Every day, a person dies due to receiving the wrong medication or incorrect dosages of the correct drug. Now, researchers at the University of Washington (UW) are exploring solutions to this issue, partly by employing artificial intelligence (AI), NBC News reported Sunday (May 25). Dr. Kelly Michaelsen, an assistant professor of anesthesiology and pain medicine, shared with the network that after reviewing studies on the frequency of medication errors among anesthesiologists, she considered whether AI could aid in detecting these mistakes. “I thought, ‘This seems like something AI should be able to handle easily, ’” she explained. “Ninety-nine percent of the medications we use consist of the same 10-20 drugs, so I envisioned training an AI to recognize them and serve as a second set of eyes. ” Her research focused on vial swap errors, which account for 20% of all medication errors, according to the report. Such errors occur when the wrong vial of an injectable drug is chosen or when the syringe is labeled incorrectly, resulting in the patient receiving the wrong medicine. Michaelsen told NBC she believed these errors could be prevented through the use of “smart eyewear”—integrating an AI-powered wearable camera into the protective glasses all staff wear during surgeries. In collaboration with colleagues from UW’s computer science department, she developed a system capable of scanning the nearby environment for syringe and vial labels, reading them, and verifying their accuracy. The report stated that Michaelsen’s study, which had no funding from AI companies, demonstrated that the device achieved 99. 6% accuracy in detecting vial swap errors. Last year, PYMNTS examined other ways AI can enhance medical outcomes during a discussion with Dr.

Michael Gao, co-founder and CEO of SmarterDx. He highlighted that hospitals in the U. S. spend approximately $500 billion annually on administrative costs. This is largely due to traditional hospital billing systems requiring numerous healthcare personnel, including nurses and medical coders, whose primary role is to verify and translate clinical notes into billing codes.