跨专业基于模拟的基础机器人手术技能培训课程的设计与验证。
Design and validation of a cross-specialty simulation-based training course in basic robotic surgical skills.
机构信息
Department of Otorhinolaryngology, Head & Neck Surgery and Audiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Department of Gynaecology, Endometriosis Team and Robotic Surgery Section, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
出版信息
Int J Med Robot. 2020 Oct;16(5):1-10. doi: 10.1002/rcs.2138. Epub 2020 Aug 19.
BACKGROUND
The aim of this study was to design and validate a cross-specialty basic robotic surgical skills training program on the RobotiX Mentor virtual reality simulator.
METHODS
A Delphi panel reached consensus on six modules to include in the training program. Validity evidence was collected according to Messick's framework with three performances in each simulator module by 11 experienced robotic surgeons and 11 residents without robotic surgical experience.
RESULTS
For five of the six modules, a compound metrics-based score could significantly discriminate between the performances of novices and experienced robotic surgeons. Pass/fail levels were established, resulting in very few novices passing in their first attempt.
CONCLUSIONS
This validated course can be used for structured simulation-based basic robotic surgical skills training within a mastery learning framework where the individual trainee can practice each module until they achieve proficiency and can continue training on other modalities and more specific to their specialty.
背景
本研究旨在设计并验证一项跨专业基本机器人手术技能培训计划，该计划将在 RobotiX Mentor 虚拟现实模拟器上进行。
方法
德尔菲小组就纳入培训计划的六个模块达成了共识。根据 Messick 的框架，通过 11 名经验丰富的机器人外科医生和 11 名没有机器人手术经验的住院医师在每个模拟器模块中的三次表现，收集了有效性证据。
结果
对于六个模块中的五个模块，基于复合指标的分数可以显著区分新手和经验丰富的机器人外科医生的表现。建立了通过/失败的标准，导致很少有新手在第一次尝试时通过。
结论
本经过验证的课程可用于基于掌握学习框架的结构化模拟基本机器人手术技能培训，在此框架下，个体受训者可以练习每个模块，直到达到熟练程度，并且可以继续在其他模式和更具体的专业领域进行培训。
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