Urology is at the forefront of minimally invasive surgery to a great extent. These procedures produce additional learning challenges and possess a steep initial learning curve. Training and assessment methods in surgical specialties such as urology are known to lack clear structure and often rely on differing operative flow experienced by individuals and institutions.
This article aims to assess current urology training modalities, to identify the role of simulation within urology, to define and identify the learning curves for various urologic procedures, and to discuss ways to decrease complications in the context of training.
A narrative review of the literature was conducted through December 2015 using the PubMed/Medline, Embase, and Cochrane Library databases.
Evidence of the validity of training methods in urology includes observation of a procedure, mentorship and fellowship, e-learning, and simulation-based training. Learning curves for various urologic procedures have been recommended based on the available literature. The importance of structured training pathways is highlighted, with integration of modular training to ensure patient safety.
Valid training pathways are available in urology. The aim in urology training should be to combine all of the available evidence to produce procedure-specific curricula that utilise the vast array of training methods available to ensure that we continue to improve patient outcomes and reduce complications.
The current evidence for different training methods available in urology, including simulation-based training, was reviewed, and the learning curves for various urologic procedures were critically analysed. Based on the evidence, future pathways for urology curricula have been suggested to ensure that patient safety is improved.
Keywords: Learning curves, Simulation, Surgical education, Training.
Training in urology is undergoing a shift, with more classical surgical apprenticeship models becoming increasingly outdated . These methods of training lack clear structure and rely on differing operative flow experienced by individuals and institutions . When considering this in the context of globally decreasing training hours due to working time restrictions and the worrying signs this seems to have for patient outcomes, it is clear this shift is necessary . Urology is also in the position of using minimally invasive surgery to a great extent, and that produces additional challenges with steep initial learning curves .
The ever-increasing scrutiny faced by surgeons combined with changes in public attitudes towards inexperienced surgeons operating on them also must not be underestimated, with ethical and legal considerations now a common concern . Furthermore, it is becoming increasingly clear that the content of training requires review. We now accept that there is more to being a good surgeon than astute technical ability, with the role of nontechnical skills in operating practice increasingly understood . This review article aims (1) to assess current urology training modalities, (2) to identify the role of simulation within urology, (3) to define and identify the learning curves for various urologic procedures, and (4) to discuss ways to decrease complications in the context of training.
2. Evidence acquisition
A narrative review of the literature was conducted through December 2015 using the PubMed, Embase, and Cochrane Library databases. A broad search strategy was used with the following terms (title/abstract): (urology OR urological OR urologist) AND (training OR simulation OR learning curve). Results were limited to the English language, without restrictions placed. Abstract review was conducted for relevance to the aims of the review, and full text was subsequently analysed. No formal quality assessment of the included studies was performed.
3. Evidence synthesis
This section provides an overview of (1) training modalities in urology, (2) simulation-based training, (3) learning curves for various urologic procedures, and (4) ways to reduce complications in the context of training.
3.1. Training in urology
Observing another surgeon perform a procedure for the purpose of training has long been common practice. It builds procedural knowledge and allows an individual to ask questions to address gaps in knowledge, providing a vital first step in training programmes . Despite this hugely common practice, little evidence is available in the literature about its effectiveness or how to best utilise this method of training in urology; however, this has not stopped organisations from recommending the use of observership in curricula. Robotic curricula from the European Association of Urology (EAU) and the British Association of Urology (BAUS) state that it should be used as an initial step, allowing for the development of basic principles and knowledge relevant to robotic surgery  and . Its practice, however, is limited to this initial phase of training because it allows limited opportunity for improvement of technical ability.
e-Learning is the use of the Internet and multimedia technology to deliver knowledge and to aid learning . e-Learning is a flexible, easily accessed, and updatable method of training that has been demonstrated to aid learning in surgery . Three identified methods use this type of teaching: instruction with virtual patients, delivery of theoretical knowledge, and teaching of surgical skills . e-Learning has an established role in urology, with both the EAU and the American Urological Association offering numerous online modules  and . In addition, the recently developed EAU robotic curriculum used e-learning as the initial method of teaching in combination with observership, further establishing the role of e-learning as a useful adjunct to training in urology .
3.1.3. Mentorship and fellowship
The process of having an experienced and competent mentor guiding a less experienced individual is an old practice in surgical teaching and forms the basis of old Halstedian models of training. Through the process of sharing knowledge, practical teaching, and feedback, a trainee can acquire significant knowledge and improve skill sets . Within modern urology training, it is becoming increasingly understood how to get the most out of this age-old practice. The role of the mentor is pivotal to the success of this process, and appropriate experience and skills are vital . In addition, the ability to share the expertise possessed often is not innate, and the increasing need for training of mentors is being recognised . Furthermore, this training method requires a structured approach to ensure that maximal benefit is gained. Clear objectives should be identified at the outset, with a structured learning pathway in place prior to a formal sign-off process through which constructive feedback can be given .
Many of the structured mentorship programmes are delivered through formal fellowships. These programmes are designed to provide focused exposure to a specific area of a specialty through longer fellowships or minifellowships . Urologic fellowships are offered at institutions across the globe, have been demonstrated to be educationally useful, and help urologists gain experience and confidence in incorporating new techniques into their practice , , and .
