BMJ Open Diabetes Research & Care (Dec 2022)

Using the IMEDS distributed database for epidemiological studies in type 2 diabetes mellitus

  • Young Hee Nam,
  • Tongtong Wang,
  • Robert T Greenlee,
  • James Marshall,
  • Aaron B Mendelsohn,
  • Aziza Jamal-Allial,
  • Sengwee Toh,
  • Ting-Ying Huang,
  • Carla Rodriguez-Watson,
  • Shawna R Calhoun,
  • Jillian Burk,
  • Mano Selvan,
  • Pamala A Pawloski,
  • Cheryl N McMahill Walraven,
  • Ashish Rai,
  • Jeffery S Brown

DOI
https://doi.org/10.1136/bmjdrc-2022-002916
Journal volume & issue
Vol. 10, no. 6

Abstract

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Introduction This study aimed to assess data relevancy and data quality of the Innovation in Medical Evidence Development and Surveillance System Distributed Database (IMEDS-DD) for diabetes research and to evaluate comparability of its type 2 diabetes cohort to the general type 2 diabetes population.Research design and methods A retrospective study was conducted using the IMEDS-DD. Eligible members were adults with a medical encounter between April 1, 2018 and March 31, 2019 (index period). Type 2 diabetes and co-existing conditions were determined using all data available from April 1, 2016 to the most recent encounter within the index period. Type 2 diabetes patient characteristics, comorbidities and hemoglobin A1c (HbA1c) values were summarized and compared with those reported in national benchmarks and literature.Results Type 2 diabetes prevalence was 12.6% in the IMEDS-DD. Of 4 14 672 patients with type 2 diabetes, 52.8% were male, and the mean age was 65.0 (SD 13.3) years. Common comorbidities included hypertension (84.5%), hyperlipidemia (82.8%), obesity (45.3%), and cardiovascular disease (44.7%). Moderate-to-severe chronic kidney disease was observed in 20.2% patients. The most commonly used antihyperglycemic agents included metformin (35.7%), sulfonylureas (14.8%), and insulin (9.9%). Less than one-half (48.9%) had an HbA1c value recorded. These findings demonstrated the notable similarity in patient characteristics between type 2 diabetes populations identified within the IMEDS-DD and other large databases.Conclusions Despite the limitations related to HbA1c data, our findings indicate that the IMEDS-DD contains robust information on key data elements to conduct pharmacoepidemiological studies in diabetes, including member demographic and clinical characteristics and health services utilization.