Objective measures for longitudinal assessment of robotic surgery training

Rajesh Kumar, Amod Jog, Balazs Vagvolgyi, Hiep Nguyen, Gregory Hager, Chi Chiung Grace Chen, David Yuh
2012 Journal of Thoracic and Cardiovascular Surgery  
Objectives: Current robotic training approaches lack the criteria for automatically assessing and tracking (over time) technical skills separately from clinical proficiency. We describe the development and validation of a novel automated and objective framework for the assessment of training. Methods: We are able to record all system variables (stereo instrument video, hand and instrument motion, buttons and pedal events) from the da Vinci surgical systems using a portable archival system
more » ... ated with the robotic surgical system. Data can be collected unsupervised, and the archival system does not change system operations in any way. Our open-ended multicenter protocol is collecting surgical skill benchmarking data from 24 trainees to surgical proficiency, subject only to their continued availability. Two independent experts performed structured (objective structured assessment of technical skills) assessments on longitudinal data from 8 novice and 4 expert surgeons to generate baseline data for training and to validate our computerized statistical analysis methods in identifying the ranges of operational and clinical skill measures. Results: Objective differences in operational and technical skill between known experts and other subjects were quantified. The longitudinal learning curves and statistical analysis for trainee performance measures are reported. Graphic representations of the skills developed for feedback to the trainees are also included. Conclusions: We describe an open-ended longitudinal study and automated motion recognition system capable of objectively differentiating between clinical and technical operational skills in robotic surgery. Our results have demonstrated a convergence of trainee skill parameters toward those derived from expert robotic surgeons during the course of our training protocol. (J Thorac Cardiovasc Surg 2012;143:528-34) Minimally invasive cardiothoracic operations have been facilitated by new surgical robotic technologies. Although more than 1700 surgical robotic systems were in clinical use worldwide 1 by mid-2010, the application of robotics to cardiothoracic surgery has not caught up with other surgical disciplines largely because of the steep learning curves in developing operational proficiency with surgical robotic platforms, 2,3 coupled with comparatively lower tolerances for technical error and delay. Specifically, the technical challenges presented in performing precise and complex reconstructive techniques with limited access and the longer cardiopulmonary bypass and aortic crossclamp times associated with robot-assisted cardiac operations 2-4 have hampered widespread acceptance of robotics in the cardiothoracic surgical community. A smaller user base, the slow refinement of the technology, and, consequently, the slow accumulation of evidence of clinical benefit has also slowed the adoption of the new technology. Improved adoption and the use of robotic surgery technology will require improvements in both technology and training methods. The traditional Halstedian principles of surgical training using a "see one, do one, teach one" apprenticeship model are not wholly applicable to surgical robotic training. To develop clinical proficiency, effective training and practice strategies to familiarize surgeons with new robotic technologies are required. 2,3 However, currently practiced robotic training approaches lack uniform criteria for automatically assessing and tracking technical and operational skills. Establishing standard, objective, and automated skill measures, leading to effective training curricula and certification programs for robotic surgery will require (1) a significant cohort of robotic surgeons-in-training of similar
doi:10.1016/j.jtcvs.2011.11.002 pmid:22172215 pmcid:PMC3288290 fatcat:lj5cdoto35d3rixai62s6v4hti