Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins Hospital, Baltimore, Maryland 21218, USA.
Laryngoscope. 2012 Oct;122(10):2184-92. doi: 10.1002/lary.23369. Epub 2012 Aug 22.
OBJECTIVES/HYPOTHESIS: To develop a robotic surgery training regimen integrating objective skill assessment for otolaryngology and head and neck surgery trainees consisting of training modules of increasing complexity leading up to procedure-specific training. In particular, we investigated applications of such a training approach for surgical extirpation of oropharyngeal tumors via a transoral approach using the da Vinci robotic system.
Prospective blinded data collection and objective evaluation (Objective Structured Assessment of Technical Skills [OSATS]) of three distinct phases using the da Vinci robotic surgical system in an academic university medical engineering/computer science laboratory setting.
Between September 2010 and July 2011, eight otolaryngology-head and neck surgery residents and four staff experts from an academic hospital participated in three distinct phases of robotic surgery training involving 1) robotic platform operational skills, 2) set up of the patient side system, and 3) a complete ex vivo surgical extirpation of an oropharyngeal tumor located in the base of tongue. Trainees performed multiple (four) approximately equally spaced training sessions in each stage of the training. In addition to trainees, baseline performance data were obtained for the experts. Each surgical stage was documented with motion and event data captured from the application programming interfaces of the da Vinci system, as well as separate video cameras as appropriate. All data were assessed using automated skill measures of task efficiency and correlated with structured assessment (OSATS and similar Likert scale) from three experts to assess expert and trainee differences and compute automated and expert assessed learning curves.
Our data show that such training results in an improved didactic robotic knowledge base and improved clinical efficiency with respect to the set up and console manipulation. Experts (e.g., average OSATS, 25; standard deviation [SD], 3.1; module 1, suturing) and trainees (average OSATS, 15.9; SD, 3.9; week 1) are well separated at the beginning of the training, and the separation reduces significantly (expert average OSATS, 27.6; SD, 2.7; trainee average OSATS, 24.2; SD, 6.8; module 3) at the conclusion of the training. Learning curves in each of the three stages show diminishing differences between the experts and trainees, which is also consistent with expert assessment. Subjective assessment by experts verified the clinical utility of the module 3 surgical environment, and a survey of trainees consistently rated the curriculum as very useful in progression to human operating room assistance.
Structured curricular robotic surgery training with objective assessment promises to reduce the overhead for mentors, allow detailed assessment of human-machine interface skills, and create customized training models for individualized training. This preliminary study verifies the utility of such training in improving human-machine operations skills (module 1), and operating room and surgical skills (modules 2 and 3). In contrast to current coarse measures of total operating time and subjective assessment of error for short mass training sessions, these methods may allow individual tasks to be removed from the trainee regimen when skill levels are within the standard deviation of the experts for these tasks, which can greatly enhance overall efficiency of the training regimen and allow time for additional and more complex training to be incorporated in the same time frame.
目的/假设:开发一种机器人手术培训方案,将耳鼻喉头颈外科受训者的客观技能评估与越来越复杂的培训模块相结合,最终达到特定手术的培训。特别是,我们研究了这种培训方法在使用达芬奇机器人系统经口途径切除口咽肿瘤手术中的应用。
在学术大学医学工程/计算机科学实验室环境中,使用达芬奇机器人手术系统进行前瞻性盲数据收集和客观评估(客观结构化评估技术技能[OSATS]),共分为三个不同阶段。
2010 年 9 月至 2011 年 7 月,8 名耳鼻喉头颈外科住院医师和 4 名来自学术医院的专家参加了三个不同阶段的机器人手术培训,包括 1)机器人平台操作技能,2)患者侧系统设置,和 3)在舌根基底位置完整切除口咽肿瘤的离体手术。学员在每个阶段都进行了多次(4 次)大约相等间隔的培训。除了学员外,基线表现数据也获得了专家的数据。每个手术阶段都记录了达芬奇系统应用编程接口捕获的运动和事件数据,以及适当的单独摄像机。所有数据均使用任务效率的自动技能测量值进行评估,并与三位专家的结构化评估(OSATS 和类似的李克特量表)相关联,以评估专家和学员之间的差异,并计算自动和专家评估的学习曲线。
我们的数据表明,这种培训可提高机器人教学基础,并提高与设置和控制台操作相关的临床效率。专家(例如,平均 OSATS,25;标准差[SD],3.1;模块 1,缝合)和学员(平均 OSATS,15.9;SD,3.9;第 1 周)在培训开始时差异明显,培训结束时差异显著减少(专家平均 OSATS,27.6;SD,2.7;学员平均 OSATS,24.2;SD,6.8;模块 3)。三个阶段中的每个学习曲线都显示出专家和学员之间的差异逐渐缩小,这也与专家评估一致。专家的主观评估验证了模块 3 手术环境的临床实用性,学员的调查一致认为该课程非常有助于他们进入人类手术室辅助阶段。
有客观评估的结构化机器人手术培训有望减少导师的工作量,允许详细评估人机界面技能,并为个性化培训创建定制的培训模型。这项初步研究验证了这种培训在提高人机操作技能(模块 1)和手术室及手术技能(模块 2 和 3)方面的实用性。与目前短期大量培训课程中总操作时间的粗略测量和对错误的主观评估相比,这些方法可以在学员的技能水平达到这些任务的专家标准差范围内时,将个别任务从学员的培训方案中删除,这可以大大提高培训方案的整体效率,并允许在相同的时间框架内纳入更多和更复杂的培训。