Assessing the Effect of Electronic Health Record Data Quality on Identifying Patients With Type 2 Diabetes: Cross-Sectional Study.

ABSTRACT:

Background

Increasing and substantial reliance on electronic health records (EHRs) and data types (ie, diagnosis, medication, and laboratory data) demands assessment of their data quality as a fundamental approach, especially since there is a need to identify appropriate denominator populations with chronic conditions, such as type 2 diabetes (T2D), using commonly available computable phenotype definitions (ie, phenotypes).

Objective

To bridge this gap, our study aims to assess how issues of EHR data quality and variations and robustness (or lack thereof) in phenotypes may have potential impacts in identifying denominator populations.

Methods

Approximately 208,000 patients with T2D were included in our study, which used retrospective EHR data from the Johns Hopkins Me

SUBMITTER: Sood PD 

PROVIDER: S-EPMC11370182 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature