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Our understanding and use of simulation based training has evolved from simply practicing or learning performance in an accurate re-creation of the operating room as first envisaged by anaesthetist simulation pioneers. The efficacy of simulation training has been quantitatively demonstrated in prospective, randomized, double blinded studies. Simulation training models used in these studies have varied from bespoke models for training intra-corporeal suturing skills, VR emulation models for basic laparoscopic skill acquisition through to full physics VR simulations for the learning of endovascular skills. The understanding of why specific simulation models are effective needs to be better understood by trainers, researchers and engineers if simulation based training is to deliver on its potential for more advanced skills training but more importantly for the acquisition of procedural wisdom. This development will require a better understanding and more forthright approach to the issue of simulation fidelity. [ABSTRACT FROM AUTHOR]

High profile error cases and reduced work hours have forced medicine to consider new approaches to training. Simulation-based learning for the acquisition and maintenance of skills has a growing role to play. Considerable advances have been made during the last 20 years on how simulation should be used optimally. Simulation is also more than a technology learning experience for supplanting the traditional approach of repeated practice. Research has shown that simulation works best when it is integrated into a curriculum. Learning is optimal when trainees receive metric-based feedback on their performance. Metrics should unambiguously characterize important aspects of procedure or skill performance. They are developed from a task analysis of the procedure or skills to be learned. The outcome of the task analysis should also shape how the simulation looks and behaves. Metric-based performance characterization can be used to establish a benchmark (i.e., a level of proficiency) which trainees must demonstrate before training progression. This approach ensures a more homogeneous skill-set in graduating trainees and can be applied to any level of training. Prospective, randomized and blinded clinical studies have shown that trainees who acquired their skills to a level of proficiency on a simulator in the skills laboratory perform significantly better in vivo in comparison to their traditionally trained colleagues. The Food and Drug Administration in the USA and the Department of Health in the UK have candidly indicated that they see an emergent and fundamental role for simulation- based training. Although a simulation-based approach to medical education and training may be conceptually and intellectually appealing it represents a paradigm shift in how doctors are educated and trained. [ABSTRACT FROM AUTHOR]

Summary: Objective: The objective of this study was to develop and validate a transparent, fair and objective assessment programme for the selection of surgical trainees into higher surgical training (HST) in plastic surgery in the Republic of Ireland. Methods: Thirty-four individuals applied for HST in plastic surgery at the Royal College of Surgeons in Ireland (RCSI) in the academic years 2005–2006 and 2006–2007. Eighteen were short-listed for interview and further assessment. All applicants were required to report on their undergraduate educational performance and their postgraduate professional development. Short-listed applicants completed validated objective assessment simulations of surgical skills, an interview and assessment of their suitability for a career in surgery. Results: When applicants'' short-listing scores were combined with their interview scores and assessment of their suitability for a career in surgery, individuals who were selected for HST in plastic surgery performed significantly better than those who were not (P <0.002). However, when the assessment of technical skills scores were added the significance level of this difference increased further (P <0.0001) as did the statistical power of the difference to 99.9%, thus increasing the robustness of the selection package. Conclusion: The results from this study suggest that the assessment protocol we used to select individuals for HST in plastic surgery reliably and statistically significantly discriminated between the performances of candidates. [Copyright &y& Elsevier]

Computer‐based learning environments create the possibility of dynamic adaptation to address learner capabilities and user performance. Software algorithms, code‐named Smart Tutor, for motor skill learning were developed and applied to an abstract environment for laparoscopic surgery (RapidFire). Smart Tutor dynamically adjusts the environment to minimize frustration and optimize learning conditions for all learners. This study compared the first generation RapidFire / Smart Tutor (RF / ST) to the Minimal Invasive Surgery Trainer Virtual Reality (MIST VR) system for laparoscopic performance improvement and level of frustration. Two groups of novice laparoscopic learners were assessed by pre‐ and post‐ training paper cutting exercise and subjective surveys. Users of both systems showed improvement of laparoscopic skills as measured by the paper cutting exercises. No differences were shown between groups for level of improvement. However, a significant difference was seen in the subjective ratings on the post‐training survey with less frustration for the RF / ST training group. Important information was acquired for refinements of the Smart Tutor algorithms. [ABSTRACT FROM AUTHOR]

