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Stigmatizing Language in EHR Notes Reveals Implicit Bias Concerns

EHR notes about Black patients were 67 percent more likely to contain stigmatizing language compared to notes about White patients.

EHR notes of Black patients were more likely to contain stigmatizing language compared to those of White patients, according to a study published in JAMA Network Open that raises concerns for implicit bias in clinical documentation and its potential to exacerbate racial health disparities.

Researchers used natural language processing to analyze EHR admission notes for 29,783 patients at a large, urban academic medical center.

Clinicians used stigmatizing language about diabetes, substance use disorder, or chronic pain in one of 40 hospital admission notes.

The study authors defined stigmatizing words and phrases based on the current literature for each condition.

For instance, referring to someone with substance use disorder as a “user” is considered stigmatizing. For chronic pain patients, an example of stigmatizing language in EHR documentation is using “narcotic” opposed to “opioid.”

Across all conditions studied, admission notes about non-Hispanic Black patients were 67 percent more likely to contain stigmatizing language than notes about non-Hispanic White patients.

“This is unsurprising given evidence that physicians (like the general US population) display pro-White and anti-Black attitudes on tests of implicit bias, and that this racism adversely affects the care provided to patients of color,” the study authors wrote.

The researchers noted the disproportionate use of stigmatizing language in Black patients EHR notes raises concern for how implicit bias in clinical documentation could worsen racial health disparities.

“Stigmatizing language in notes may magnify the adverse health consequences of stigma imposed by racism in other venues,” they wrote.

“Furthermore, the history of medical experimentation and physician mistreatment of Black patients has undermined the trust of many racial and ethnic minority individuals in the medical system, which may cause avoidance of vaccines and other care,” the study authors added.

As patients gain access to their EHR data, the disproportionate use of stigmatizing language in notes for Black patients risks intensifying patients’ distrust in the medical establishment, the researchers said.

The authors pointed out several limitations to the study.

“While we compiled lists of stigmatizing language from existing literature, no consensus exists about what language is stigmatizing, and many stigmatizing terms have not been linked to substandard care,” they wrote.

They also noted that it may be challenging for physicians to accurately document patients’ care without the use of stigmatizing words, such as nonadherence.

Additionally, the researchers pointed out that their data did not include measures of socioeconomic status (SES), barring analysis of whether differences in SES play a role in the race-based disparities observed.

“Untangling the roles of race and SES is particularly complex because racism is associated with low SES,” they wrote. “Exploration of the relationships between patient race and ethnicity, SES, and the use of stigmatizing language is an important area for future study.”

This study builds on recent research published in Health Affairs that found black patients were 2.54 times more likely to have at least one negative descriptor in their EHR notes compared to White patients.

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