Is Bias Evident in How Doctors talk to Patients?

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Is Bias Evident in How Doctors talk to Patients?

Jim Windell

            Does bias as well as both racial and gender prejudice influence how doctors talk to patients? If so, how can those biases be detected?

            It has been fairly well documented throughout our society that bias plays a part in how Whites interact with both ethnic and racial minorities and with females. But how do these biases show up in the language doctors use with their patients?

            That was the question underlying research carried out by a University of Oregon researcher.        

           David Markowitz, assistant professor and a psychology of language researcher in the School of Journalism and Communication at the University of Oregon, analyzed 1.8 million medical records for the language doctors used when communicating with patients and their families.

           Markowitz used a database of medical records for nearly 46,000 critical care patients, including over 58,000 hospital admissions to Beth Israel Deaconess Medical Center in Boston. The records excluded patient names but included demographic data and notes from doctors and nurses about the patients’ care. Then, he used an automated text analysis tool that measured impersonal pronouns (such as it, someone and who), positive emotion terms (brave, safe and gentle), negative emotion terms (bad, weak and panic), body terms (nerve, spine, stomach), analytic thinking, and cognitive processing terms (solve, determine and perhaps).

           Markowitz says that he looked at language patterns reflecting bias across groups. As he explains, “So, for example, there are patients who are identified as white or Black or male, female, etc. Using computational methods to analyze language, I identified patterns of bias through the descriptions of a patient’s condition and progress.”

           The resulting study provides some of the first evidence suggesting how language plays a central role in the patient-physician relationship from actual medical records and patient interactions, and it demonstrates systematic gender and ethnicity biases in medicine through language.

           The evidence establishes a link between communication patterns and bias that is often unobserved or under examined in medicine, Markowitz noted. It also builds on other, non-linguistic findings that indicate such inequalities are widespread in medicine.

           The analysis suggested that physicians refer to female patients in impersonal and emotional terms compared with male patients, physicians attend less to the negative experiences of Black patients than white patients, and physicians require more effort organizing their thoughts to resolve issues for Black females compared to other groups of people. Additionally, physicians writing about male patients focused more on their body than those writing about female patients.

           The data also indicated physicians thought in more analytical and rational terms when attending to male patients compared to female patients, and they used fewer indicators of needing to psychologically “work through” diagnoses for male compared to female patients.

           When Markowitz looked at gender and ethnicity, he found that physicians demonstrated the greatest need to work through diagnoses for Black women, whereas patients of other gender and ethnicities received less questioning and required less cognitive effort from caregivers. Black females, on average, were described with the lowest rate of positive affect compared to other patients.

           “What was most surprising is how clear the signals were in the data,” Markowitz said. “It really paints a picture that bias is not just a one-off phenomenon among certain physicians or individuals. Bias is systemic, subtle and consequential in medicine.” And he added that based on the evidence, caregivers of Black women tend to communicate, at least linguistically, with the greatest indicators of bias.

            Furthermore, Markowitz went on to say that not only does the evidence suggest bias in how physicians talk about their patients, but he said, “…it's probably not too far of a leap to also suggest it might affect their care as well.”

           Markowitz notes there are some caveats with these data. For instance, the data was only collected from one hospital, and it could not account for physician demographics. Also, it is unclear if the physician demographics in the study are typical of most hospitals in the U.S. Also, he said that the next steps could include incorporating findings for individual physicians into annual performance evaluations or perhaps eventually use them in real-time situations.

           “These data are unlikely to be useful as a bias detector, but instead they could be used as a red flag to indicate how some physicians are communicating with patients and make them aware of possible harmful behavior,” Markowitz said. “It would be fantastic to also get ratings from patients, too, to figure out whether they can pick up on some of these subtle biases reflected in language.”

           He also wonders of this information could lead to trainings or the providing of ways of understanding the systems that are perpetuating bias. “Because medicine as an institution has a significant negative history of undermining people of color and undermining women,” he said. “So how can we use this evidence to motivate change? We need ways to improve the system because making it more inclusive not only provides better care, it's also just the right thing to do.”

           To read the full report, find it with this reference:

Markowitz, D. M. (2022, January 10). Gender and Ethnicity Bias in Medicine: A Text Analysis of 1.8 Million Critical Care Records.



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