Use of electronic medical records for clinical research in the management of type 2 diabetes

Background: Essential to optimal diabetes care is the organization and management of complex clinical data. An EMR system can facilitate better management of clinical and clinical-related information by standardizing care and increasing the efficiency of delivering quality care to patients. However, studies have not described clinical characteristics of patients with type 2 diabetes in a primary practice setting that utilizes an EMR system. Objective: To describe the demographic characteristics, clinical measures, and resource utilization of patients with type 2 diabetes in a primary care setting that employs an EMR system. Methods: Patients >= 18 years of age, having two or more visits with their physicians (January 1, 2012 to December 31, 2012), and with a recorded diagnosis of diabetes (ICD-9-CM: 250.xx) were retrospectively identified from the GE Centricity (R) EMR database of a primary care physician group. Demographic characteristics, clinical measures, and resource utilization were evaluated. Descriptive statistics were conducted using frequencies and proportions for categorical data and means and standard deviations for continuous variables. Results: 5170 patients with type 2 diabetes were identified for year 2012. Majority of patients with type 2 diabetes were males (53.38%), whites (86.63%), and obese (62.19%); had HbA1c levels < 7% (51.72%), LDL-C levels < 100 mg/dL (59.09%), HDL-C levels >= 40 (56.25%); and had never smoked (54.89%). Compared to patients with HbA1c < 7% and 7%-9%, those with HbA1c > 9% were the youngest, had higher average office visits/patient, and had a higher prevalence of depression, obesity, elevated LDL-C and lower HDL-C levels. Conclusions: This study provides insight into the potential risk factors for diabetes such as the presence of obesity, dyslipidemia, and depression, specifically in patients with HbA1c levels above 9%. Physicians should use evidence-based benchmarks in the development of EMR disease management programs to improve patient outcomes and quality of care. (C) 2014 Elsevier Inc. All rights reserved.