2022
DOI: 10.1001/jamanetworkopen.2021.44967
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Examination of Stigmatizing Language in the Electronic Health Record

Abstract: This cross-sectional study analyzes the prevalence of stigmatizing language in the electronic health records at a large academic medical center.

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Cited by 104 publications
(66 citation statements)
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References 36 publications
(70 reference statements)
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“…Finally, questions remain with respect to how PAEHRs affect the quality of documentation [ 102 ]. In this area, the approach of natural language processing has been increasingly used to quantitatively examine note changes, for example, according to ethnicity and disease chronicity [ 103 ].…”
Section: Discussionmentioning
confidence: 99%
“…Finally, questions remain with respect to how PAEHRs affect the quality of documentation [ 102 ]. In this area, the approach of natural language processing has been increasingly used to quantitatively examine note changes, for example, according to ethnicity and disease chronicity [ 103 ].…”
Section: Discussionmentioning
confidence: 99%
“…This non-accommodation has been translated into inequities in healthcare practices. For instance, racially dissimilar (e.g., Non-Hispanic White) physicians who are likely experiencing communication through an intergroup (interracial) lens may not recognize situations requiring communication accommodation (e.g., exercising cultural sensitivity during both listening and speaking), which has led to labeling Black-identifying patients as uncooperative [ 44 , 45 ]. Our findings suggest that such implicit biases towards AAE persist to this day and such negative perceptions toward AAE translate into poor evaluation of AAE-speaking HCPs.…”
Section: Discussionmentioning
confidence: 99%
“…A large US based study in three centers found that 11% (n=2411) of patients who accessed their notes felt judged or offended by what they read, which included errors, surprises, forms of labeling, and disrespectful wording. 22 Linguistic analyses of documentation in the US recently found that stigmatizing language was significantly more common in notes written about black patients than notes about white patients, 23 24 and among patients with diagnoses of diabetes, 24 substance abuse disorders, or chronic pain.…”
Section: Risks Of Patients’ Online Access To Their Recordsmentioning
confidence: 99%