MP22-05 EVALUATION OF TECHNICAL LEARNING-CURVES FOR ROBOT ASSISTED RADICAL PROSTATECTOMY - A MULTI-INSTITUTIONAL STUDY

Abstract

You have accessJournal of UrologyTechnology & Instruments: Surgical Education & Skills Assessment I1 Apr 2015MP22-05 EVALUATION OF TECHNICAL LEARNING-CURVES FOR ROBOT ASSISTED RADICAL PROSTATECTOMY - A MULTI-INSTITUTIONAL STUDY Catherine Lovegrove, Giacomo Novara, Khurshid Guru, Alex Mottrie, Ben Challacombe, Johar Raza, Henk Van der Poel, James Peabody, Rick Popert, Prokar Dasgupta, and Kamran Ahmed Catherine LovegroveCatherine Lovegrove More articles by this author , Giacomo NovaraGiacomo Novara More articles by this author , Khurshid GuruKhurshid Guru More articles by this author , Alex MottrieAlex Mottrie More articles by this author , Ben ChallacombeBen Challacombe More articles by this author , Johar RazaJohar Raza More articles by this author , Henk Van der PoelHenk Van der Poel More articles by this author , James PeabodyJames Peabody More articles by this author , Rick PopertRick Popert More articles by this author , Prokar DasguptaProkar Dasgupta More articles by this author , and Kamran AhmedKamran Ahmed More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.1017AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Use of robot-assisted radical prostatectomy (RARP) has become the current standard of care. Surgical training and its—assessment are critical in assuring optimal outcomes after robot-assisted approach towards prostatectomy. Learning curves can be used to identify learning needs and evaluate the success of training methods to ensure efficient use of resources in helping trainee surgeons achieve competence. This study aims to evaluate the technical skills of trainees by constructing learning curves for individual steps of RARP. METHODS This multi-institutional, observational, prospective study used a validated assessment score designed to examine the technical skills required for the most hazardous steps of RARP. The RARP Assessment Score was distributed to 15 trainees who performed numerous RARP cases and were scored by their mentors. Results were analysed relative to RARP experience to examine learning—curves for each step. RESULTS 15 trainees were assessed for 8 months. They participated in 426 RARP cases (Range 4–79) and, all 17 procedural steps were attempted. Of reported data, the majority of cases were T stage 2 (40.3%), N stage 0 (59.9%) and “Intermediate” D'Amico risk (36.1%). Learning curves derived demonstrated several findings. Of note were the plateaus for Anterior Bladder Neck Transection (16 cases), Posterior Bladder Neck Transection (18 cases), Posterior Dissection (9 cases), Dissection of Prostatic Pedicle and Seminal Vesicles (15 cases) and Anastomosis (17 cases). For the rest of the steps the LC did not plateau for the data collection period (e.g. Expose Prostatic Apex and Endopelvic Fascia; 31 cases, Stitching and Division of Dorsal Venous Plexus; 32 cases). CONCLUSIONS RARP Assessment Score based on HFMEA methodology identified critical hazardous steps specific to RARP and was used to assess and evaluate surgeons while performing RARP. The learning curves derived demonstrate the experience necessary to reach a level of competence in essential technical skills required to protect patient safety. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e242-e243 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Catherine Lovegrove More articles by this author Giacomo Novara More articles by this author Khurshid Guru More articles by this author Alex Mottrie More articles by this author Ben Challacombe More articles by this author Johar Raza More articles by this author Henk Van der Poel More articles by this author James Peabody More articles by this author Rick Popert More articles by this author Prokar Dasgupta More articles by this author Kamran Ahmed More articles by this author Expand All Advertisement Advertisement PDF DownloadLoading ...