1.3.1 Introduction

The traditional Halsted model of surgical training, ‘see one, do one, teach one’, has become increasingly difficult to implement. The introduction of new surgical technologies has been accompanied by more challenging surgical procedures for a more complex patient population. In addition, reduction in working hours, fear of litigation, outcome reporting, and pressures to utilise costly operating room (OR) resources more efficiently have led to significant changes in the curricula for surgical training.

Recognising modern changes to surgical practice, surgical simulation has evolved over the last two decades as an education tool that seeks to bridge the gap between the initial phases of a procedural learning curve and the OR. The aim of simulation is to aid the acquisition of specific skills and improve both competence and confidence. Simulation training provides a safe environment for repetitive practice of different surgical skills free from risk of harm to patients and a means of providing trainees with immediate feedback and the opportunity to train to a predetermined expert proficiency. This is exemplified by the theory of ‘deliberate practice’ [1], which dictates that to achieve ‘expertise’, multiple repetitions of a skill and the provision of constructive feedback to ensure the skill is being learned correctly is required. Surgical simulation provides the trainee with an opportunity to repeatedly perform a specific skill, or set of skills, in a low‐risk environment away from patients, thus allowing for a safe environment where mistakes can occur. The trainee is then able to learn how to correct mistakes, problem solve, and develop the confidence to deal with complications when they occur in real‐world settings without it being experienced for the first time. Furthermore, simulation allows the trainer to provide timely and constructive formative or summative feedback based on trainee performance, ensuring acquisition of competency.

1.3.2 History of Simulation in Medicine

Surgical simulation has been around long before complex, high‐fidelity, virtual‐reality devices were developed. Traditional basic surgical skill training was done on oranges to practise suturing skills or on a table leg for surgical knots. Currently, synthetic models have greatly improved in look, feel, and tactile behaviours, and many medical device companies now produce a range of general and specialist surgical skills models from high‐fidelity materials. However, the earliest contribution to the field of surgical simulation was by the ancient Indian surgeon, Sushruta Samhita [2]. He advocated the use of cadavers and synthetic models for practice prior to surgery. He taught technical skills using experimental models that included probing on worm‐eaten wood and incising vegetables, such as watermelons and cucumbers. The first modern skills ‘simulator’ was produced in 1928 when Edwin Link created a pilot trainer, which allowed trainee pilots to learn important aeronautical manoeuvres whilst remaining on the ground, making learning to fly cheaper, safer, and more accessible. By the end of World War II in 1945, there were 6271 Link Trainer simulators in circulation [3]. One of the earliest examples of medical simulation was a foetal and human pelvis bone model used by Madame du Coudray to train midwives in eighteenth‐century France [4]. In 1960, the first medical simulator, a resuscitation training manikin was developed when a girl drowned in the River Seine in Paris. This model, initially created by the toy maker Asmund S. Laerdal, has now become the Resusci Anne, which is still widely used today by first aid and life support courses to teach mouth to mouth resuscitation and airway and breathing assessments. In the 1960s, Abrahamson and Denson developed the Sim One, resuscitation trainer. This could simulate breathing, heart rate, pulses, and blood pressure and had eyes and a mouth that could open and close. Further developments in high‐fidelity simulators had to wait until the 1980s. The Comprehensive Anaesthetic Simulation Environment (CASE) and the Gainesville Anaesthetic Simulator (GAS) utilised concepts developed by the aviation industry to teach anaesthetic crisis management using team‐based simulated scenarios. Modern high‐fidelity training focuses on the technical and nontechnical skills (NTS) required to make a safe, effective surgeon and also add a realistic environment for simulations.

In 1989, the US computer scientist Jaron Lanier took the concept of virtual, describing something that appeared to exist without actually existing, and combined it with the term ‘reality’, meaning something that is observable and measurable as opposed to the imaginary or delusional [5]. Virtual‐reality (VR) surgical simulators began to grow in the 1990s beginning with lower limb reconstruction simulator (Delph et al.) to the late 1990s where a range of operations could be catered for by this technology. Evidence for its safety and effectiveness began to emerge; in particular, Seymour et al. showed that trainees could significantly reduce their procedure times to perform a cholecystectomy by 29% and were five times less likely to injure the gallbladder after using a VR trainer [6]. In 2004, the US Food and Drug Administration approved the introduction of the VR carotid stent procedure into their training programme. For the first time, trainees had to prove themselves on a competency‐based task to be allowed to perform a human procedure [7]. With the development of web‐based simulations, such teaching modalities are becoming cheaper and more accessible. However, the future of surgical education does not solely lie with one form of simulation, but in the combination of different modalities integrated into the curriculum.

