Smart Eyewear to Automatically Detect Drug Delivery Events

Detailed Summary: The goal of this study is to devise a high-fidelity system that automatically collects data about anesthesia care, specifically drug preparation and delivery to the patient. We use a novel wearable data input device that collects computer processed images (video only, no audio) to determine details of the preparation and delivery of medications in the operating room. The wearable data input device is used by an anesthesia provider. The device collects computer processed images and in the anesthesia workspace, which will be used to develop machine learning algorithms that can automatically recognize drug administration events in order to automate medical record keeping in this environment.

Procedure: The principle investigator or a study coordinator will review the electronic operating room schedule to screen for potential data collection. The operating room team will be notified of the study the day prior to and day of data collection. The consented anesthesia provider will wear a point of view device to record drug preparation and drug delivery events in the operating room. Video recordings will be edited to remove Protected Health Information (PHI). Edited footage will then be annotated by volunteers on a computer vision learning tool website. The computer processed images will be then used to develop machine learning algorithms that can automatically recognize drug administration events.

Participants: The initial recruitment goal for the study is 10 nurse anesthetists recording 5 days each in the operating room. Nurse anesthetists are recruited as participants through word of mouth. If determined after data analysis that additional data needs to collected, additional anesthesia providers will be consented.

Inclusion criteria

• Anesthesia providers (attending anesthesiologist or certified registered nurse anesthetist) who work in an operating room at University of Washington Montlake Medical Center

Exclusion criteria

• Medical students and anesthesiology residents