Analysis of Uncertain Situations in Operating Rooms
Operating rooms are one of the most complex clinical environments, and errors during surgeries can negatively impact patient outcomes, such as longer hospital stay and fatality rate. Existing analysis of surgical performance focuses heavily on adverse events reported after the surgery. This project leverages the capability of the OR Black Box, which is a platform that can collect video, audio, vital signs, and laparoscopic view of the patient during laparoscopic surgeries. By utilizing the surgical recordings, this project sought to identify transitions from routine work to uncertain situations where the surgical team may be unclear about the current situation, the best choices, and future outcomes of the surgery. We would like to gain a deeper understanding of both the causes of uncertainties and the resilience factors (e.g., technological, environmental, technical skills, and non-technical skills) that allowed clinicians to appropriately and quickly respond.
One of the main challenges of conducting the analysis of surgical videos is the fact that manual review of the OR Black Box® videos is extremely time consuming which delays the feedback sent to the surgical team. Thus, the second aim of the project was to improve the analysis efficiency by applying machine learning algorithms to identify the transition from routine work to uncertain situations.
One of the main challenges of conducting the analysis of surgical videos is the fact that manual review of the OR Black Box® videos is extremely time consuming which delays the feedback sent to the surgical team. Thus, the second aim of the project was to improve the analysis efficiency by applying machine learning algorithms to identify the transition from routine work to uncertain situations.
My Roles
I was primarily involved with the first aim of the project. My specific accomplishments are described below:
- Established the patient research protocol and obtained research ethics approval for the project to study patient safety in operating rooms. The protocol details processes related to patient consent, participant recruitment, and information flow across several departments.
- Collaborated and coordinated with clinicians, researchers, information services, administration, and external vendors
- Recruited patient and clinician participants
- Conducted literature review to define and scope the problem as well as to explore existing approaches
- Iteratively designed a data analysis framework for uncertain situations during laparoscopic surgeries by collaborating with human factors experts, surgeons, and surgical video analysts
- Conducted surgical video analysis to understand supporting and hindering factors (e.g. technological and environmental) related to surgery performance
- Coached students in conducting literature review and video analysis
News
Collaborators
- Bijan Dastgheib – St. Michael’s Hospital
- Mark Fan – North York General Hospital
- Alistair Forsyth – North York General Hospital
- Teodor Grantcharov – St. Michael’s Hospital, Surgical Safety Technologies
- Usmaan Hameed – North York General Hospital
- Darryl Irwin – North York General Hospital
- Donna McRitchie – North York General Hospital
- Sonia Pinkney – University of Toronto
- Adrian Ragobar – North York General Hospital
- Michell Richardson – North York General Hospital
- Lloyd Smith – North York General Hospital
- Patricia Trbovich – University of Toronto, North York General Hospital
- Julie Zen – North York General Hospital
Acknowledgement
This project was funded through Ontario Centres of Excellence VIP I + NSERC Engage and Steinberg Fund at the North York General Hospital with support from the Surgical Safety Technologies. This work was completed as part of my postdoctoral fellowship funded through the Health System Impact Fellowship sponsored by Canadian Institutes of Health Research.