1.3.3 Simulation Modalities

Surgical simulator training can be separated into four broad categories: physical (mechanical) simulators, animal, cadaveric, and virtual reality (VR). Physical simulator models range from part task trainers (e.g. laparoscopic box trainers) to procedure‐specific trainers (e.g. ureteroscopy trainers). These are often more suitable to novice or intermediate trainees. Because of the lack of clinical variability and the inability to provide individualised proficiency‐based variations in complexity, inanimate surgical simulation models often decrease in utility for advanced‐level training. Animal and cadaveric surgical training has more significant cost and ethical and legislative implications; however, this is offset by providing improved contextual fidelity and opportunities to practise a whole procedure. To maximise this finite resource, it is paramount that animal‐model training forms part of a well‐designed, comprehensive curriculum with clear learning objectives.

VR simulators have been the mainstay of training in aviation and nuclear industries for decades, being utilised for teaching, evaluation, certification, and recertification purposes. Tasks are performed on a computer‐based platform and artificially generated virtual environment. Improvements in computer processing have led to more realistic and sensitive VR simulators, which are now capable of providing statistical feedback on the surgeon’s performance, a quality that is not shared by mechanical or cadaveric simulator trainers. This feature also eliminates the need for expert faculty present during the entirety of training and promotes a self‐directed learning environment. The improvements in modern software allow for clinical variations to be built into the simulator, improving the training content delivered. VR simulators have been validated as a training tool with shown educational impact and content, context, and construct validity [8]. The main challenge to programme directors has been justifying the steep costs because little data currently shows any cost effectiveness.

Simulation training also encompasses simulated clinical scenarios such as mock OR team‐training sessions. These high‐fidelity facilities are used in the development and assessment of crisis management skills and nontechnical skills (NTS) training such as leadership, management, and communication. With the majority of surgical errors as a result of poor communication [9], increasing attention has been directed towards simulated OR facilities to improve pre‐, intra‐, and postoperative communication between the surgical multidisciplinary team.

1.3.4 Simulation in Urology

Urology remains at the forefront of surgical innovation, particularly in the field of minimally invasive surgery, which includes endoscopy, laparoscopy, and robotics. As the nature of practice is changing, so are the definitions and requirements of competency [10]. Fundamental to this change in practise is patient safety, which must not be compromised. A competent urologist must have a plethora of attributes to practice in the modern surgical environment including excellent technical, team‐working, communication, leadership, and decision‐making skills. Urology has embraced simulation training, both in its development and application.

1.3.5 Endourology Simulation

Over the last few decades, the applications of endoscopic techniques have expanded. The development of ureterorenoscopy (URS) and percutaneous nephrolithotomy (PCNL), superseding open stone surgery, and novel bladder outflow obstruction (BOO) techniques challenging the gold standard transurethral resection of the prostate (TURP), such as Holium enucleation and Green light laser, are growing. This has necessitated the concomitant need for training and qualification in the established and newer techniques. In response to this demand, there have been a range of endourological simulators focusing on core procedures, including urethrocystoscopy, URS, transurethral resection of a bladder tumour (TURBT), TURP, and percutaneous access (Table 1.3.1). The most extensively studied models are the URO Mentor (Simbionix); a computer‐based VR model offering semi‐rigid and flexible urethrocystoscopy and URS modules and the Uro‐Scopic trainer (Limbs & Things, Bristol UK), a high‐fidelity bench model permitting use of real OR instruments in urethrocystoscopy and URS. Three prospective randomised controlled trials have supported these two ureteroscopy simulators in terms of face, content, and construct validity, with training on the URO Mentor showing improvements in surgical performance in the OR [11–14]. There are only two available simulators for TURBT training, with few validation studies. This may be related to difficulties in developing simulators that can encompass the variation of tumours in patients. Eight TURP, nine URS, eight urethrocystoscopy, and nine percutaneous access models have been developed. Universities have developed the majority of these, in particular the TURP and percutaneous access models, while ureteroscopy simulation has received greater interest from the industry.

