In the WHAT HEALTH !? newsletter, find the latest news that has made the buzz, cutting-edge trends and groundbreaking innovations in the digital health field.
A recent study from the University Hospital of Bordeaux has revealed that gender biases may influence patient triage in emergency departments.
By analyzing over 480,000 patient records using artificial intelligence, researchers found that, for identical clinical cases, the severity of female patients’ conditions tended to be underestimated compared to male patients. This discrepancy could lead to delays in treatment for women and highlights the need for tools to detect and address such biases.
The research team plans to extend their work to assess biases related to other patient characteristics, such as age and ethnicity, and to incorporate nonverbal variables—like facial expressions and tone of voice—that are not typically captured in written data but can be critical in decision-making.
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