

Background: Prediabetes is a high-risk factor for progression to diabetes. Without lifestyle changes, such as weight loss and moderate physical activity, 15%-30% of people with prediabetes are projected to develop type 2 diabetes within 5 years. Progression to diabetes increases the financial burden significantly for patients and health care systems. Populations with low socioeconomic status are associated with a higher risk of diabetes. However, knowledge is limited about the effect of transition to diabetes on future costs incurred in low-income populations., Objectives: To (a) describe the characteristics of low-income and insured patients with prediabetes and (b) examine the effect of progression to type 2 diabetes on health care utilization and costs., Methods: This study used South Carolina Medicaid claims data (2009-2014) to identify patients (aged ≥18 years) with newly diagnosed prediabetes. All patients were enrolled in Medicaid continuously for at least 1 year before and after the diagnosis of prediabetes and were followed for at least 1 year and up to 6 years. The time to progression to type 2 diabetes was measured by a Kaplan Meier curve, and risk factors associated with onset of type 2 diabetes were identified by Cox regression. Generalized linear models were applied to assess the effect of progression to type 2 diabetes on total health care costs during the first 3-year period., Results: A total of 7,650 patients with prediabetes met the study criteria. During the follow-up period, 30.3% of the study population developed type 2 diabetes within 3 years. Older age, African-American race, fee-for-service plan, comorbid hypertension, obesity, and dyslipidemia were associated with higher risk for onset of type 2 diabetes. Compared with patients who did not progress to type 2 diabetes, the progression to type 2 diabetes increased total health care costs by 22.1% (P < 0.001), 39.1% (P < 0.001), and 47.6% (P < 0.001) during the first 3 years after adjusting for demographic and comorbid conditions., Conclusions: Age, race, type of Medicaid plan, and diabetes-related comorbidities were associated with risk for progression of prediabetes. Progression to type 2 diabetes significantly increased total health care costs in the first 3 years. Early detection and intervention to prevent or delay onset of type 2 diabetes are needed to control health care utilization and costs., Disclosures: This study was funded by Small Pharmacy Awards for Research and Collaboration, Presbyterian College. The funding resource had no role in the design and conduct of the study, analysis or interpretation of the data, or the preparation or final approval of the manuscript before publication. The authors declare no conflicts of interest. Study concept and design were contributed by Wu, Ward, and Lu, along with Threatt. Wu took the lead in data collection, along with Ward and Lu, with assistance from Threat. Data interpretation was provided by Wu, Ward, Threatt, and Lu. The manuscript was written and revised by Wu, Ward, and Threatt, along with Lu.