Detecting clinical medication errors with AI enabled wearable cameras (22 October 2024)

Summary

Drug-related errors are a leading cause of preventable patient harm in the clinical setting. Chan et al. present the first wearable camera system to automatically detect potential errors, prior to medication delivery.

The authors demonstrate that using deep learning algorithms, the system can detect and classify drug labels on syringes and vials in drug preparation events recorded in real-world operating rooms. They created a first-of-its-kind large-scale video dataset from head-mounted cameras comprising 4K footage across 13 anaesthesiology providers, 2 hospitals and 17 operating rooms over 55 days.

The system was evaluated on 418 drug draw events in routine patient care and a controlled environment and achieved 99.6% sensitivity and 98.8% specificity at detecting vial swap errors. These results suggest that the wearable camera system has the potential to provide a secondary check when a medication is selected for a patient, and a chance to intervene before a potential medical error.