Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for "Complete Data": Observational Clinical Data Analysis.

ABSTRACT:

Background

Integrated clinical databases from national biobanks have advanced the capacity for disease research. Data quality and completeness filters are used when building clinical cohorts to address limitations of data missingness. However, these filters may unintentionally introduce systemic biases when they are correlated with race and ethnicity.

Objective

In this study, we examined the race and ethnicity biases introduced by applying common filters to 4 clinical records databases. Specifically, we evaluated whether these filters introduce biases that disproportionately exclude minoritized groups.

Methods

We applied 19 commonly used data filters to electronic health record datasets from 4 geographically varied locations comprising close to 12 million patients to

SUBMITTER: Acitores Cortina JM 

PROVIDER: S-EPMC11967746 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature