Automated performance metrics, learning curve and robotic colorectal surgery

被引:0
|
作者
Wong, Shing Wai [1 ,2 ]
Crowe, Philip [1 ,2 ]
机构
[1] Prince Wales Hosp, Dept Gen Surg, Sydney, NSW, Australia
[2] Univ New South Wales, Sch Clin Med, Randwick Campus, Sydney, NSW, Australia
关键词
automated performance metrics; learning curve; robotic colorectal surgery; system event data; GLOBAL EVALUATIVE ASSESSMENT; VALIDATION; SKILLS;
D O I
10.1002/rcs.2588
中图分类号
R61 [外科手术学];
学科分类号
摘要
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.
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页数:9
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