IMPORTANCE Assessing nontechnical skills in operating rooms (ORs) is crucial for enhancing surgical performance and patient safety. However, automated and real-time evaluation of these skills remains challenging. OBJECTIVE To explore the feasibility of using motion features extracted from surgical video recordings to automatically assess nontechnical skills during cardiac surgical procedures. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study used video recordings of cardiac surgical procedures at a tertiary academic US hospital collected from January 2021 through May 2022. The OpenPose library was used to analyze videos to extract body pose estimations of team members and compute various team motion features. The Non-Technical Skills for Surgeons (NOTSS) assessment tool was employed for rating the OR team's nontechnical skills by 3 expert raters. MAIN OUTCOMES AND MEASURES NOTSS overall score, with motion features extracted from surgical videos as measures. RESULTS A total of 30 complete cardiac surgery procedures were included: 26 (86.6%) were on-pump coronary artery bypass graft procedures and 4 (13.4%) were aortic valve replacement or repair procedures. All patients were male, and the mean (SD) age was 72 (6.3) years. All surgical teams were composed of 4 key roles (attending surgeon, attending anesthesiologist, primary perfusionist, and scrub nurse) with additional supporting roles. NOTSS scores correlated significantly with trajectory (r = 0.51, P = .005), acceleration (r = 0.48, P = .008), and entropy (r = -0.52, P = .004) of team displacement. Multiple linear regression, adjusted for patient factors, showed average team trajectory (adjusted R-2 = 0.335; coefficient, 10.51 [95% CI, 8.81-12.21]; P = .004) and team displacement entropy (adjusted R-2 = 0.304; coefficient, -12.64 [95% CI, -20.54 to -4.74]; P = .003) were associated with NOTSS scores. CONCLUSIONS AND RELEVANCE This study suggests a significant link between OR team movements and nontechnical skills ratings by NOTSS during cardiac surgical procedures, suggesting automated surgical video analysis could enhance nontechnical skills assessment. Further investigation across different hospitals and specialties is necessary to validate these findings.

Deep Learning Analysis of Surgical Video Recordings to Assess Nontechnical Skills / Harari, Rayan Ebnali; Dias, Roger D.; Kennedy-Metz, Lauren R.; Varni, Giovanna; Gombolay, Matthew; Yule, Steven; Salas, Eduardo; Zenati, Marco A.. - In: JAMA NETWORK OPEN. - ISSN 2574-3805. - 7:7(2024). [10.1001/jamanetworkopen.2024.22520]

Deep Learning Analysis of Surgical Video Recordings to Assess Nontechnical Skills

Varni, Giovanna;
2024-01-01

Abstract

IMPORTANCE Assessing nontechnical skills in operating rooms (ORs) is crucial for enhancing surgical performance and patient safety. However, automated and real-time evaluation of these skills remains challenging. OBJECTIVE To explore the feasibility of using motion features extracted from surgical video recordings to automatically assess nontechnical skills during cardiac surgical procedures. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study used video recordings of cardiac surgical procedures at a tertiary academic US hospital collected from January 2021 through May 2022. The OpenPose library was used to analyze videos to extract body pose estimations of team members and compute various team motion features. The Non-Technical Skills for Surgeons (NOTSS) assessment tool was employed for rating the OR team's nontechnical skills by 3 expert raters. MAIN OUTCOMES AND MEASURES NOTSS overall score, with motion features extracted from surgical videos as measures. RESULTS A total of 30 complete cardiac surgery procedures were included: 26 (86.6%) were on-pump coronary artery bypass graft procedures and 4 (13.4%) were aortic valve replacement or repair procedures. All patients were male, and the mean (SD) age was 72 (6.3) years. All surgical teams were composed of 4 key roles (attending surgeon, attending anesthesiologist, primary perfusionist, and scrub nurse) with additional supporting roles. NOTSS scores correlated significantly with trajectory (r = 0.51, P = .005), acceleration (r = 0.48, P = .008), and entropy (r = -0.52, P = .004) of team displacement. Multiple linear regression, adjusted for patient factors, showed average team trajectory (adjusted R-2 = 0.335; coefficient, 10.51 [95% CI, 8.81-12.21]; P = .004) and team displacement entropy (adjusted R-2 = 0.304; coefficient, -12.64 [95% CI, -20.54 to -4.74]; P = .003) were associated with NOTSS scores. CONCLUSIONS AND RELEVANCE This study suggests a significant link between OR team movements and nontechnical skills ratings by NOTSS during cardiac surgical procedures, suggesting automated surgical video analysis could enhance nontechnical skills assessment. Further investigation across different hospitals and specialties is necessary to validate these findings.
2024
7
Harari, Rayan Ebnali; Dias, Roger D.; Kennedy-Metz, Lauren R.; Varni, Giovanna; Gombolay, Matthew; Yule, Steven; Salas, Eduardo; Zenati, Marco A....espandi
Deep Learning Analysis of Surgical Video Recordings to Assess Nontechnical Skills / Harari, Rayan Ebnali; Dias, Roger D.; Kennedy-Metz, Lauren R.; Varni, Giovanna; Gombolay, Matthew; Yule, Steven; Salas, Eduardo; Zenati, Marco A.. - In: JAMA NETWORK OPEN. - ISSN 2574-3805. - 7:7(2024). [10.1001/jamanetworkopen.2024.22520]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/437036
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