Purpose: To create and determine face validity and content validity of arthroscopic rotator cuff repair (ARCR) performance metrics, to confirm construct validity of the metrics coupled with a cadaveric shoulder, and to establish a performance benchmark for the procedure on a cadaveric shoulder.Methods: Five experienced arthroscopic shoulder surgeons created step, error, and sentinel error metrics for an ARCR. Fourteen shoulder arthroscopy faculty members from the Arthroscopy Association of North America formed the modified Delphi panel to assess face and content validity. Eight Arthroscopy Association of North America shoulder arthroscopy faculty members (experienced group) were compared with 9 postgraduate year 4 or 5 orthopaedic residents (novice group) in their ability to perform an ARCR. Instructions were given to perform a diagnostic arthroscopy and a 2-anchor, 4-simple suture repair of a 2-cm supraspinatus tear. The procedure was videotaped in its entirety and independently scored in blinded fashion by trained, paired reviewers.Results: Delphi panel consensus for 42 steps and 66 potential errors was obtained. Overall performance assessment showed a mean inter-rater reliability of 0.93. Novice surgeons completed 17% fewer steps (32.1 vs 37.5, P = .001) and enacted 2.5 times more errors than the experienced group (6.21 vs 2.5, P = .012). Fifty percent of the experienced group members and none of the novice group members achieved the proficiency benchmark of a minimum of 37 steps completed with 3 or fewer errors.Conclusions: Face validity and content validity for the ARCR metrics, along with construct validity for the metrics and cadaveric shoulder, were verified. A proficiency benchmark was established based on the mean performance of an experienced group of arthroscopic shoulder surgeons.Clinical Relevance: Validated procedural metrics combined with the use of a cadaveric shoulder can be used to accurately assess the performance of an ARCR. [ABSTRACT FROM AUTHOR]

Objective Methods Results Conclusion To develop performance metrics that objectively define a reference approach to a transurethral resection of bladder tumours (TURBT) procedure, seek consensus on the performance metrics from a group of international experts.The characterisation of a reference approach to a TURBT procedure was performed by identifying phases and explicitly defined procedure events (i.e., steps, errors, and critical errors). An international panel of experienced urologists (i.e., Delphi panel) was then assembled to scrutinise the metrics using a modified Delphi process. Based on the panel's feedback, the proposed metrics could be edited, supplemented, or deleted. A voting process was conducted to establish the consensus level on the metrics. Consensus was defined as the panel majority (i.e., >80%) agreeing that the metric definitions were accurate and acceptable. The number of metric units before and after the Delphi meeting were presented.A core metrics group (i.e., characterisation group) deconstructed the TURBT procedure. The reference case was identified as an elective TURBT on a male patient, diagnosed after full diagnostic evaluation with three or fewer bladder tumours of ≤3 cm. The characterisation group identified six procedure phases, 60 procedure steps, 43 errors, and 40 critical errors. The metrics were presented to the Delphi panel which included 15 experts from six countries. After the Delphi, six procedure phases, 63 procedure steps, 47 errors, and 41 critical errors were identified. The Delphi panel achieved a 100% consensus.Performance metrics to characterise a reference approach to TURBT were developed and an international panel of experts reached 100% consensus on them. This consensus supports their face and content validity. The metrics can now be used for a proficiency‐based progression training curriculum for TURBT. [ABSTRACT FROM AUTHOR]

The European Society of Coloproctology (ESCP) has released guidelines on training in robotic colorectal surgery to standardize training and assessment methods in this field. The guidelines address topics such as knowledge and technical skills required, assessment of competency and proficiency, and the need for further research. The recommendations are based on a literature review and expert opinion, with some supported by low-quality evidence. The guidelines recommend the use of simulation training and in-person mentoring, but acknowledge limited evidence on their effects on patient outcomes. Further research is needed to determine the impact of training methods on patient outcomes and establish best practices in robotic colorectal surgery training. [Extracted from the article]