An interesting extension of mentorship has recently arisen through telementoring. Through a real-time video link, an expert can interact and mentor a surgeon located in a separate location during a procedure . Use of telementoring in surgery is supported by a good evidence base that demonstrates educational effectiveness and is said to be improving surgical education  and . Nevertheless, it is important to recognise some of the legal and ethical considerations if considering its use. Concerns regard patient confidentiality, recognition of qualifications of mentors in different countries, and legal liability in the eventuality of errors, making it important to use telementoring in the context of institutional guidelines . Regardless, as minimally invasive surgery continues to expand in urology, telementoring is likely to become a common training method in the future.
3.1.4. Modular training
Modular training divides a procedure to be learned into steps with differing levels of difficulty. The trainee would not perform the entire procedure at first but instead develop skills progressively for an entire procedure by learning increasingly difficult segments under the supervision of an experienced mentor . Each module of the procedure is repeated until the supervisor decides that the trainee may progress to the next module, with independent performance of the steps as the final objective. This structured method of training is supported by a good evidence base in urology, and numerous suggested training modules exist for minimally invasive procedures . In addition, within endourology, the Holmium User Group has developed a modular mentorship programme for holmium laser enucleation of the prostate (HoLEP) to produce a safe and systematised method of training for this procedure .
Despite its widespread use, uncertainties remain regarding this method of training. It is unclear when a trainee can progress from one module to the next, with current practice relying largely on subjective evaluation by the mentor . Recent development of a modular assessment tool for robotic-assisted radical prostatectomy may help overcome this difficulty . The tool allows for evaluation of learning curves for individual steps of the procedure, giving mentors an objective way to assess progression through the modules. Similar tools need to be developed for various individual procedures to further enhance learning from this training method.
3.2. Simulation in urology
Simulation-based training is increasingly being recognised as a valuable adjunct to training in urology and other craft disciplines. It offers trainees the opportunity to practice fundamental skills in a safe and forgiving environment, protecting patient safety and enhancing progression along the initial phase of the learning curve . Various modalities are available including virtual reality (VR) and bench-top simulators as well as animal and cadaveric models, each with their potential advantages and disadvantages (Table 1) . In addition, with their associated costs, it is important that we ensure that simulators are effective and validated according to predetermined validation criteria . As the evidence supporting simulation continues to expand and improved skills transfer to the operating room , the question increasingly is not whether simulation is effective but rather how it is best utilised.
|Cadaver||Fresh frozen human and Thiel's method||Unrivaled anatomy fidelity and full-procedure simulation possible||High cost, facilities, tissue compliance, and nonreusable||Procedural simulation, anatomic teaching, continuing medical education|
|Animal||Live or dissected animal tissues, (eg, porcine)||Comparable anatomy, complete procedure simulation||High cost, ethical considerations, and limited reusability||Procedural simulation|
|Virtual reality||Computer-based simulation models||Reusable, flexible utilisation, performance data capture and analysis for feedback||Maintenance, high initial cost, and little to no haptic feedback||Basic surgical skills tasks or procedural simulation|
|Bench-top||Inanimate models, synthetic suturing mats and pegboards||Large availability, lower cost to VR, often portable and reusable||Anatomic fidelity is often low with differing tissue haptics, allows for true operative equipment use||Basic surgical skills or procedural simulation|
3.2.1. Available simulation modalities
A wide variety of procedures are conducted in urology, and thus a variety of simulation modalities have become available. Minimally invasive surgical simulation such as in laparoscopy is well established, and VR, bench, animal, and cadaveric simulation modalities have been validated for procedures such as laparoscopic nephrectomy and prostatectomy (Table 2) , , , , , and . In addition, robotic simulation has developed enormously since its uptake, with six commercially available VR simulators developed and validated to varying degrees , , and  and porcine models also showing a proven benefit .
|Simulation modality||Face validity||Content validity||Construct validity||Educational impact|
|Urethrovesical model ||✓||✓|
|Animal , , and ||✓||✓||✓|
|Procedicus MIST (Mentice)  and ||✓||✓||✓|
|LAP mentor (Symbionix) ||✓||✓||✓||✓|
|Animal  and ||✓||✓||✓||✓|
|RoSS (Simulated Surgical Systems)  and ||✓||✓||✓||✓|
|SEP (SimSurgery)  and ||✓||✓||✓|
|ProMIS (Haptica)  and ||✓||✓||✓||✓|
|MdVT (Mimic Technologies)  and ||✓||✓||✓||✓|
|dVSS (Intuitive Surgical Inc.)  and ||✓||✓||✓||✓|
|RobotiX Mentor ||✓||✓||✓|
|Uro-Scopic Traininer (Limbs and Things)  and ||✓||✓||✓|
|Scope Trainer (Mediskills)  and ||✓||✓||✓|
|Adult ureterscopy trainer (IDA) ||✓||✓||✓|
|URO Mentor (Simbionix)  and ||✓||✓||✓||✓|
|Cadaveric  and ||✓||✓||✓|
|Percutaneous renal access|
|PERC Mentor (Simbionix) , , and ||✓||✓||✓||✓|
|Animal  and ||✓||✓|
|TURP trainer (Limbs and Things) ||✓||✓||✓|
|VR TURP simulator (UCL)  and ||✓|
|TURP simulator (UHL)  and ||✓||✓|
|UW TURP trainer (UoW) , , and ||✓||✓||✓|
|Simbla TURBT Simulator (SAMED GmbH)) ||✓||✓||✓|
|URO Trainer (Karl Storz)  and ||✓||✓|
|HoLEP Simulator (Kansai University) ||✓||✓|
|GreenLight SIM (AMS)  and ||✓||✓||✓||✓|
|Myo Sim Simulator (VirtaMed) ||✓|
|UroSim HoLEP Simulator (VirtaMed) ||✓||✓||✓|
AMS = American Medical Systems (Boston Scientific); dVSS = da Vinci Skills Simulator; HoLEP = holmium laser enucleation of the prostate; IDA = Ideal Anatomical Modelling; MdVT = Mimic dV-Trainer; RoSS = Robotic Surgery Simulator; SEP = Simsurgery Educational Platform; TURBT = transurethral resection of bladder tumour; TURP = transurethral resection of the prostate; UCL = Iniversity College London; UHL = University Hospital Linköping; UoW = University of Washington.
