Deep Learning Analysis of Surgical Video Recordings to Assess Nontechnical Skills.


Journal

JAMA network open
ISSN: 2574-3805
Titre abrégé: JAMA Netw Open
Pays: United States
ID NLM: 101729235

Informations de publication

Date de publication:
01 Jul 2024
Historique:
medline: 31 7 2024
pubmed: 31 7 2024
entrez: 31 7 2024
Statut: epublish

Résumé

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. To explore the feasibility of using motion features extracted from surgical video recordings to automatically assess nontechnical skills during cardiac surgical procedures. 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. NOTSS overall score, with motion features extracted from surgical videos as measures. 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 R2 = 0.335; coefficient, 10.51 [95% CI, 8.81-12.21]; P = .004) and team displacement entropy (adjusted R2 = 0.304; coefficient, -12.64 [95% CI, -20.54 to -4.74]; P = .003) were associated with NOTSS scores. 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.

Identifiants

pubmed: 39083274
pii: 2821697
doi: 10.1001/jamanetworkopen.2024.22520
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2422520

Auteurs

Rayan Ebnali Harari (RE)

Mass General Brigham, Harvard Medical School, Boston, Massachusetts.

Roger D Dias (RD)

Mass General Brigham, Harvard Medical School, Boston, Massachusetts.

Lauren R Kennedy-Metz (LR)

Department of Psychology, Roanoke College, Salem, Virginia.

Giovanna Varni (G)

Department of Information Engineering and Computer Science, University of Trento, Trento, Italy.

Matthew Gombolay (M)

School of Interactive Computing, Georgia Institute of Technology, Atlanta.

Steven Yule (S)

Department of Clinical Surgery, University of Edinburgh, Edinburgh, United Kingdom.

Eduardo Salas (E)

Department of Psychological Sciences, Rice University, Houston, Texas.

Marco A Zenati (MA)

Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
VA Boston Healthcare System, West Roxbury, Massachusetts.

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Classifications MeSH