Explore the clinical tools that use race to steer care
Every day, physicians use clinical algorithms to make decisions about the patients in their exam rooms. To help weigh a patient’s surgical risk or likelihood of disease, they factor in attributes such as blood pressure, age, weight, surgical history — and in some cases, a patient’s race. Like many clinical researchers, bioinformatician Shyam Visweswaran started learning about those race-based tools in 2020, when a catalyzing New England Journal of Medicine paper laid out 13 common examples in medicine.
“That started me thinking,” said Visweswaran, who helps clinicians implement their experimental algorithms as vice chair of informatics at the University of Pittsburgh. “I wanted to see what the scope of this is, how many such algorithms are out there.” He couldn’t find a resource to answer the question — so he decided to build one. In the most comprehensive list to date, Visweswaran and his colleagues describe 48 clinical tools with race adjustments, three of which were added based on STAT’s reporting.
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