The prevalence of renal cell carcinoma (RCC) is increasing due to advanced imaging techniques. Surgical resection is the standard treatment, involving complex radical and partial nephrectomy procedures that demand extensive training and planning. Furthermore, artificial intelligence (AI) can potentially aid the training process in the field of kidney cancer. This review explores how artificial intelligence (AI) can create a framework for kidney cancer surgery to address training difficulties. Following PRISMA 2020 criteria, an exhaustive search of PubMed and SCOPUS databases was conducted without any filters or restrictions. Inclusion criteria encompassed original English articles focusing on AI's role in kidney cancer surgical training. On the other hand, all non-original articles and articles published in any language other than English were excluded. Two independent reviewers assessed the articles, with a third party settling any disagreement. Study specifics, AI tools, methodologies, endpoints, and outcomes were extracted by the same authors. The Oxford Center for Evidence-Based Medicine's evidence levels were employed to assess the studies. Out of 468 identified records, 14 eligible studies were selected. Potential AI applications in kidney cancer surgical training include analyzing surgical workflow, annotating instruments, identifying tissues, and 3D reconstruction. AI is capable of appraising surgical skills, including the identification of procedural steps and instrument tracking. While AI and augmented reality (AR) enhance training, challenges persist in real-time tracking and registration. The utilization of AI-driven 3D reconstruction proves beneficial for intraoperative guidance and preoperative preparation. Artificial intelligence (AI) shows potential for advancing surgical training by providing unbiased evaluations, personalized feedback, and enhanced learning processes. Yet challenges such as consistent metric measurement, ethical concerns, and data privacy must be addressed. The integration of AI into kidney cancer surgical training offers solutions to training difficulties and a boost to surgical education. However, to fully harness its potential, additional studies are imperative. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To assess the face and content validity of a novel, full physics, full procedural, virtual reality simulation housed in a hybrid procedure suite. Methods and Materials: After completing 60 minutes of hands-on training in uterine artery embolization and coronary angioplasty, 24 radiologists and 18 cardiologists with mean 10 years of endovascular experience assessed the functionality of a comprehensive hybrid procedure suite simulation (Orcamp; Orzone, Gothenburg, Sweden). Results: C-arm and operating table functionality and realism were reliably (α = 0.0.89–0.92) rated highly (80/100). Performance realism of the catheter, guide wire, fluoroscopy image, electrocardiogram, and vital signs readout also reliably and statistically significantly predicted subjects'' overall positive assessment (mean = 87/100) of the simulation experience in a multiple regression model (α = .83; r = 0.85 and r 2 = 0.67; P < .0001). Conclusions: This study reports a quantitative evaluation of a comprehensive simulation of an authentic procedure suite for image-guided intravascular procedures. This new facility affords the opportunity for trainers to provide higher fidelity training of operative technical, procedural, and management skills in the realistic context of a complete procedure suite with all its complexities and potential distractions. [Copyright &y& Elsevier]

Objective: To determine whether proficiency‐based progression (PBP) training leads to better robotic surgical performance compared to traditional training (TT), given that the value of PBP training for learning robotic surgical skills is unclear. Materials and Methods: The PROVESA trial is a multicentric, prospective, randomized and blinded clinical study comparing PBP training with TT for robotic suturing and knot‐tying anastomosis skills. A total of 36 robotic surgery‐naïve junior residents were recruited from 16 training sites and 12 residency training programmes. Participants were randomly allocated to metric‐based PBP training or the current standard of care TT, and compared at the end of training. The primary outcome was percentage of participants reaching the predefined proficiency benchmark. Secondary outcomes were the numbers of procedure steps and errors made. Results: Of the group that received TT, 3/18 reached the proficiency benchmark versus 12/18 of the PBP group (i.e. the PBP group were ~10 times as likely to demonstrate proficiency [P = 0.006]). The PBP group demonstrated a 51% reduction in number of performance errors from baseline to the final assessment (18.3 vs 8.9). The TT group demonstrated a marginal improvement (15.94 vs 15.44) in errors made. Conclusions: The PROVESA trial is the first prospective randomized controlled trial on basic skills training in robotic surgery. Implementation of a PBP training methodology resulted in superior surgical performance for robotic suturing and knot‐tying anastomosis performance. Compared to TT, better surgical quality could be obtained by implementing PBP training for basic skills in robotic surgery. [ABSTRACT FROM AUTHOR]

Formula One (F1) is a high-performance competitive sport that relies heavily on advanced technologies driven by a driver. Not only did the GB Cycling team win the Tour de France ahead of their set target, but the British Cycling team has also become the leading team in the world. Learning has evolved, from text-based learning and apprentice model to eLearning and simulation including virtual reality (VR). [Extracted from the article]

