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Huang TY, Rodriguez-Watson C, Wang T, Calhoun SR, Marshall J, Burk J, Nam YH, Mendelsohn AB, Jamal-Allial A, Greenlee RT, Selvan M, Pawloski PA, McMahill Walraven CN, Rai A, Toh S, Brown JS. Using the IMEDS distributed database for epidemiological studies in type 2 diabetes mellitus. BMJ Open Diabetes Res Care 2022; 10:10/6/e002916. [PMID: 36535702 PMCID: PMC9764656 DOI: 10.1136/bmjdrc-2022-002916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 11/09/2022] [Indexed: 12/23/2022] Open
Abstract
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.
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Affiliation(s)
- Ting-Ying Huang
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Carla Rodriguez-Watson
- Reagan-Udall Foundation for the Food and Drug Administration, Washington, District of Columbia, USA
| | - Tongtong Wang
- Epidemiology, Merck & Co, Inc, Rahway, New Jersey, USA
| | | | - James Marshall
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - Jillian Burk
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - Young Hee Nam
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Aaron B Mendelsohn
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | | | | | - Mano Selvan
- Humana Healthcare Research, Louisville, Kentucky, USA
| | | | | | - Ashish Rai
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Sengwee Toh
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Jeffery S Brown
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, USA
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