Partial nephrectomy series using Versius robotic surgical system: technique and outcomes of an initial experience.

Partial nephrectomy (PN) represents a procedure where the use of a robot has further enabled successful completion of this complex surgery. The results of this procedure using Versius Robotic Surgical System (VRSS) still need to be evaluated. Our working group described the technique and reported the initial results of a series of PN using VRSS. We presented our setting, surgical technique and outcomes for PN, using VRSS. Between 2022 and 2023, 15 patients underwent PN performed by two surgeons in two different centers. Fifteen patients underwent PN. The median lesion size identified on preoperative imaging was 4 (IQR 2.3-5) cm. Median PADUA score was 8 (IQR 7-9). Two procedures were converted to radical nephrectomy for enhanced oncological disease control. Of the 13 nephrectomies that were completed as partial, 7 were performed clampless and 6 with warm ischemia clamping. Median clamping time was 10 (IQR 9-11) minutes. No procedure was converted to open. Median blood loss was 200 (IQR 100-250) mL. Median total operative time was 105 (IQR 100-110) minutes. Median console time was 75 (IQR 66-80) minutes. Median set-up time was 13 (IQR 12-14) minutes. No intraoperative complications were reported. The median hospitalization time was 4 (IQR 3.5-4) days. None of the patients were transfused and none of the patients required readmission. In a pathology report, one patient had a positive surgical margin. Our initial experience suggests that performing PN using VRSS is feasible with good short-term outcomes.

Technical and ethical considerations in telesurgery.

Telesurgery, a cutting-edge field at the intersection of medicine and technology, holds immense promise for enhancing surgical capabilities, extending medical care, and improving patient outcomes. In this scenario, this article explores the landscape of technical and ethical considerations that highlight the advancement and adoption of telesurgery. Network considerations are crucial for ensuring seamless and low-latency communication between remote surgeons and robotic systems, while technical challenges encompass system reliability, latency reduction, and the integration of emerging technologies like artificial intelligence and 5G networks. Therefore, this article also explores the critical role of network infrastructure, highlighting the necessity for low-latency, high-bandwidth, secure and private connections to ensure patient safety and surgical precision. Moreover, ethical considerations in telesurgery include patient consent, data security, and the potential for remote surgical interventions to distance surgeons from their patients. Legal and regulatory frameworks require refinement to accommodate the unique aspects of telesurgery, including liability, licensure, and reimbursement. Our article presents a comprehensive analysis of the current state of telesurgery technology and its potential while critically examining the challenges that must be navigated for its widespread adoption.

Evaluation of objective tools and artificial intelligence in robotic surgery technical skills assessment: a systematic review.

BACKGROUND: There is a need to standardize training in robotic surgery, including objective assessment for accreditation. This systematic review aimed to identify objective tools for technical skills assessment, providing evaluation statuses to guide research and inform implementation into training curricula. METHODS: A systematic literature search was conducted in accordance with the PRISMA guidelines. Ovid Embase/Medline, PubMed and Web of Science were searched. Inclusion criterion: robotic surgery technical skills tools. Exclusion criteria: non-technical, laparoscopy or open skills only. Manual tools and automated performance metrics (APMs) were analysed using Messick's concept of validity and the Oxford Centre of Evidence-Based Medicine (OCEBM) Levels of Evidence and Recommendation (LoR). A bespoke tool analysed artificial intelligence (AI) studies. The Modified Downs-Black checklist was used to assess risk of bias. RESULTS: Two hundred and forty-seven studies were analysed, identifying: 8 global rating scales, 26 procedure-/task-specific tools, 3 main error-based methods, 10 simulators, 28 studies analysing APMs and 53 AI studies. Global Evaluative Assessment of Robotic Skills and the da Vinci Skills Simulator were the most evaluated tools at LoR 1 (OCEBM). Three procedure-specific tools, 3 error-based methods and 1 non-simulator APMs reached LoR 2. AI models estimated outcomes (skill or clinical), demonstrating superior accuracy rates in the laboratory with 60 per cent of methods reporting accuracies over 90 per cent, compared to real surgery ranging from 67 to 100 per cent. CONCLUSIONS: Manual and automated assessment tools for robotic surgery are not well validated and require further evaluation before use in accreditation processes.PROSPERO: registration ID CRD42022304901.