Limitations in endourological‐simulator validity studies relate to small participant numbers and the use of time as the objective parameter to assess competency. Although time is an easy parameter to measure, it is not necessarily a sign of competency, and more focus is required to objectively measure outcomes and the various steps within a procedure. For example, TURP parameters should include volume of prostate resected, blood loss, and associated injuries such as ureteric orifice or sphincter damage. With the majority of endourological simulator literature in the form of descriptive texts as opposed to validity studies, coupled with the lack of randomised controlled studies, none of the urology training models described and researched can be said to have proven validity for use in specialty training. There is also a lack in the development and research of simulation devices that focus on novel bladder outflow obstruction procedures such as Green Light Laser and Holium Enucleation.

1.3.6 Laparoscopy Simulation

There are two laparoscopic urology simulators that have undergone validation studies: Procedieus MIST VR (Mentice) and the LAP mentor (Symbionix) (Table 1.3.2). Currently these platforms have only been developed and researched for training in laparoscopic nephrectomy (LN). Wijn et al. assessed the construct validity of the LN VR simulator (Mentice, Gothenburg, Sweden) [15].

1.3.7 Robotic Surgery Simulation

Since its first application in 2000 by Binder and Kramer, the uptake of robotic surgery has been rapid. This ever‐evolving surgical technique has cemented itself as the gold standard for the removal of the prostate gland. There are six commercially available robotic simulators all of which are VR platforms (Table 1.3.3): Robotic Surgical Simulator (RoSS™), SimSurgery Educational Platform (SEP), ProMIS^®, Mimic dV‐Trainer (MdVT), Surgical SIM RSS, and the da Vinci® Skills Simulator™ (dVSS) (Figure 1.3.1). The biomechanics lab at the University of Nebraska at Omaha have also developed their own VR simulator. These platforms aim to establish the basic principles of robotic operative techniques, namely, endowrist manipulation, camera and clutching, needle control and driving, energy, and dissection control. In terms of validation, all of the simulators except RoSS have demonstrated face, content, and construct validity, but the numbers in these studies remain small. Educational impact has been shown in studies and in all commercially available simulators except SEP. Evidence of criterion validity, such as predictive or concurrent validity, is sparse. Other parameters, such as inter‐rater and inter‐item reliability, feasibility, acceptability, and cost effectiveness of the simulation platforms were not evaluated by any of the studies. Similarly no group has validated the use of animal models and freshly frozen cadavers and structured skills training based on observation for robotic surgery. There is a distinct lack of comparative studies between the different simulators. The current body of evidence does not identify any one simulator being more effective in training the next generation of robotic surgeons than another. Each platform has the capability to train and assess a range of different robotic skills fundamental to the technique. Unlike the dVSS, the MdVT and RoSS platforms have user interfaces that are similar to, but not exact duplicates of, the dVSS console used in clinical practice. The ProMIS simulator enables virtual and physical reality to be used together and has been investigated in the laparoscopic setting previously. A randomised control trial by Feifer et al. represents the highest level of evidence for any of the simulators currently available [19]. Their study showed that the use of ProMIS and LapSim simulators in conjunction with each other could improve robotic console performance. Interestingly, the LapSim group showed no improvement, and it was therefore not clear what contribution LapSim had on the overall improvement seen when both simulators were used in conjunction. Despite SEP’s level of validation, its biggest disadvantage lies in the fact that the images are not three dimensional (3D), a fundamental concept pertaining to robotic compared with laparoscopic surgery. Further studies or perhaps even hardware upgrades to convert the two‐dimensional (2D) simulator into a 3D platform are therefore warranted.

The majority of robotic surgical simulators focus on prostatectomy training. There is an ever‐growing role for robotic cystectomy, radical nephrectomy, and partial nephrectomy. As such, current simulators will require software updates, and in future simulator, developers will need to consider these advances in their designs.