Treatment Patterns of Type 2 Diabetes Assessed Using a Common Data Model Based on Electronic Health Records of 2000–2019

ABSTRACT

Background@#Real-world data analysis is useful for identifying treatment patterns.Understanding drug prescription patterns of type 2 diabetes mellitus may facilitate diabetes management. We aimed to analyze treatment patterns of type 2 diabetes mellitus using Observational Medical Outcomes Partnership Common Data Model based on electronic health records. @*Methods@#This retrospective, observational study employed electronic health records of patients who visited Jeonbuk National University Hospital in Korea during January 2000– December 2019. Data were transformed into the Observational Medical Outcomes Partnership Common Data Model and analyzed using R version 4.0.3 and ATLAS ver. 2.7.6. Prescription frequency for each anti-diabetic drug, combination therapy pattern, and prescription pattern according to age, renal function, and glycated hemoglobin were analyzed. @*Results@#The number of adults treated for type 2 diabetes mellitus increased from 1,867 (2.0%) in 2000 to 9,972 (5.9%) in 2019. In the early 2000s, sulfonylurea was most commonly prescribed (73%), and in the recent years, metformin has been most commonly prescribed (64%). Prescription rates for DPP4 and SGLT2 inhibitors have increased gradually over the past few years. Monotherapy prescription rates decreased, whereas triple and quadruple combination prescription rates increased steadily. Different drug prescription patterns according to age, renal function, and glycated hemoglobin were observed. The proportion of patients with HbA1c ≤ 7% increased from 31.1% in 2000 to 45.6% in 2019, but that of patients visiting the emergency room for severe hypoglycemia did not change over time. @*Conclusion@#Medication utilization patterns have changed significantly over the past 20 years with an increase in the use of newer drugs and a shift to combination therapies. In addition, various prescription patterns were demonstrated according to the patient characteristics in actual practice. Although glycemic control has improved, the proportion within the target is still low, underscoring the need to improve diabetes management.