Implementing an AI-powered endoscopic surgery video recording system in a large hospital network: lessons learned and future prospects

Aim: Traditional methods of evaluating surgical performance, such as self-assessment and peer review, are limited by bias and inconsistency. Recent advances in artificial intelligence (AI) have introduced novel tools for objective evaluation of surgical techniques. This study reports the implementation of an AI-powered video management system across four surgical centers and its impact on the documentation, analysis, and standardization of minimally invasive surgeries (MIS). Methods: A retrospective analysis was conducted of all MIS procedures performed at four centers within Assuta Medical Centers between July 2023 and June 2024. The AI system (TheatorTM, Inc.) is integrated with endoscopic cameras to automatically document, store, and analyze surgeries in real time, focusing on key intraoperative steps. Performance metrics, including the achievement of key surgical steps, were recorded. Rates of surgeon engagement in self-assessment and postoperative reviews were also evaluated. Results: A total of 11,080 MIS procedures were performed, with 96.7% (10,725) documented by the AI system. The most frequently performed procedures were laparoscopic inguinal hernia repair (36.6%), gastric bypass (22.7%), and cholecystectomy (19.9%). The Critical View of Safety (CVS) was achieved in 60.6% of cholecystectomies, with inter-center variability ranging from 14% to 70%. Surgeon self-assessment was conducted in 22.2% of documented cases. Conclusion: The implementation of an AI-powered video management system facilitated comprehensive surgical documentation and analysis, supporting both the standardization of surgical key steps and surgeon self-assessment. This system holds promise for improving surgical performance and safety through enhanced feedback and data-driven practice improvements.