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

Abstract

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.

Quantification of surgical workflow during robotic proctectomy

“…Through step segmentation, OPIs have enabled objective step‐specific feedback to provide insights into surgical workflow, procedure complexity, surgeon skill and surgical outcomes 12–14 . Although there is no universally accepted annotation card for robotic proctectomy (RP), we have identified 21 steps during RP, and have previously published regarding our annotation process 9 …”

“…Machine learning‐enabled metrics, objective performance indicators (OPIs) , can be captured from surgical video and robotic system data. OPIs include measurements of surgeon console actions (hand, wrist and foot movements, clutching, energy use, arm swaps) and patient cart activity (camera movements, instrument path length, travel time, velocity, acceleration, jerk), as well as other calculated indices (economy of motion, smoothness, workspace volume) 7–9 . A specific OPI, step duration , enables accurate time‐stamping of critical steps within a given procedure and provides a tool to evaluate surgical workflow and its variability across cases.…”

“…OPIs include measurements of surgeon console actions (hand, wrist and foot movements, clutching, energy use, arm swaps) and patient cart activity (camera movements, instrument path length, travel time, velocity, acceleration, jerk), as well as other calculated indices (economy of motion, smoothness, workspace volume). [7][8][9] A specific OPI, step duration, enables accurate time-stamping of critical steps within a given procedure and provides a tool to evaluate surgical workflow and its variability across cases. A prerequisite for step-specific analyses is the ability to annotate surgical videos so as to identify discrete, functionally relevant surgical steps.…”

“…[12][13][14] Although there is no universally accepted annotation card for robotic proctectomy (RP), we have identified 21 steps during RP, and have previously published regarding our annotation process. 9 In this study, we objectively describe step-specific workflow and transitions within RP. Additionally, we identify critical steps that highly correlate with CT and TOT, as well as steps more likely to be convergent (varied steps precede, but few follow), divergent (few steps precede, but varied follow), or nodal (varied steps precede and follow), providing novel insights into workflow variabilities of RP.…”

Quantification of Surgical Workflow during Robotic Proctectomy

“…Machine learning-enabled metrics, objective performance indicators (OPIs), can be captured from surgical video and robotic system data. OPIs include measurements of surgeon console actions (hand, wrist and foot movements, clutching, energy use, arm swaps) and patient cart activity (camera movements, instrument path length, travel time, velocity, acceleration, jerk), as well as other calculated indices (economy of motion, smoothness, workspace volume) [7][8][9]. A speci c OPI, step duration, enables accurate time-stamping of critical steps within a given procedure and provides a tool to evaluate surgical work ow and its variability across cases.…”