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

Nir Messer , Eran Nizri , Guy Lahat , Amir Szold

Artificial Intelligence Surgery ›› 2025, Vol. 5 ›› Issue (2) : 191 -9.

PDF
Artificial Intelligence Surgery ›› 2025, Vol. 5 ›› Issue (2) :191 -9. DOI: 10.20517/ais.2024.93
Original Article

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

Author information +
History +
PDF

Abstract

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.

Keywords

Artificial intelligence (AI) / video management / minimally invasive surgery (MIS) / self-assessment / surgical key steps

Cite this article

Download citation ▾
Nir Messer, Eran Nizri, Guy Lahat, Amir Szold. Implementing an AI-powered endoscopic surgery video recording system in a large hospital network: lessons learned and future prospects. Artificial Intelligence Surgery, 2025, 5(2): 191-9 DOI:10.20517/ais.2024.93

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Stolarski A,Sell N.Mentoring experience of new surgeons during their transition to independent practice: a nationwide survey.Surgery2021;169:1354-60

[2]

Apramian T,Sener A.How do thresholds of principle and preference influence surgeon assessments of learner performance?.Ann Surg2018;268:385-90 PMCID:PMC5711515

[3]

Ahmed K,Darzi A,Hanna GB.Observational tools for assessment of procedural skills: a systematic review.Am J Surg2011;202:469-80.e6

[4]

Gawad N,Mimeault R.The inter-rater reliability of technical skills assessment and retention of rater training.J Surg Educ2019;76:1088-93

[5]

Kramp KH,Hoff C,Veeger NJ.Validity and reliability of global operative assessment of laparoscopic skills (GOALS) in novice trainees performing a laparoscopic cholecystectomy.J Surg Educ2015;72:351-8

[6]

Grüter AAJ,van Oostendorp SE.Video-based tools for surgical quality assessment of technical skills in laparoscopic procedures: a systematic review.Surg Endosc2023;37:4279-97 PMCID:PMC10234871

[7]

Alibhai KM,Gawad N,Raîche I.Assessment of laparoscopic skills: comparing the reliability of global rating and entrustability tools.Can Med Educ J2022;13:36-45 PMCID:PMC9684047

[8]

Claus C,Malcher F,Felix E.Ten golden rules for a safe MIS inguinal hernia repair using a new anatomical concept as a guide.Surg Endosc2020;34:1458-64

[9]

Adrales G,Chowbey P.Laparoscopic cholecystectomy critical view of safety (LC-CVS): a multi-national validation study of an objective, procedure-specific assessment using video-based assessment (VBA).Surg Endosc2024;38:922-30

[10]

Lam T,Chan ST.Are we getting the critical view?.HPB2014;16:859-63 PMCID:PMC4159460

[11]

Kowalewski KF,Schmidt MW,Müller-Stich BP.Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying.Surg Endosc2019;33:3732-40

[12]

Baghdadi A,Ahmed Y,Guru KA.A computer vision technique for automated assessment of surgical performance using surgeons’ console-feed videos.Int J Comput Assist Radiol Surg2019;14:697-707

[13]

Ganni S,Chmarra M,Goossens RHM.Validation of motion tracking software for evaluation of surgical performance in laparoscopic cholecystectomy.J Med Syst2020;44:56 PMCID:PMC6981315

[14]

Bar O,Zohar M.Impact of data on generalization of AI for surgical intelligence applications.Sci Rep2020;10:22208 PMCID:PMC7747564

[15]

Korndorffer JR Jr,Spain DA.Situating artificial intelligence in surgery: a focus on disease severity.Ann Surg2020;272:523-8

[16]

Ortenzi M,Antolin A.A novel high accuracy model for automatic surgical workflow recognition using artificial intelligence in laparoscopic totally extraperitoneal inguinal hernia repair (TEP).Surg Endosc2023;37:8818-28 PMCID:PMC10615930

[17]

Khanna A,Bar O.Automated identification of key steps in robotic-assisted radical prostatectomy using artificial intelligence.J Urol2024;211:575-84

[18]

Deol ES,Antolin A.Automated surgical step recognition in transurethral bladder tumor resection using artificial intelligence: transfer learning across surgical modalities.Front Artif Intell2024;7:1375482 PMCID:PMC10958784

[19]

Levin I,Bar O,Cohen A.Introducing surgical intelligence in gynecology: automated identification of key steps in hysterectomy.Int J Gynaecol Obstet2024;166:1273-8

[20]

Fried GM,Dayan D.Surgical intelligence can lead to higher adoption of best practices in minimally invasive surgery.Ann Surg2024;280:525-34

[21]

Chou E,Shamim Khan M,Ahmed K.Should surgical outcomes be published?.J R Soc Med2015;108:127-35 PMCID:PMC4406890

[22]

Bresnick SD.Highly publicized litigation against doctors: how plastic surgeons should protect themselves and their patients.Aesthet Surg J2023;43:NP297-9

[23]

Green A,Young HL.Stress in surgeons.Br J Surg1990;77:1154-8

PDF

340

Accesses

0

Citation

Detail

Sections
Recommended

/