Related Experiment Video
Updated: Jul 12, 2025
Robotics in Surgery: A Modular Robotic Platform Driven Gastric Wedge Resection
Published on: February 7, 2025
Automated performance metrics, learning curve and robotic colorectal surgery
Shing Wai Wong1,2, Philip Crowe1,2
1Department of General Surgery, Prince of Wales Hospital, Sydney, New South Wales, Australia.
Background:
The aim of this study was to evaluate the usefulness of Automated Performance Metrics (APMs) in assessing the learning curve.
Methods:
A retrospective review of 85 consecutive patients who underwent total robotic colorectal surgery at a single institution between August 2020 and October 2022 was performed. Patient demographics, operation type, and APMs were collected and analysed. Cumulative summation technique (CUSUM) was used to construct learning curves of surgeon console time (SCT), use of the fourth arm, clutch activation, instrument off screen (number and duration), and cut electrocautery activation.
Results:
Two phases with 50 and 35 cases were identified from the CUSUM graph for SCT. The SCT was significantly different between the two phases (176 and 251 min, p < 0.002). After adjustment for SCT, the APMs were not significantly different between the two phases.
Conclusions:
Most APMs do not offer additional learning curve information when compared with SCT analysis alone.
