- A new study reveals a racial bias in how clinicians describe patients in their electronic health records, raising concerns about stigmatizing language that could contribute to ongoing racial and ethnic healthcare disparities.
- Black patients were 2.5 times more likely to have one or more negative descriptor in their EHR compared with White patients, according to the study published Wednesday in Health Affairs.
- Patients with government insurance and unmarried patients also had higher adjusted odds of negative descriptors compared with commercially insured and married patients.
Racial disparities in the U.S. medical system have been well documented, with mountains of research finding massive gaps in care and access for White versus non-White people. However, recent cultural movements like Black Lives Matter and the COVID-19 pandemic have brought the issue to the fore, leading numerous health systems to pledge their commitment to erasing care discrepancies and causing the Biden administration to make health equity a key prong of its healthcare agenda.
Despite more attention on the issue, it's unclear whether the needle is moving. In 2020, four national surveys found that 11% to 20% of Black adults reported experiencing discrimination in healthcare in the preceding year — a rate almost three times higher than White adults and about twice as high as Latino and Hispanic adults.
Often, unconscious attitudes and stereotypes can negatively impact the care some patients receive. Studies have found such implicit biases are associated with lower adherence to treatment plans and lower trust in providers, and can lead to patients avoiding or delaying needed care, worsening outcomes.
Researchers associated with the University of Chicago wanted to investigate whether the use of negative patient descriptors in EHRs varied by patient race and ethnicity, perhaps reflecting implicit biases of medical workers. To do so, they reviewed more than 40,000 history and physical notes covering about 18,500 patients from one urban academic medical center in Chicago, from January 2019 to October 2020. The notes were combed for sentences containing negative descriptors such as "resistant," "noncompliant," "defensive" or "aggressive." Researchers then used machine learning to determine the odds of finding at least one such descriptor as a function of race, controlling for other sociodemographic and health factors.
The study found such negative descriptors were being disproportionately applied to racially minoritized patients, especially Black patients.
That's alarming as history and physical notes contain key information that's frequently accessed by other care providers, researchers noted. Therefore, the negative descriptors are more likely to be copied onto future notes, amplifying any initial bias.
"Our findings suggest disproportionate use of negative patient descriptors for Black patients compared with their White counterparts, which raises concerns about racial bias and possible transmission of stigma in the medical record," the researchers wrote. "Such bias has the potential to stigmatize Black patients and possibly compromise their care, raising concerns about systemic racism in health care."
Notably, medical notes written after the beginning of the pandemic were less likely to include negative descriptors, researchers found.
The onset of COVID-19 in the U.S. in early 2020 coincided with Black Lives Matter, a political and social movement seeking to highlight racism and discrimination that gained national attention following the police murder of George Floyd. The movement grew in intensity at the same time as early pandemic statistics were revealing stark racial disparities in health access and outcomes.
Those social pressures may have sensitized providers to racism and increased empathy for the experiences of Black Americans, lowering their use of negative descriptors in notes, researchers said.
Researchers noted that while further research on implicit biases is needed, medical institutions can better address such biases today through interventions like provider bias training and better education on race and racism in America.