Details

Autor(en) / Beteiligte

• Devin, Courtney L.
• Gillani, Mishal
• Shields, Mallory C.
• Eldredge, Kyle
• Kucera, Walter
• Rupji, Manali
• Purvis, Lilia A.
• Paul Olson, Terrah Jean
• Liu, Yuan
• Jarc, Anthony
• Rosen, Seth A.

Titel

Ratio of Economy of Motion: A New Objective Performance Indicator to Assign Consoles During Dual-Console Robotic Proctectomy

Ist Teil von

• The American surgeon, 2023-08, Vol.89 (8), p.3416-3422

Ort / Verlag

Los Angeles, CA: SAGE Publications

Erscheinungsjahr

2023

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Background Our group investigates objective performance indicators (OPIs) to analyze robotic colorectal surgery. Analyses of OPI data are difficult in dual-console procedures (DCPs) as there is currently no reliable, efficient, or scalable technique to assign console-specific OPIs during a DCP. We developed and validated a novel metric to assign tasks to appropriate surgeons during DCPs. Methods A colorectal surgeon and fellow reviewed 21 unedited, dual-console proctectomy videos with no information to identify the operating surgeons. The reviewers watched a small number of random tasks and assigned “attending” or “trainee” to each task. Based on this sampling, the remainder of task assignments for each procedure was extrapolated. In parallel, we applied our newly developed OPI, ratio of economy of motion (rEOM), to assign consoles. Results from the 2 methods were compared. Results A total of 1811 individual surgical tasks were recorded during 21 proctectomy videos. A median of 6.5 random tasks (137 total) were reviewed during each video, and the remainder of task assignments were extrapolated based on the 7.6% of tasks audited. The task assignment agreement was 91.2% for video review vs rEOM, with rEOM providing ground truth. It took 2.5 hours to manually review video and assign tasks. Ratio of economy of motion task assignment was immediately available based on OPI recordings and automated calculation. Discussion We developed and validated rEOM as an accurate, efficient, and scalable OPI to assign individual surgical tasks to appropriate surgeons during DCPs. This new resource will be useful to everyone involved in OPI research across all surgical specialties.