MP11-04 LEARNING CURVE IN ROBOT-ASSISTED RADICAL PROSTATECTOMY: PRACTICE MAKES PERFECT, BUT WHAT PRACTICE?

Abstract

You have accessJournal of UrologySurgical Technology & Simulation: Training & Skills Assessment I1 Apr 2016MP11-04 LEARNING CURVE IN ROBOT-ASSISTED RADICAL PROSTATECTOMY: PRACTICE MAKES PERFECT, BUT WHAT PRACTICE? 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.2016.02.2375AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Reduced training hours and novel technology require that surgical training be adapted accordingly. Effective use of observation, simulation and clinical practice can enhance progression along the learning curve and promote patient safety. This study sought to examine the effect of prior experience in dry-lab simulation, robotic simulation and clinical experience on the learning curve for technical skills in robot-assisted radical prostatectomy (RARP). METHODS A multi-institutional, prospective, observational, longitudinal study was conducted using a validated training tool with a scoring scale to measure technical competence in RARP procedural stages. 15 urology trainees and their mentors from Europe and Australia were recruited to examine their learning curves for the procedure. Their previous experiences were noted to assess what effect this had on the technical competence attained. RESULTS Over eight months, 15 surgeons were assessed by their mentors in 425 RARP cases (range 7-79). Seven surgeons (46.67%) had prior console experience (range 2-8 months). This was associated with a significant difference in scores attained in six of the 17 procedural stages (p<0.05), particularly more challenging steps such as “posterior bladder neck transection” (p=0.017), “seminal vesicle dissection” (p=0.029) and “apical dissection of the prostate” (p<0.001). 11/15 surgeons had experience of robotic simulation (73.34%). This related to significantly higher scores in four stages, notably “apical dissection of the prostate” (p=0.026) and “lymph node dissection” (p=0.034). 9/15 (60%) surgeons had utilised dry-lab simulation. This was significantly associated to greater technical skill in five stages of RARP. Again, more challenging steps such as “dissection of prostate pedicle and neurovascular bundle +/- nerve preservation” (p=0.028) and “vesicourethral anastomosis” (p=0.006). Of steps where there was a difference related to prior experience, 10/15 (66.67%) were difficulty level III or IV. CONCLUSIONS Prior experience in robotic or dry-lab simulation and console experience was associated with significantly greater technical skill in numerous stages of RARP. More difficult steps were frequently associated with a difference in the learning curve attained. Results should be used to design modular curricula to optimise surgical training experiences. © 2016FiguresReferencesRelatedDetails Volume 195Issue 4SApril 2016Page: e112 Advertisement Copyright & Permissions© 2016MetricsAuthor 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 ...

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