Simulation in endourology is equally as diverse. Procedures such as ureteroscopy and cystoscopy are well suited to simulation and thus have generated much interest for developers. Extensive modalities are available, with several bench-top simulators and a VR model produced and validated  and . Moreover, animal and cadaveric models have been demonstrated to be effective teaching modalities within ureteroscopy and cystoscopy , , and . Similarly, percutaneous access procedures can be trained through validated VR simulators and porcine models , , , and . In looking at simulation in transurethral resection of the prostate (TURP), it is surprising to find that although a bench model and various VR models exist, no evidence has been found for their educational impact as of yet , , and . Similar issues are present in looking at transurethral resection of bladder tumour (TURBT), for which one VR and one benchtop model exist , , and . Finally, with the rise of laser therapies such as HoLEP and GreenLight laser prostatectomy (Boston Scientific, Marlborough, MA, USA), there was a recent need to develop suitable modalities to train for these newer techniques. Various VR simulators for both procedures and a bench model for HoLEP are now available; however, evidence of educational impact is still lacking for the majority  and .
It is evident that simulation modalities for the training of technical skills in all aspects of urology are well established. A good evidence base supports their use, with the exception of TURP, TURBT and laser therapy simulators, which lack evidence of educational impact. Nevertheless, although the impact of simulators in operative performance in surgery as a whole is known, few studies have looked at this tool specifically in urology , largely due to the difficulties of organising such a trial. This lack should be addressed when considering future research on the role of individual simulators in urology.
3.2.2. Simulation for nontechnical skills training
The role of nontechnical skills in surgery is being increasingly understood and is an expanding area within the literature. It is now known that deficiencies in this area are a large cause of surgical error , and it is increasingly recognised that these skill sets are not peripheral but rather should be seen alongside technical skills as being of core importance. Nontechnical skills can be divided into three categories: cognitive (situation awareness, decision making, and planning), social (communication, teamwork, and leadership), and personal resource skills (coping with stress and fatigue) . Much like technical skills, nontechnical skills are not innate and can be enhanced through training, which is known to improve patient safety . This is done either through didactic delivery of the components of nontechnical skills or practically through simulation-based training . Through either full-immersion simulation or crisis resource management, scenarios and complete procedures can be performed with several members of the team, allowing for a structured debrief and thus development of these skills .
High-fidelity, fully immersive simulation is being used increasingly in urology. Various procedures such as laparoscopic nephrectomy, TURP, and ureteroscopy have demonstrated this tool to be educationally useful for developing both social and cognitive skills , , and . In addition, it is increasingly being used within formal training for many minimally invasive curricula  and ; however, just like technical skills, many nontechnical skills are procedure specific. The skills used by a robotic surgeon, who is located at a distance from the patient, are very different from those used in one-person procedures such as TURP ; however, little evidence exists regarding what these procedure-specific skills are or how best to train for them. This area should be further explored in future research.
3.2.3. Simulation-based curricula
Although the evidence for simulators is evident, they should not be used as a standalone or one-time method of training; instead, simulators should be integrated into comprehensive and proficiency-based curricula to ensure progressive acquisition of skills . Simulation-based curricula are available in many parts of urology with the most common example being the Fundamental Laparoscopic Skills, which are not urology specific but offer an extensively validated and useful introduction to basic laparoscopic techniques . In robotics, similar curricula have been developed and validated, including the Fundamentals of Robotic Surgery and the Fundamental Skills of Robotic Surgery . Curricula for individual procedures also exist in the literature, including laser therapies of the prostate and ureteroscopy and a programme integrating various endourologic, laparoscopic, and robotic procedures , , and .
For these curricula to be effective, they must be designed to meet needs in practice. Only recently has there been a shift in thinking in which curricula no longer focus on either technical or nontechnical aspects of a procedure but instead aim to train these skill sets alongside each other. These skills are used simultaneously in practice and should be trained as such; this approach has already been shown to be effective in developing both skill sets simultaneously  and . In addition, curricula should use the different modalities available at different stages of the learning process because each has potential advantages for different skill levels  and ; this approach is beginning to be considered for the EAU and BAUS robotic curricula  and . There is now a need to develop curricula for all urologic procedures that not only integrate technical and nontechnical skills training but also use various training modalities. It has been suggested that curricula should use VR simulation followed by bench models as an initial step for learning basic procedural skills . This should be followed by increasing fidelity models, including animal models, full-immersion simulation, and finally human cadaveric models, all of which can teach advanced technical skills and nontechnical skills concurrently. Moreover, with increasing experience, there should be a shift from basic procedural skills to full case training and management of complications .
