Abstract
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 academic medical center and to investigate whether providers' use of negative patient descriptors varied by patient race or ethnicity. We analyzed a sample of 40,113 history and physical notes (January 2019-October 2020) from 18,459 patients for sentences containing a negative descriptor (for example, resistant or noncompliant) of the patient or the patient's behavior. We used mixed effects logistic regression to determine the odds of finding at least one negative descriptor as a function of the patient's race or ethnicity, controlling for sociodemographic and health characteristics. Compared with White patients, Black patients had 2.54 times the odds of having at least one negative descriptor in the history and physical notes. Our findings raise concerns about stigmatizing language in the EHR and its potential to exacerbate racial and ethnic health care disparities.
Highlights
Little is known about how racism and bias may be communicated in the medical record
8.2 percent of patients had one or more negative descriptors recorded in the history and physical notes in their electronic health records (EHRs)
In this study conducted at an urban academic medical center, we found that Black patients had 2.54 times the odds of being described with one or more negative descriptors in the history and physical notes of their EHRs, even after we adjusted for their sociodemographic and health characteristics
Summary
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 academic medical center and to investigate whether providers’ use of negative patient descriptors varied by patient race or ethnicity. Racial disparities in health and health care during the COVID-19 pandemic have brought additional attention to how structural racism (differential access to goods, services, or opportunities based on race) can affect patient care.Yet despite greater recognition of the potential for clinician bias in health care delivery,[11] few studies have quantified clinician bias or examined how racism and bias are communicated among health care providers in clinical settings Stigmatizing language such as “sickler,” “frequent-flyer,” and other terms persist in everyday medical language[12,13,14] and may have consequences for patient care. No study to date has used a quantitative approach to examine differences in providers' use of negative patient descriptors by race or ethnicity in the context of real-world medical notes
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