We’ve all heard of black boxes that are used to determine what went wrong in commercial airline disasters – but did you know that there are also black boxes that can be used to identify errors in the operating room (OR)? With a new four-year, $1.6 million grant from the federal Agency for Healthcare Research and Quality, Division of Endocrine Surgery Associate Professor Courtney Balentine, MD, MPH and University of Texas (UT) Southwestern Associate Professor of Surgery and Biomedical Engineering Ganesh Sankaranarayanan, PhD, will test how the Operating Room Black Box® (ORBB) could be used to help reduce errors that occur in the OR.
“ORBBs can identify things that happen during surgeries that contribute to complications. Our grant aims to use information captured by the ORBB to develop targeted simulation training to reduce intraoperative errors, improve safety, and enhance patient recovery from surgery. We also plan to study how the ORBB technology can be more efficiently implemented across hospital systems so that more institutions can use it to improve quality and safety,” said Balentine.
In 2020, UT Southwestern’s Clements University Hospital was one of the first hospitals in the U.S. to implement the use of ORBBs when they installed them in five of their ORs. The system captures audio, video, and patient physiological data from the OR, and it also links to the medical record to gather information about how the patient does after surgery. The data captured from UT Southwestern’s first 5 ORBBs was successfully used in several quality improvement projects. They have since expanded the program to include the devices in all 37 of their ORs, making UT Southwestern well-suited to test the effects of scaling up ORBB programs and determining how best to use the data to reduce surgical errors and improve patient outcomes.
Sankaranarayanan and Balentine will now be co-leading a project team that will use the data generated by UT Southwestern’s ORBBs to develop a virtual simulation-based training.
“The simulation training will be interactive, multiplayer, and immersive, and it will include virtual debriefing for training on surgical safety checklists and timeouts, which are key tools in decreasing surgical errors,” said Sankaranarayanan. “In addition, we’ll apply machine learning algorithms to ORBB data so we can adaptively generate training scenarios and automatically observe improvement in performance. In other words, the simulation will use real-life scenarios from the OR to challenge and train the surgical team.”
After developing the training and establishing its validity, Sankaranarayanan and Balentine will pilot test it with surgical teams at UT Southwestern and determine whether the simulation can improve team performance in the OR. They’ll also gather information about potential barriers to implementing ORBBs and the simulation training more broadly. Ultimately, the team’s goal is to develop innovative ways that ORBB data can be used to improve the quality of surgical care and the safety of the OR for our patients.