Automated performance metrics, learning curve and robotic colorectal surgery

IF 2.3 3区医学 Q2 SURGERY

International Journal of Medical Robotics and Computer Assisted Surgery Pub Date : 2023-10-19 DOI:10.1002/rcs.2588

Shing Wai Wong, Philip Crowe

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Abstract

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.

Abstract Image

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自动化性能指标、学习曲线和机器人结直肠手术。

背景：本研究的目的是评估自动化绩效指标（APM）在评估学习曲线方面的有用性。方法：对2020年8月至2022年10月期间在一家机构接受全机器人结直肠手术的85名连续患者进行回顾性审查。收集并分析患者的人口统计数据、手术类型和APM。累积求和技术（CUSUM）用于构建外科医生控制台时间（SCT）、第四臂的使用、离合器激活、仪器屏幕外（数量和持续时间）和切割电烙器激活的学习曲线。结果：从SCT的CUSUM图中可以识别出两个阶段，分别为50例和35例。SCT在两个阶段之间有显著差异（176和251分钟，p结论：与单独的SCT分析相比，大多数APM没有提供额外的学习曲线信息。

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来源期刊

International Journal of Medical Robotics and Computer Assisted Surgery 医学-外科

CiteScore

4.50

自引率

12.00%

发文量

131

审稿时长

6-12 weeks

期刊介绍： The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.