J Korean Med Sci.  2021 Sep;36(36):e230. 10.3346/jkms.2021.36.e230.

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

• Lee KA
• Jin HY
• Kim YJ
• Im YJ
• Kim EY
• Park TS

• KMID: 2520109
• DOI: http://doi.org/10.3346/jkms.2021.36.e230

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.

Keyword

Diabetes Mellitus Type 2; Hypoglycemic Agents; Common Data Model; Electronic Health Records

Figure

• 

  Fig. 1 Time trends in drug prescriptions for type 2 diabetes from 2000 to 2019.SU = sulfornylurea, TZD = thiazolidinedione, AGI = alpha-glucosidase inhibitor, GLP-1RA = glucagon like peptide-1 receptor agonist.

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  Fig. 2 Changes in patterns of combination therapy of oral hypoglycemic agents for type 2 diabetes from 2000 to 2019. Over time, the monotherapy prescription rates have decreased, whereas prescription rates for triple and quadruple combinations have increased steadily.Mono = monotherapy, Double = dual combination therapy, Triple = triple combination therapy, Quadruple = quadruple combination therapy.

• 

  Fig. 3 Anti-diabetic drug prescription patterns determined using a cohort pathway analysis in ATLAS software according to renal function for the period from 2013–2019. The center of each plot represents patients with diabetes initiating first-line therapy. The first ring in each sunburst plot depicts the proportion of patients in whom a type of first-line therapy was initiated defined by the event cohort. The second set of rings represents the second event cohort for patients. Patients with HbA1c < 9% were included in this analysis.eGFR = estimated glomerular filtration rate, SU = sulfornylurea, TZD = thiazolidinedione, AGI = alpha-glucosidase inhibitor, GLP-1RA = Glucagon like peptide-1 receptor agonist, DPP4I = DPP4 inhibitor, SGLT2I = SGLT2 inhibitor.

• 

  Fig. 4 Glycemic control rate over time from 2000 to 2019.

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