Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

Operating rooms present one of the most complex, high-risk situations in clinical settings, and the Operating Room Black Boxx000D
system seeks to enable the analysis of surgical procedures to improve patient safety. The Black Box is a device that recordsx000D
audio, video, environmental, and biometric data within the operating room during a surgical case. This information can be used forx000D
surgical safety improvement. For example, retrospectively, analyzing this data can enable researchers to understand the origin ofx000D
an adverse event. Prospectively, it can allow for the identification of intraoperative factors that potentially risk or enhance patientx000D
safety. Currently, deriving such insight from the Black Box data is labour intensive, requiring significant amount of time and manualx000D
effort in reviewing recordings. Thus, we aim to improve the efficiency and effectiveness of Black Box analysis by automating thex000D
detection of interested segments within Black Box recordings, specifically episodic uncertainty. Episodic uncertainty is a statex000D
experienced by individuals or teams during abnormal situations that may lead to adverse events if not managed correctly.x000D
Research will first be conducted to uncover the association between recorded data and observed instances of episodicx000D
uncertainties. Machine learning techniques informed by the correlation will be developed to process Black Box data and identifyx000D
instances of episodic uncertainty. Such detection capability in Black Box will decrease the resource demands associated with datax000D
analysis, expand its availability to more hospitals, expedite the identification of uncertainty during patient care, and enable rapidx000D
improvements and higher quality management in patient safety.