3.3. The learning curves in urology
The learning curve is the initial period of learning and skill acquisition specific to a procedure and is said to be overcome either when performance plateaus or once competency is achieved . This period is when near-miss or adverse events are likely to occur. In addition, this period requires increased amounts of time for procedures to be completed and thus has increased cost . Consequently, it is useful to understand learning curves and how to assess whether surgeons have overcome them for planning of training, for ensuring that competency has been attained, and for adopting a new technique .
Several attempts have been made to quantify the learning curve for urologic procedures, including minimally invasive and endourologic procedures (Table 3). All of these studies used patient outcome as a quantitative measure to evaluate learning curves. Few laparoscopic procedures have a suggested learning curve, with only radical prostatectomy (200–250 cases, using positive surgical margins and biochemical recurrence) and partial nephrectomy (25–65 cases for warm ischaemia time and estimated blood loss) having been investigated , , and . This is different from robotic procedures, for which more studies have been conducted, and various outcome parameters have been used for learning curve evaluation. For robot-assisted laparoscopic prostatectomies, it has been suggested that 40 cases be required to plateau operating time compared with 80–300 cases when using oncologic parameters. Twenty to 75 cases are recommended for stabilisation of warm ischaemia time and estimated blood loss for robotic partial nephrectomy. A relatively short case load with 15–30 procedures for radical cystectomy, using lymph node yield and positive surgical margins, was required for stabilisation of outcomes . In addition, in percutaneous nephrolithotomy, a few studies recognised a learning curve of 12–60 cases (105 when looking at stone extraction rates), with similar figures of 50 cases seen in ureteroscopy (for stone-free rates)  and . There has been little investigation into the learning curve for TURP (10 cases suggested for monopolar TURP, 30–50 cases for bipolar, using functional outcome resection efficiency)  and . This is in contrast to the more recently developed HoLEP procedure, for which extensive investigation led to a figure of 20–60 cases (according to functional outcomes and operative efficiency markers) . Finally, a single study identified a learning curve of 120 cases for the GreenLight procedure (for energy delivered and functional outcomes) .
|Procedure||Learning curve||Outcomes used|
|Radical prostatectomy  and ||200–250 (>500 for BCR)||PSM, CR, continence, potency, BCR, OT, EBL|
|Partial nephrectomy ||25–65||WIT, EBL, OT,|
|Radical prostatectomy ||80–300 (40 for OT)||OT, EBL, CR, success rates, PSA reduction, PSM|
|Partial nephrectomy ||20–75||OT, EBL, WIT, CR|
|Radical cystectomy ||15–30||OT, lymph node yield, EBL, PSM|
|Radical prostatectomy ||20–30 (250 for PSM)||OT, EBL, CR, recurrence, continence, potency, PSM|
|Percutaneous nephrolithotomy ||12–60 (105 for SER)||OT, CR, SER, stone-free rates|
|Ureteroscopy ||50||CR, success rates, stone-free rates|
|Monopolar ||10||Resection efficiency, capsular lesions, OT, percentage of resected tissue|
|Bipolar ||30–50||OT, IPSS, QoL, Qmax, residual prostate volume|
|HoLEP ||20–60||OT, enucleation ratio efficiency, morcellation efficiency, CR, IPSS, Qmax|
|GreenLight ||120||Energy delivered, lasing time/OT ratio, IPSS, residual prostate volume|
CR = complication rate; BCR = biochemical recurrence; EBL = estimated blood loss; HoLEP = holmium laser enucleation of the prostate; IPSS = International Prostate Symptom Score; OT = operative time; PSA = prostate-specific antigen; PSM = positive surgical margins; Qmax = maximum flow rate; QoL = quality of life; SER = stone expulsion rate; TURP = transurethral resection of the prostate; WIT = warm ischaemia time.
It is evident that extensive investigation has been undertaken for learning curves in urologic procedures. Nevertheless, several important weaknesses in current studies affect the quality of the evidence and must be considered when quantifying the learning curve. Many studies analysed experiences of single surgeons, many of whom had completed their basic training and had prior experience with other procedures. It is known that surgeons with previous open experience have slower learning curves for laparoscopic procedures ; therefore, the learning experience of an experienced single surgeon may not be applicable to the trainee surgeon (residents and fellows). Furthermore, large variations exist in suggested figures for many of the extensively studied procedures. This variation reflects the varying methodologies used for identification of the learning curve. Various studies divide cohorts into arbitrary cohorts of patients and define the learning curve once performance stabilises between cohorts; however, this approach makes it difficult to establish true stabilisation of performance and results in large variances in identified values. In addition, this variation is compounded by the fact that the learning curve is often outcome dependent, with simpler measures such as operative time easier to master than oncologic recurrence rates. Finally, there is little recognition in the literature that learning curves are also dependent on the patient group analysed . Consequently, future research must focus on attempting to address these weaknesses within the methodology to ensure that high-quality evidence is produced for accurate quantification of learning curves.
Although many studies have looked at the stabilisation of performance, it is more applicable to assess the achievement of a predefined competency level. This allows for translation into clinical practice and is what the BAUS robotic curriculum has attempted. Evidence from learning curve studies was used to set clear quality indicators, along with an expected number of procedures for anticipated achievement, although little consideration was given to the weaknesses of these studies . This approach provides a clearly defined competency level based on the evidence, and the aim should be to produce similar indicators for all urologic procedures based on learning curve studies, once further good evidence is produced within the literature.
