Black patients who received care at an urban academic medical center were more than two-and-a-half times as likely as white patients to have negative descriptors listed in their electronic health record, according to a new analysis exploring potential racial bias and stigmatizing language in healthcare.
“This difference may indicate implicit racial bias not only among individual providers but also among the broader beliefs and attitudes maintained by the healthcare system,” researchers wrote in the study published in Health Affairs. “Such bias has the potential to stigmatize Black patients and possibly compromise their care, raising concerns about systemic racism in healthcare.”
The study, conducted by University of Chicago researchers, used natural language processing and machine learning to analyze a sample of 40,113 history and physical notes collected from 18,459 adult patients between January 2019 and October 2020. Fifteen negative descriptions such as “aggressive,” “non-compliant,” “defensive” and “refuse” were identified and included in the model, which also filtered out the use of these descriptors considered to be out of context.
Alongside the disproportionate use tied to race or ethnicity, the researchers’ analysis also found negative descriptors to be more likely among patients with Medicare or Medicaid, those who were unmarried, and those with comorbidities.
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On the other hand, notes that were written in an outpatient setting or after March 1, 2020 (the onset of the COVID-19 pandemic) were less likely to include at least one negative descriptor, they wrote.
The researchers speculated that the trend among outpatient encounters could be the result of a less stressful clinical environment or the long-term, one-on-one nature of many relationships in that setting.
They also suggested that the dip in negative descriptors after March 1 could be tied to the “historically defining moment of national response to racialized state violence” that came early in the pandemic following “the police murders of George Floyd and others.”
These events “may have sensitized providers to racism and increased empathy for the experiences of racially minoritized communities,” they wrote, although more research would be needed to determine whether this or other aspects of the early pandemic—such as less frequent patient encounters—drove the change in physicians’ language.
To stem use of negative descriptors due to implicit bias, the researchers floated interventions such provider bias training as well as broader structural changes tackling workforce burnout, which prior data found was associated with greater biases among residents.
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Preventing the introduction and perpetuation of biased language will become even more critical as the healthcare industry adopts policies to share EHRs with other institutions and patients alike, they added.
“The ongoing implementation of OpenNotes should encourage both providers and institutions to seriously consider the language used to describe patients or else risk harming the patient-provider relationship with downstream effects on patient satisfaction, trust and even potential litigation,” the researchers wrote.
Racial and ethnic inequities within healthcare settings have been well documented in recent years.
Analyses from the Commonwealth Fund and the Urban Institute published within the last few months, for instance, have outlined reduced quality of care across every state and even within the same hospital. With these disparities in mind, numerous organizations have come together promising action on health equity across care settings and technologies.