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How racist is your algorithm?


 

Every time Nathan Chomilo, MD, uses a clinical decision support tool, he tells his patients they have a choice: He can input their race or keep that field blank.

Until recently, many clinicians didn’t question the use of race as a datapoint in tools used to make decisions about diagnosis and care. But that is changing.

“I’ve almost universally had patients appreciate that someone actually told them that their kidney function was being scored differently because of the color of their skin or how they were identified in the medical chart along lines of race,” Dr. Chomilo, an adjunct assistant professor of pediatrics at the University of Minnesota Medical School, Minneapolis, said.

Dr. Chomilo is referring to the estimated glomerular filtration rate (eGFR), which combines results from a blood test with factors such as age, sex, and race to calculate kidney function.

The eGFR weighed an input of “African American” as automatically indicating a higher concentration of serum creatinine than a non African American patient on the basis of the unsubstantiated idea that Black people have more creatinine in their blood at baseline.

The calculator creates a picture of a Black patient who is not as sick as a White patient with the same levels of kidney failure. But race is based on the color of a patient’s skin, not on genetics or other clinical datapoints.

“I often use my own example of being a biracial Black man: My father’s family is from Cameroon, my mother’s family is from Norway. Are you going to assign my kidneys or my lungs to my mom’s side or my dad’s side? That’s not clear at all in the way we use race in medicine,” Dr. Chomilo, an executive committee member on the section on minority health equity and inclusion at the American Academy of Pediatrics (AAP), said.

Long before the COVID-19 pandemic so publicly exposed the depths of inequality in morbidity and mortality in the United States, health advocates had been pointing out these disparities in tools used by medical professionals. But efforts to recognize that race is a poor proxy for genetics is in its infancy.

In May, the AAP published a policy statement that kicked off its examination of clinical guidelines and policies that include race as a biological proxy. A committee for the society is combing through each guideline or calculator, evaluating the scientific basis for the use of race, and examining whether a stronger datapoint could be used instead.

The eGFR is perhaps the best example of a calculator that’s gone through the process: Health care stakeholders questioned the use of race, and investigators went back to study whether race was really a good datapoint. It wasn’t, and Dr. Chamilo’s hospital joined many others in retiring the calculator.

But the eGFR is one of countless clinical tools – from rudimentary algorithms to sophisticated machine-learning instruments – that change the course of care in part on the basis of race in the same way datapoints such as weight, age, and height are used to inform decisions about patient management. But unlike race, height, weight, and age can be objectively measured. A physician either makes a guess, or a patient enters their race on a form. And while that can be useful on a population level, race does not equal genetics or any other measurable datapoint.

In a study published in JAMA Pediatrics, researchers reviewed 414 clinical practice guidelines from sources such as PubMed and MetaLib.gov. Almost 1 in 6 guidelines included race in an inappropriate way, such as by conflating race as a biological risk factor or establishing testing or treatment thresholds using race.

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