Comparing computable type 2 diabetes phenotype definitions in identifying populations of interest for clinical research.

ABSTRACT:

Objective

Significant variations exist in computable phenotype definitions to identify patients with type 2 diabetes (T2D) using electronic health records (EHRs). These variations cause challenges in identifying T2D populations for clinical research. To address these challenges, this study compares the variations in common phenotypes in identifying patients with T2D using EHRs.

Methods

A retrospective data analysis was performed using clinical data extracted from EHRs of 207 813 adult patients captured 2017-2019. Multiple T2D phenotypes were used: (1) Surveillance, Prevention and Management of Diabetes Mellitus, (2) Centers for Medicare and Medicaid Services Chronic Conditions Data Warehouse (CCW), (3) eMERGE Northwestern Group, (4) Durham Diabetes Coalition (DDC) and (5) a

SUBMITTER: Sood PD 

PROVIDER: S-EPMC12548627 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature