A team of researchers says it has developed the first wearable camera system that, with the help of artificial intelligence, detects potential errors in medication delivery.
In a test whose results were published today, the video system recognized and identified, with high proficiency, which medications were being drawn in busy clinical settings. The AI achieved 99.6% sensitivity and 98.8% specificity at detecting vial-swap errors.
The findings are reported Oct. 22 in npj Digital Medicine.
The system could become a critical safeguard, especially in operating rooms, intensive-care units and emergency-medicine settings, said co-lead author Dr. Kelly Michaelsen, an assistant professor of anesthesiology and pain medicine at the University of Washington School of Medicine.
“The thought of being able to help patients in real time or to prevent a medication error before it happens is very powerful,” she said. “One can hope for a 100% performance but even humans cannot achieve that. In a survey of more than 100 anesthesia providers, the majority desired the system to be more than 95% accurate, which is a goal we achieved.”
Drug administration errors are the most frequently reported critical incidents in anesthesia, and the most common cause of serious medical errors in intensive care. In the bigger picture, an estimated 5% to 10% of all drugs given are associated with errors. Adverse events associated with injectable medications are estimated to affect 1.2 million patients annually at a cost of $5.1 billion.
https://www.nature.com/articles/s41746-024-01295-2
