Shirin Azadi1, Isabel C Green2, Anne Arnold3, Mireille Truong4, Jacqueline Potts1, Martin A Martino5. 1. Department of Obstetrics and Gynecology, Lehigh Valley Health Network, Allentown, Pennsylvania (Drs. Azadi, Potts, and Martino). 2. Department of Gynecology and Obstetric, Mayo Clinic, Rochester, Minnesota (Dr. Green). 3. American College of Obstetricians and Gynecologists, University of Pennsylvania Graduate School of Education, Philadelphia, PA (Ms. Arnold). 4. Division of Minimally Invasive Gynecologic Surgery, Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, California (Dr. Truong). 5. Department of Obstetrics and Gynecology, Lehigh Valley Health Network, Allentown, Pennsylvania (Drs. Azadi, Potts, and Martino); Department of Obstetrics and Gynecology, University of South Florida, Tampa, Florida (Dr. Martino). Electronic address: martin_A.Martino@lvh.com.
Abstract
OBJECTIVE: To review the current status of robotic training and the impact of various training platforms on the performance of robotic surgical trainees. DATA SOURCES: Literature review of Google Scholar and PubMed. The search terms included a combination of the following: "robotic training," "simulation," "robotic curriculum," "obgyn residency robotic training," "virtual reality robotic training," "DaVinci training," "surgical simulation," "gyn surgical training." The sources considered for inclusion included peer-reviewed articles, literature reviews, textbook chapters, and statements from various institutions involved in resident training. METHODS OF STUDY SELECTION: A literature search of Google Scholar and PubMed using terms related to robotic surgery and robotics training, as mentioned in the "Data Sources" section. RESULTS: Multiple novel platforms that use machine learning and real-time video feedback to teach and evaluate robotic surgical skills have been developed over recent years. Various training curricula, virtual reality simulators, and other robotic training tools have been shown to enhance robotic surgical education and improve surgical skills. The integration of didactic learning, simulation, and intraoperative teaching into more comprehensive training curricula shows positive effects on robotic skills proficiency. Few robotic surgery training curricula have been validated through peer-reviewed study, and there is more work to be completed in this area. In addition, there is a lack of information about how the skills obtained through robotics curricula and simulation translate into operating room performance and patient outcomes. CONCLUSION: Data collected to date show promising advances in the training of robotic surgeons. A diverse array of curricula for training robotic surgeons continue to emerge, and existing teaching modalities are evolving to keep up with the rapidly growing demand for proficient robotic surgeons. Futures areas of growth include establishing competency benchmarks for existing training tools, validating existing curricula, and determining how to translate the acquired skills in simulation into performance in the operating room and patient outcomes. Many surgical training platforms are beginning to expand beyond discrete robotic skills training to procedure-specific and team training. There is still a wealth of research to be done to understand how to create an effective training experience for gynecologic surgical trainees and robotics teams.
OBJECTIVE: To review the current status of robotic training and the impact of various training platforms on the performance of robotic surgical trainees. DATA SOURCES: Literature review of Google Scholar and PubMed. The search terms included a combination of the following: "robotic training," "simulation," "robotic curriculum," "obgyn residency robotic training," "virtual reality robotic training," "DaVinci training," "surgical simulation," "gyn surgical training." The sources considered for inclusion included peer-reviewed articles, literature reviews, textbook chapters, and statements from various institutions involved in resident training. METHODS OF STUDY SELECTION: A literature search of Google Scholar and PubMed using terms related to robotic surgery and robotics training, as mentioned in the "Data Sources" section. RESULTS: Multiple novel platforms that use machine learning and real-time video feedback to teach and evaluate robotic surgical skills have been developed over recent years. Various training curricula, virtual reality simulators, and other robotic training tools have been shown to enhance robotic surgical education and improve surgical skills. The integration of didactic learning, simulation, and intraoperative teaching into more comprehensive training curricula shows positive effects on robotic skills proficiency. Few robotic surgery training curricula have been validated through peer-reviewed study, and there is more work to be completed in this area. In addition, there is a lack of information about how the skills obtained through robotics curricula and simulation translate into operating room performance and patient outcomes. CONCLUSION: Data collected to date show promising advances in the training of robotic surgeons. A diverse array of curricula for training robotic surgeons continue to emerge, and existing teaching modalities are evolving to keep up with the rapidly growing demand for proficient robotic surgeons. Futures areas of growth include establishing competency benchmarks for existing training tools, validating existing curricula, and determining how to translate the acquired skills in simulation into performance in the operating room and patient outcomes. Many surgical training platforms are beginning to expand beyond discrete robotic skills training to procedure-specific and team training. There is still a wealth of research to be done to understand how to create an effective training experience for gynecologic surgical trainees and robotics teams.
Authors: Daniel M Costello; Isabel Huntington; Grace Burke; Brooke Farrugia; Andrea J O'Connor; Anthony J Costello; Benjamin C Thomas; Philip Dundee; Ahmed Ghazi; Niall Corcoran Journal: J Robot Surg Date: 2021-09-03
Authors: Ryan N Hansen; Basil Matthew Saour; Brian Serafini; Blake Hannaford; Lanu Kim; Takayoshi Kohno; Ryan James; Wayne Monsky; Stephen P Seslar Journal: Telemed J E Health Date: 2021-11-19 Impact factor: 5.033