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Title: | Robotic simulation training for urological trainees: a comprehensive review on cost, merits and challenges. | Austin Authors: | MacCraith, Eoin;Forde, James C;Davis, Niall F | Affiliation: | Department of Urology, Connolly Hospital, Blanchardstown, Dublin 15, Ireland Department of Urology, Austin Health, Heidelberg, Victoria, Australia |
Issue Date: | Jun-2019 | Date: | 2019-02-22 | Publication information: | Journal of robotic surgery 2019; 13(3): 371-377 | Abstract: | Simulation in surgery is a safe and cost-effective way of training. Operating room performance is improved after simulation training. The necessary attributes of surgical simulators are acceptability and cost-effectiveness. It is also necessary for a simulator to demonstrate face, content, predictive, construct and concurrent validity. Urologists have embraced robot-assisted surgery. These procedures require steep learning curves. There are 6 VR simulators available for robot-assisted surgery; the daVinci Skills Simulator (dVSS), the Mimic dV Trainer (MdVT), the ProMIS simulator, the Simsurgery Educational Platform (SEP) simulator, the Robotic Surgical Simulator (RoSS) and the RobotiX Mentor (RM). Their efficacy is limited by the lack of comparative studies, standardisation of validation and high cost. There are a number of robotic surgery training curricula developed in recent years which successfully include simulation training. There are growing calls for these simulators to be incorporated into the urology training curriculum globally to shorten the learning curve without compromising patient safety. Surgical educators in urology should aim to develop a cost-effective, acceptable, validated simulator that can be incorporated into a standardised, validated robot-assisted surgery training curriculum for the next generation of robotic surgeons. | URI: | https://ahro.austin.org.au/austinjspui/handle/1/20284 | DOI: | 10.1007/s11701-019-00934-1 | ORCID: | 0000-0002-5814-0722 0000-0002-5298-1475 |
Journal: | Journal of robotic surgery | PubMed URL: | 30796671 | Type: | Journal Article | Subjects: | Robot Robotic Simulation Surgery Training Urology |
Appears in Collections: | Journal articles |
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