Best Practices for Robotic Surgery Training and Credentialing
Jason Y. Lee, Phillip Mucksavage, Chandru P. Sundaram, Elspeth M. McDougall
- Year
- 2011
- Citations
- 152
Abstract
PURPOSE: With the rapid and widespread adoption of robotics in surgery, the minimally invasive surgical landscape has changed markedly within the last half decade. This change has had a significant impact on patients, surgeons and surgical trainees. This is no more apparent than in the field of urology. As with the advent of any new surgical technology, it is imperative that we develop comprehensive and responsible training and credentialing initiatives to ensure surgical outcomes and patient safety are not compromised during the learning process. MATERIALS AND METHODS: A literature search was conducted on surgical training curricula as well as robotic surgery training and credentialing to provide best practice recommendations for the development of a robotic surgery training curriculum and credentialing process. RESULTS: For trainees to attain the requisite knowledge and skills to provide safe and effective patient care, surgical training in robotics should involve a structured, competency based curriculum that allows the trainee to progress in a graduated fashion. This structured curriculum should involve preclinical and clinical components to facilitate the proper adoption and application of this new technology. Robotic surgery credentialing should involve an expert determined, standardized educational process, including a minimum criterion of proficiency. CONCLUSIONS: Rather than being based on a set number of completed cases, robotic surgery credentialing should involve the demonstration of proficiency and safety in executing basic robotic skills and procedural tasks. In addition, the accreditation process should be iterative to ensure accountability to the patient.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
2012
Self-Organizing Maps
Teuvo Kohonen
1995
Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller +1 more
2013