3.4. Reducing complications
Much of the evidence assessing the effects of various training methods in urology has looked only indirectly at the effects, through skills acquisition, as opposed to demonstrating better outcomes and reduced complications . The ultimate goal should be, as always, to ensure that better patient care is established, and this must now be looked at in urology. The extensive knowledge that has been developed about these training methods must not be disregarded but rather integrated to shape future training pathways that can be demonstrated to improve outcomes.
Individually, methods such as e-learning and modular and simulation-based training are known to be useful. Training is moving towards combining these methods into one structured curriculum, as in the robotic curricula discussed, and this approach needs to be considered across the board for urologic procedures  and . Methods such as e-learning and observership can be a good initial step in any curriculum, providing a foundation of theoretical knowledge (Fig. 1). Simulation is known to decrease complications along the initial learning curve and thus acts as a logical next step for initial technical skills acquisition . This step, however, needs to be delivered in a structured format through a simulation-based curriculum using the various modalities available at different stages and drawing on the benefits of each . Once basic skills are developed, modular and subsequently full-procedure training can occur in a safe and systematic manner, with fellowships offering another method towards the end of training to enhance experience. At each step, it is important to ensure that effective mentorship is present and that nontechnical skills training is integrated to correlate training with practice.
It is important that the training process be proficiency based to ensure skills acquisition at each stage . Tools for assessing competence can be divided into those that are global or procedure specific . In urology, global assessment tools such as the well-established Objective Structured Assessment of Technical Skills (OSATS) and the Global Evaluative Assessment of Robotic Skills (GEARS) are validated options  and . Nevertheless, very few validated procedure-specific tools are available, with robot-assisted radical prostatectomy as the only identified procedure with such a tool . In addition, more objective markers can be used for the assessment of proficiency, with quality indicators produced from learning curve studies offering a good method for establishing competence. Finally, it is important to also assess the nontechnical skills of a trainee with the Non-Technical Skills for Surgeons (NOTSS), the Non-Technical Skills (NOTECHS) scale, or Observational Teamwork for Surgery (OTAS), all offering extensively investigated rating scales . Currently, many of the available assessment tools are very generic, and there is a need to produce more procedure-specific tools that combine both technical and nontechnical assessment.
To ensure that this process is effective and truly reduces complications, such developed curricula should be standardised and regulated via central authorities . Through this method, data can be collected for accreditation and for assessing the effect of such curricula in terms of patient safety both during and after training. Future research in education in urology should focus on producing such procedure-specific curricula that are extensive and standardised and ensuring use of the current evidence base to decrease complications both during and after training.
The role of training in the context of continuing medical education (CME) should be considered further. Although modalities such as observership, simulation-based training, and mentorship are likely effective, little current evidence shows this in the context of ensuring the maintenance of competence and training specialists for new procedures in urology . Nevertheless, evidence from other surgical specialties and anaesthetics is encouraging  and . In addition, although outcome-based assessment followed by observation of practice may be effective assessment tools for established surgeons, more evidence is required to evaluate this . To reduce complications not only in the initial part of urology training but throughout a urologist's career, more research is necessary to investigate training in a CME setting and ensure patient safety at all times.
Extensive training methods are available in urology, from observership to structured modular pathways. In addition, simulation-based training is supported by a good evidence base in urology, with various modalities available for a wide array of urologic procedures. The aim of their use is to subsequently decrease the initial learning curve and thus to improve safety. The learning curve has been quantified in various studies; however, there is still a lack of evidence for some traditional and commonly performed procedures. The aim for urology training should now be to combine all of the available evidence to produce procedure-specific curricula that use the vast array of training methods available, ensuring that we continue to improve patient outcomes and reduce complications.
Author contributions: Kamran Ahmed had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Brunckhorst, Volpe, van der Poel, Mottrie, Ahmed.
Acquisition of data: Brunckhorst, Ahmed.
Analysis and interpretation of data: Brunckhorst, Ahmed.
Drafting of the manuscript: Brunckhorst, Ahmed.
Critical revision of the manuscript for important intellectual content: Volpe, van der Poel, Mottrie.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Volpe, Ahmed.
Supervision: Volpe, Ahmed.
Other (specify): None.
Financial disclosures: Kamran Ahmed certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Kamran Ahmed acknowledges funding from National Institute for Health Research, the Urology Foundation, and the Royal College of Surgeons of England.
Funding/Support and role of the sponsor: None.
-  S.L. de Montbrun, H. Macrae. Simulation in surgical education. Clin Colon Rectal Surg. 2012;25:156-165
-  R.K. Reznick, H. MacRae. Teaching surgical skills–changes in the wind. N Engl J Med. 2006;355:2664-2669
-  N. Ahmed, K.S. Devitt, I. Keshet, et al. A systematic review of the effects of resident duty hour restrictions in surgery: impact on resident wellness, training, and patient outcomes. Ann Surg. 2014;259:1041-1053 Crossref
-  G.R. Wignall, J.D. Denstedt, G.M. Preminger, et al. Surgical simulation: a urological perspective. J Urol. 2008;179:1690-1699 Crossref
-  A.G. Gallagher, O. Traynor. Simulation in surgery: opportunity or threat?. Ir J Med Sci. 2008;177:283-287
-  R.A. Agha, A.J. Fowler, N. Sevdalis. The role of non-technical skills in surgery. Ann Med Surg. 2015;4:422-427
-  E.M. McDougall, F.A. Corica, D.S. Chou, et al. Short-term impact of a robot-assisted laparoscopic prostatectomy ‘mini-residency’ experience on postgraduate urologists’ practice patterns. Int J Med Robot. 2006;2:70-74 Crossref
-  BAUS business: robotic surgery curriculum, guidelines for training. British Association of Urological Surgeons Web site. http://www.baus.org.uk/professionals/baus_business/publications/83/robotic_surgery_curriculum. Updated 17 August 2015.
