Importance Stigmatizing language in the electronic health record (EHR) may alter treatment
plans, transmit biases between clinicians, and alienate patients. However, neither the …

Importance Negative attitudes toward patients can adversely impact health care quality and
contribute to health disparities. Stigmatizing language written in a patient's medical record …

Background Clinician bias contributes to healthcare disparities, and the language used to
describe a patient may reflect that bias. Although medical records are an integral method of …

Little is known about how racism and bias may be communicated in the medical record. This
study used machine learning to analyze electronic health records (EHRs) from an urban …

A growing body of literature demonstrates that healthcare providers use stigmatizing
language when speaking and writing about patients. In April 2021, the 21st Century Cures …

Importance Many clinical trial outcomes are documented in free-text electronic health
records (EHRs), making manual data collection costly and infeasible at scale. Natural …

Methods| This study took place at the University of California San Francisco Medical Center
using an inpatient EHR (Epic; Epic Systems Corporation). We analyzed inpatient progress …

Background Sharing outpatient notes with patients may bring clinically important benefits,
but notes may sometimes cause patients to feel judged or offended, and thereby reduce …

Importance By law, patients have immediate access to discharge notes in their medical
records. Technical language and abbreviations make notes difficult to read and understand …

Objective We aimed to address deficiencies in structured electronic health record (EHR)
data for race and ethnicity by identifying black and Hispanic patients from unstructured …