How AI is integrated into clinical workflows may significantly influence how medical liability is perceived, according to a study in Nature Health.
Researchers from Hershey, Pa.-based Penn State College of Medicine, Providence, R.I.-based Brown University and Newark, N.J.-based Seton Hall University School of Law found that jurors were about 50% more likely to side with a plaintiff in a malpractice scenario when a radiologist reviewed imaging once after an AI alert, compared to reviewing it both before and after AI input.
“AI holds promise to improve the quality and safety of healthcare and to reduce errors and patient harm, but the risk of legal liability is a potential barrier for investment and development of this technology as well as the quality of care,” said study co-author Michael Bruno, MD, professor of radiology and medicine at Penn State College of Medicine, in a March 19 news release.
In the study, mock jurors evaluated a case in which a radiologist missed a brain bleed on a CT scan that AI had correctly flagged as abnormal, resulting in severe patient harm.
Nearly 75% of participants said the radiologist failed to meet the standard of care with a single read, compared to about 53% when the clinician performed a double read incorporating AI feedback.
The findings suggest that how AI is incorporated into clinician workflows — including timing and frequency of review — may help mitigate perceived legal risk, though researchers noted such changes could carry cost and workflow implications.
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