-  A. Volpe, K. Ahmed, P. Dasgupta, et al. Pilot validation study of the European Association of Urology robotic training curriculum. Eur Urol. 2015;68:292-299 Crossref
-  E. Evgeniou, P. Loizou. The theoretical base of e-learning and its role in surgical education. J Surg Educ. 2012;69:665-669 Crossref
-  N. Jayakumar, O. Brunckhorst, P. Dasgupta, M.S. Khan, K. Ahmed. e-Learning in surgical education: a systematic review. J Surg Educ. 2015;72:1145-1157
-  e-Learning: AUA e-learning activities. American Urological Association Web site. https://www.auanet.org/education/elearning-urologists.cfm.
-  Surgical education. European Association of Urology Web site. http://uroweb.org/education/online-education/surgical-education/.
-  A.R. Gagliardi, F.C. Wright. Exploratory evaluation of surgical skills mentorship program design and outcomes. J Contin Educ Health Prof. 2010;30:51-56 Crossref
-  W.W. Souba. Mentoring young academic surgeons, our most precious asset. J Surg Res. 1999;82:113-120 Crossref
-  P. Sinclair, J.E. Fitzgerald, F.D. McDermott, et al. Mentoring during surgical training: consensus recommendations for mentoring programmes from the Association of Surgeons in Training. Int J Surg. 2014;12(Suppl 3):S5-S8 Crossref
-  M. Abboudi, K. Ahmed, R. Kirby, M.S. Khan, P. Dasgupta, B. Challacombe. Mentorship programmes for laparoscopic and robotic urology. BJU Int. 2011;107:1869-1871 Crossref
-  D. Hay, M.S. Khan, H. Van Poppel, et al. Current status and effectiveness of mentorship programmes in urology: a systematic review. BJU Int. 2015;116:487-494 Crossref
-  B. Challacombe, S. Wheatstone. Telementoring and telerobotics in urological surgery. Curr Urol Rep. 2010;11:22-28 Crossref
-  S.A. Antoniou, G.A. Antoniou, J. Franzen, et al. A comprehensive review of telementoring applications in laparoscopic general surgery. Surg Endosc. 2012;26:2111-2116 Crossref
-  K.M. Augestad, J.G. Bellika, A. Budrionis, et al. Surgical telementoring in knowledge translation–clinical outcomes and educational benefits: a comprehensive review. Surg Innov. 2013;20:273-281 Crossref
-  E.M. Bogen, K.M. Augestad, H.R. Patel, R.O. Lindsetmo. Telementoring in education of laparoscopic surgeons: an emerging technology. World J Gastrointest Endosc. 2014;6:148-155 Crossref
-  J.U. Stolzenburg, H. Schwaibold, S.M. Bhanot, et al. Modular surgical training for endoscopic extraperitoneal radical prostatectomy. BJU Int. 2005;96:1022-1027 Crossref
-  H. van der Poel, W. Brinkman, B. van Cleynenbreugel, et al. Training in minimally invasive surgery in urology: European Association of Urology/International Consultation of Urological Diseases consultation. BJU Int. 2016;117:515-530
-  T. Aho, T.R. Herrmann. Description of a modular mentorship programme for holmium laser enucleation of the prostate. World J Urol. 2015;33:497-502 Crossref
-  C. Lovegrove, G. Novara, A. Mottrie, et al. Structured and modular training pathway for robot-assisted radical prostatectomy (RARP): validation of the RARP assessment score and learning curve assessment. Eur Urol. 2016;69:526-535
-  H. Abboudi, M.S. Khan, O. Aboumarzouk, et al. Current status of validation for robotic surgery simulators - a systematic review. BJU Int. 2013;111:194-205 Crossref
-  K. Ahmed, M. Jawad, M. Abboudi, et al. Effectiveness of procedural simulation in urology: a systematic review. J Urol. 2011;186:26-34 Crossref
-  E.M. McDougall. Validation of surgical simulators. J Endourol. 2007;21:244-247 Crossref
-  S.R. Dawe, G.N. Pena, J.A. Windsor, et al. Systematic review of skills transfer after surgical simulation-based training. Br J Surg. 2014;101:1063-1076 Crossref
-  J. Brewin, K. Ahmed, B. Challacombe. An update and review of simulation in urological training. Int J Surg. 2014;12:103-108 Crossref
-  R. Khan, A. Aydin, M.S. Khan, P. Dasgupta, K. Ahmed. Simulation-based training for prostate surgery. BJU Int. 2015;116:665-674
-  R. Sabbagh, S. Chatterjee, A. Chawla, J. Hoogenes, A. Kapoor, E.D. Matsumoto. Transfer of laparoscopic radical prostatectomy skills from bench model to animal model: a prospective, single-blind, randomized, controlled study. J Urol. 2012;187:1861-1866 Crossref
-  B. Prasad Rai, B. Tang, R. Eisma, R.W. Soames, H. Wen, G. Nabi. A qualitative assessment of human cadavers embalmed by Thiel's method used in laparoscopic training for renal resection. Anat Sci Educ. 2012;5:182-186 Crossref
-  A. Ganpule, J.S. Chhabra, M. Desai. Chicken and porcine models for training in laparoscopy and robotics. Curr Opin Urol. 2015;25:158-162 Crossref
-  Moglia A, Ferrari V, Morelli L, Ferrari M, Mosca F, Cuschieri A. A systematic review of virtual reality simulators for robot-assisted surgery. Eur Urol. In press. http://dx.doi.org/10.1016/j.eururo.2015.09.021
-  Whittaker G, Aydin A, Raison N, et al. Validation of the RobotiX Mentor robotic surgery simulator. J Endourol. In press.
