Automated analysis of operative video in surgical training: scoping review

Abstract

Background: There is increasing availability of operative video for use in surgical training. Emerging technologies can now assess video footage and automatically generate metrics that could be harnessed to improve the assessment of operative performance. However, a comprehensive understanding of which technology features are most impactful in surgical training is lacking. The aim of this scoping review was to explore the current use of automated video analytics in surgical training.

Methods: PubMed, Scopus, the Web of Science, and the Cochrane database were searched, to 29 September 2023, following PRISMA extension for scoping reviews (PRISMA-ScR) guidelines. Search terms included 'trainee', 'video analytics', and 'education'. Articles were screened independently by two reviewers to identify studies that applied automated video analytics to trainee-performed operations. Data on the methods of analysis, metrics generated, and application to training were extracted.

Results: Of the 6736 articles screened, 13 studies were identified. Computer vision tracking was the common method of video analysis. Metrics were described for processes (for example movement of instruments), outcomes (for example intraoperative phase duration), and critical safety elements (for example critical view of safety in laparoscopic cholecystectomy). Automated metrics were able to differentiate between skill levels (for example consultant versus trainee) and correlated with traditional methods of assessment. There was a lack of longitudinal application to training and only one qualitative study reported the experience of trainees using automated video analytics.

Conclusion: The performance metrics generated from automated video analysis are varied and encompass several domains. Validation of analysis techniques and the metrics generated are a priority for future research, after which evidence demonstrating the impact on training can be established.