The introduction of robot-assisted surgical devices requires the application of objective performance metrics to verify performance levels. To develop and validate (face, content, response process, and construct) the performance metrics for a robotic dissection task using a chicken model. In a procedure characterization, we developed the performance metrics (i.e., procedure steps, errors, and critical errors) for a robotic dissection task, using a chicken model. In a modified Delphi panel, 14 experts from four European Union countries agreed on the steps, errors, and critical errors (CEs) of the task. Six experienced surgeons and eight novice urology surgeons performed the robotic dissection task twice on the chicken model. In the Delphi meeting, 100% consensus was reached on five procedure steps, 15 errors and two CEs. Novice surgeons took 20 min to complete the task on trial 1 and 14 min during trial two, whereas experts took 8.2 min and 6.5 min. On average, the Expert Group completed the task 56% faster than the Novice Group and made 46% fewer performance errors. Sensitivity and specificity for procedure errors and time were excellent to good (i.e., 1.0-0.91) but poor (i.e., 0.5) for step metrics. The mean interrater reliability for the assessments by two robotic surgeons was 0.91 (Expert Group inter-rater reliability = 0.92 and Novice Group = 0.9). We report evidence which supports the demonstration of face, content, and construct validity for a standard and replicable basic robotic dissection task on the chicken model. • Dry-laboratory technical skills training may represent a fundamental step to improve manual dexterity and acquisition of basic robotic surgical skills. • Standardized and objective performance metrics can facilitate the implementation of basic skills training. • A proficiency based progression approach to training can lead to a more homogeneous skill set in graduating trainees and can be applied to any level of training. • We develop and present evidence of the face, content, and construct validity for the performance metrics for robotic dissection task, using the avian model. [ABSTRACT FROM AUTHOR]

Introduction: Identifying objective performance metrics for surgical training in orthopedic surgery is imperative for effective training and patient safety. The objective of this study was to determine if an internationally agreed, metric-based objective assessment of video recordings of an unstable pertrochanteric 31A2 intramedullary nailing procedure distinguished between the performance of experienced and novice orthopedic surgeons.Materials and Methods: Previously agreed procedure metrics (i.e., 15 phases of the procedure, 75 steps, 88 errors, and 28 sentinel errors) for a closed reduction and standard cephalomedullary nail fixation with a single cephalic element of an unstable pertrochanteric 31A2 fracture. Experienced surgeons trained to assess the performance metrics with an interrater reliability (IRR) > 0.8 assessed 14 videos from 10 novice surgeons (orthopaedic residents/trainees) and 20 videos from 14 experienced surgeons (orthopaedic surgeons) blinded to group and procedure order.Results: The mean IRR of procedure assessments was 0.97. No statistically significant differences were observed between the two groups for Procedure Steps, Errors, Sentinel Errors, and Total Errors. A small number of Experienced surgeons made a similar number of Total Errors as the weakest performing Novices. When the scores of each group were divided at the median Total Error score, large differences were observed between the Experienced surgeons who made the fewest errors and the Novices making the most errors (p < 0.001). Experienced surgeons who made the most errors made significantly more than their Experienced peers (p < 0.003) and the best performing Novices (p < 0.001). Error metrics assessed with Area Under the Curve demonstrated good to excellent Sensitivity and Specificity (0.807-0.907).Discussion: Binary performance metrics previously agreed by an international Delphi meeting discriminated between the objectively assessed video-recorded performance of Experienced and Novice orthopedic surgeons when group scores were sub-divided at the median for Total Errors. Error metrics discriminated best and also demonstrated good to excellent Sensitivity and Specificity. Some very experienced surgeons performed similar to the Novice group surgeons that made most errors.Conclusions: The procedure metrics used in this study reliably distinguish Novice and Experienced orthopaedic surgeons' performance and will underpin quality-assured novice training. [ABSTRACT FROM AUTHOR]

Background: To improve patient safety, there is an imperative to develop objective performance metrics for basic surgical skills training in robotic surgery. Objective: To develop and validate (face, content, and construct) the performance metrics for robotic suturing and knot tying, using a chicken anastomotic model. Design, setting and participants: Study 1: In a procedure characterization, we developed the performance metrics (i.e., procedure steps, errors, and critical errors) for robotic suturing and knot tying, using a chicken anastomotic model. In a modified Delphi panel of 13 experts from four EU countries, we achieved 100% consensus on the five steps, 18 errors and four critical errors (CE) of the task. Study 2: Ten experienced surgeons and nine novice urology surgeons performed the robotic suturing and knot tying chicken anastomotic task. The mean inter-rater reliability for the assessments by two experienced robotic surgeons was 0.92 (95% CI, 0.9–0.95). Novices took 18.5 min to complete the task and experts took 8.2 min. (p = 0.00001) and made 74% more objectively assessed performance errors than the experts (p = 0.000343). Conclusions: We demonstrated face, content, and construct validity for a standard and replicable basic anastomotic robotic suturing and knot tying task on a chicken model. Patient summary: Validated, objective, and transparent performance metrics of a robotic surgical suturing and knot tying tasks are imperative for effective and quality assured surgical training. [ABSTRACT FROM AUTHOR]