-  O. Brunckhorst, A. Aydin, H. Abboudi, et al. Simulation-based ureteroscopy training: a systematic review. J Surg Educ. 2015;72:135-143 Crossref
-  B.M. Schout, A.J. Hendrikx, A.J. Scherpbier, B.L. Bemelmans. Update on training models in endourology: a qualitative systematic review of the literature between January 1980 and April 2008. Eur Urol.. 2008;54:1247-1261 Crossref
-  F. Soria, E. Morcillo, J.L. Sanz, A. Budia, A. Serrano, F.M. Sanchez-Margallo. Description and validation of realistic and structured endourology training model. Am J Clin Exp Urol. 2014;2:258-265
-  K. Ahmed, A. Aydin, P. Dasgupta, M.S. Khan, J.E. McCabe. A novel cadaveric simulation programme in urology. J Surg Educ. 2015;72:556-565 Crossref
-  Noureldin YA, Fahmy N, Anidjar M, Andonian S. Is there a place for virtual reality simulators in assessment of competency in percutaneous renal access? World J Urol. In press.
-  J. Stern, I.S. Zeltser, M.S. Pearle. Percutaneous renal access simulators. J Endourol. 2007;21:270-273 Crossref
-  de Vries AH, van Genugten HG, Hendrikx AJ, et al. The Simbla TURBT simulator in urological residency training: from needs analysis to validation. J Endourol. In press.
-  A. Aydin, G.H. Muir, M.E. Graziano, M.S. Khan, P. Dasgupta, K. Ahmed. Validation of the GreenLight simulator and development of a training curriculum for photoselective vaporisation of the prostate. BJU Int. 2015;115:994-1003 Crossref
-  A.A. Gawande, M.J. Zinner, D.M. Studdert, T.A. Brennan. Analysis of errors reported by surgeons at three teaching hospitals. Surgery. 2003;133:614-621 Crossref
-  R.H. Flin, P. O’Connor, M. Crichton. Safety at the Sharp End: A Guide to Non-technical Skills. (Ashgate, Farnham, England, 2008)
-  M. Gordon, D. Darbyshire, P. Baker. Non-technical skills training to enhance patient safety: a systematic review. Med Educ. 2012;46:1042-1054 Crossref
-  J. Brewin, J. Tang, P. Dasgupta, et al. Full immersion simulation: validation of a distributed simulation environment for technical and non-technical skills training in urology. BJU Int. 2015;116:156-162 Crossref
-  M.T. Gettman, C.W. Pereira, K. Lipsky, et al. Use of high fidelity operating room simulation to assess and teach communication, teamwork and laparoscopic skills: initial experience. J Urol. 2009;181:1289-1296 Crossref
-  O. Brunckhorst, S. Shahid, A. Aydin, et al. Simulation-based ureteroscopy skills training curriculum with integration of technical and non-technical skills: a randomised controlled trial. Surg Endosc. 2015;29:2728-2735
-  W. Shepherd, K.S. Arora, H. Abboudi, M. Shamim Khan, P. Dasgupta, K. Ahmed. A review of the available urology skills training curricula and their validation. J Surg Educ. 2014;71:289-296 Crossref
-  R.A. Fisher, P. Dasgupta, A. Mottrie, et al. An over-view of robot assisted surgery curricula and the status of their validation. Int J Surg. 2015;13:115-123 Crossref
-  M. Shamim Khan, K. Ahmed, A. Gavazzi, et al. Development and implementation of centralized simulation training: evaluation of feasibility, acceptability and construct validity. BJU Int. 2013;111:518-523 Crossref
-  Aydin A, Ahmed K, Shafi AM, Khan MS, Dasgupta P. The role of simulation in urological training - a quantitative study of practice and opinions. Surgeon. In press. http://dx.doi.org/10.1016/j.surge.2015.06.003
-  S. Arora, B. Lamb, S. Undre, R. Kneebone, A. Darzi, N. Sevdalis. Framework for incorporating simulation into urology training. BJU Int. 2011;107:806-810 Crossref
-  N. Khan, H. Abboudi, M.S. Khan, P. Dasgupta, K. Ahmed. Measuring the surgical ‘learning curve’: methods, variables and competency. BJU Int. 2014;113:504-508 Crossref
-  Catchpole K, Perkins C, Bresee C, et al. Safety, efficiency and learning curves in robotic surgery: a human factors analysis. Surg Endosc. In press.
