Why clinicians are reconsidering race-based algorithms

Algorithms are ubiquitous in medicine. They can take the form of a flowchart, a simple equation, or a complicated AI model, and are used to help clinicians diagnose diseases, predict the chances of survival, and determine if a patient is eligible for certain treatments. Many of these algorithms take a person's race into account. For example, if the person is Black, a clinician may add or subtract a point from the patient's score, which can affect their treatment.

Many in the medical community are starting to reconsider the use of race in the algorithms, and finding that in some cases, race-based calculators have delayed or prevented people from getting the right diagnoses and accessing appropriate care.

This video is a part of Embedded Bias, a series that explores how these race-based clinical algorithms are pervasive in medicine, the harm they may cause — and why it’s proving so difficult to remove race from the equation. Read the series here: https://www.statnews.com/embedded-bias/

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