Assessing the accuracy of electronic health record gender identity and REaL data at an academic medical center

Assessing the accuracy of electronic health record gender identity and REaL data at an academic medical center

Abstract Background Collection of accurate patient race, ethnicity, preferred language (REaL) and gender identity in the electronic health record (EHR) is essential for equitable and inclusive care. Misidentification of these factors limits quality measurement of health outcomes in at-risk populatio...

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Bibliographic Details
Main Authors: Rachael Proumen, Hannah Connolly, Nadia Alexandra Debick, Rachel Hopkins
Format: Article
Language:English
Published: BMC 2023-08-01
Series:BMC Health Services Research
Subjects:
Electronic health record
Race and ethnicity
Language
Gender identity
Data quality
Online Access:https://doi.org/10.1186/s12913-023-09825-6

Internet

https://doi.org/10.1186/s12913-023-09825-6

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