-  H. Abboudi, M.S. Khan, K.A. Guru, et al. Learning curves for urological procedures: a systematic review. BJU Int. 2014;114:617-629 Crossref
-  D.W. Good, G.D. Stewart, J.U. Stolzenburg, S.A. McNeill. Analysis of the pentafecta learning curve for laparoscopic radical prostatectomy. World J Urol. 2014;32:1225-1233 Crossref
-  P.M. Pierorazio, H.D. Patel, T. Feng, J. Yohannan, E.S. Hyams, M.E. Allaf. Robotic-assisted versus traditional laparoscopic partial nephrectomy: comparison of outcomes and evaluation of learning curve. Urology. 2011;78:813-819 Crossref
-  A. Skolarikos, S. Gravas, M.P. Laguna, O. Traxer, G.M. Preminger, J. de la Rosette. Training in ureteroscopy: a critical appraisal of the literature. BJU Int. 2011;108:798-805 discussion 805
-  K.G. Yamacake, E.T. Nakano, I.B. Soares, P. Cordeiro, M. Srougi, A.A. Antunes. Analysis of the learning curve for transurethral resection of the prostate. Is there any influence of musical instrument and video game skills on surgical performance?. Turk J Urol. 2015;41:132-137
-  W. Xiong, M. Sun, Q. Ran, F. Chen, Y. Du, K. Dou. Learning curve for bipolar transurethral enucleation and resection of the prostate in saline for symptomatic benign prostatic hyperplasia: experience in the first 100 consecutive patients. Urol Int. 2013;90:68-74 Crossref
-  O. Brunckhorst, K. Ahmed, O. Nehikhare, G. Marra, B. Challacombe, R. Popert. Evaluation of the learning curve for holmium laser enucleation of the prostate using multiple outcome measures. Urology. 2015;86:824-829
-  V. Misrai, M. Faron, J. Guillotreau, et al. Assessment of the learning curves for photoselective vaporization of the prostate using GreenLight 180-Watt-XPS laser therapy: defining the intra-operative parameters within a prospective cohort. World J Urol. 2014;32:539-544 Crossref
-  A.J. Vickers, C.J. Savage, M. Hruza, et al. The surgical learning curve for laparoscopic radical prostatectomy: a retrospective cohort study. Lancet Oncol. 2009;10:475-480 Crossref
-  A.J. Vickers, F.J. Bianco, M. Gonen, et al. Effects of pathologic stage on the learning curve for radical prostatectomy: evidence that recurrence in organ-confined cancer is largely related to inadequate surgical technique. Eur Urol. 2008;53:960-966 Crossref
-  J. Cloutier, O. Traxer. Do high-fidelity training models translate into better skill acquisition for an endourologist?. Curr Opin Urol. 2015;25:143-152 Crossref
-  H. Samia, S. Khan, J. Lawrence, C.P. Delaney. Simulation and its role in training. Clin Colon Rectal Surg. 2013;26:47-55
-  K. Ahmed, T. Amer, B. Challacombe, P. Jaye, P. Dasgupta, M.S. Khan. How to develop a simulation programme in urology. BJU Int. 2011;108:1698-1702 Crossref
-  K. Ahmed, D. Miskovic, A. Darzi, T. Athanasiou, G.B. Hanna. Observational tools for assessment of procedural skills: a systematic review. Am J Surg. 2011;202 469–80.e6
-  A.C. Goh, D.W. Goldfarb, J.C. Sander, B.J. Miles, B.J. Dunkin. Global evaluative assessment of robotic skills: validation of a clinical assessment tool to measure robotic surgical skills. J Urol. 2012;187:247-252
-  O.B. Argun, K. Chrouser, S. Chauhan, et al. Multi-institutional validation of an OSATS for the assessment of cystoscopic and ureteroscopic skills. J Urol. 2015;194:1098-1105
-  K. Ahmed, T.T. Wang, H. Ashrafian, G.T. Layer, A. Darzi, T. Athanasiou. The effectiveness of continuing medical education for specialist recertification. Can Urol Assoc J. 2013;7:266-272
-  W. McIvor, A. Burden, M.B. Weinger, R. Steadman. Simulation for maintenance of certification in anesthesiology: the first two years. J Contin Educ Health Prof. 2012;32:236-242
-  C.M. Pugh, F.O. Arafat, C. Kwan, et al. Development and evaluation of a simulation-based continuing medical education course: beyond lectures and credit hours. Am J Surg. 2015;210:603-609
-  K. Ahmed, R.S. Khan, A. Darzi, T. Athanasiou, G.B. Hanna. Recertification: what do specialists think about skill assessment?. Surgeon. 2013;11:120-124 Crossref
a MRC Centre for Transplantation, King's College London, Department of Urology, Guy's and St. Thomas’ NHS Foundation Trust, King's Health Partners, London, UK
b Division of Urology, University of Eastern Piedmont, Maggiore della Carità Hospital, Novara, Italy
c Department of Urology, Netherlands Cancer Institute, Amsterdam, The Netherlands
d OLV Vattikuti Robotic Surgery Institute, Aalst, Belgium
Corresponding author. MRC Centre for Transplantation, King's College London, Guy's Hospital, London, SE1 9RT, UK. Tel. +44 0 20 7188 5906.
© 2016 European Association of Urology, Published by Elsevier B.V.