BACKGROUND: Robotic surgery is increasingly used worldwide to treat many different diseases. The robot is controlled by a surgeon, which may give them greater precision and better outcomes for patients. However, surgeons' robotic skills should be assessed properly, to make sure patients are safe, to improve feedback and for exam assessments for certification to indicate competency. This should be done by experts, using assessment tools that have been agreed upon and proven to work. AIM: This review's aim was to find and explain which training and examination tools are best for assessing surgeons' robotic skills and to find out what gaps remain requiring future research. METHOD: This review searched for all available studies looking at assessment tools in robotic surgery and summarized their findings using several different methods. FINDINGS AND CONCLUSION: Two hundred and forty-seven studies were looked at, finding many assessment tools. Further research is needed for operation-specific and automatic assessment tools before they should be used in the clinical setting.

Versius robotic surgical system: case series of 18 robot-assisted radical prostatectomies.

OBJECTIVE: To present the results of the first series of patients treated with robot-assisted radical prostatectomy (RARP) with the use of the Versius® Surgical System (CMR Surgical Ltd., Cambridge, UK). RARP has demonstrated better perioperative outcomes compared to open RP. However, RARP remains limited by platform availability and cost-effectiveness issues. The increasing competition from new robotic surgical platforms may further drive utilisation of the robotic approach. PATIENTS AND METHODS: Data were collected prospectively for our first 18 consecutive patients with localised prostate cancer who underwent RARP at our centre over a 3-month period. We recorded parameters, including patient demographics and perioperative outcomes. We also report our optimised set-up with regard to trocar placement, bedside unit placement, and overall composition of the operating room for this procedure. Describing the incremental modifications carried out to achieve reductions in set-up and operating times to optimise utilisation of the Versius system. RESULTS: The median (interquartile range [IQR]) set-up time was 8.5 (7-10) min. The median (IQR) console time was 201 (170-242) min. The median (IQR) operative time was 213 (186-266) min. The median (IQR) total surgery time was 226 (201-277) min. Bilateral pelvic lymphadenectomy median (IQR) time was 19 (17-20) min. There were no complications and/or limitations related to the use of the Versius system including need for conversion. There were no relevant intra- or postoperative complications at the 1-month follow-up related to the use of the Versius system. Patients were discharged after a median (IQR) of 4 (3.75-5) days, and the transurethral catheter was removed after a mean (range) of 8 (7-14) days. Continence at 2 months was achieved in 72.2% of the patients. CONCLUSIONS: Performing RARP using the Versius system is feasible, safe, and easily reproducible. Our set-up enables a rapid docking approach and efficient completion of the surgery.

Competency assessment for the Versius surgical robot: a validity investigation study of a virtual reality simulator-based test.

BACKGROUND: When introducing new equipment like robotic surgical systems, it is essential to ensure that surgeons have the basic skills before operating on patients. The objective was to investigate the validity evidence for a competency-based test for basic robotic surgical skills using the Versius® trainer. METHODS: We recruited medical students, residents, and surgeons which were classified based on data on clinical experience with the Versius system as either novices (0 min), intermediates (1-1000 min), or experienced (> 1000 min). All participants completed three rounds of eight basic exercises on the Versius trainer, where the first was used for familiarization and the final two for data analysis. The simulator automatically recorded data. Validity evidence was summarized using Messick's framework, and the contrasting groups' standard-setting method was used to define pass/fail levels. RESULTS: 40 participants completed the three rounds of exercises. The discriminatory abilities of all parameters were tested, and five exercises including relevant parameters were selected to be part of the final test. 26 of 30 parameters could differentiate between novices and experienced surgeons but none of the parameters could discriminate between the intermediate and experienced surgeons. Test-retest reliability analysis using Pearson's r or Spearman's rho showed only 13 of 30 parameters had moderate or higher reliability. Non-compensatory pass/fail levels were defined for each exercise and showed that all novices failed all the exercises and that most experienced surgeons either passed or nearly passed all five exercises. CONCLUSION: We identified relevant parameters for five exercises that could be used to assess basic robotic skills for the Versius robotic system and defined a credible pass/fail level. This is the first step in developing a proficiency-based training program for the Versius system.

Utilising an accelerated Delphi process to develop consensus on the requirement and components of a pre-procedural core robotic surgery curriculum.

Robot-assisted surgery (RAS) continues to grow globally. Despite this, in the UK and Ireland, it is estimated that over 70% of surgical trainees across all specialities have no access to robot-assisted surgical training (RAST). This study aimed to provide educational stakeholders guidance on a pre-procedural core robotic surgery curriculum (PPCRC) from the perspective of the end user; the surgical trainee. The study was conducted in four Phases: P1: a steering group was formed to review current literature and summarise the evidence, P2: Pan-Specialty Trainee Panel Virtual Classroom Discussion, P3: Accelerated Delphi Process and P4: Formulation of Recommendations. Forty-three surgeons in training representing all surgical specialties and training levels contributed to the three round Delphi process. Additions to the second- and third-round surveys were formulated based on the answers and comments from previous rounds. Consensus opinion was defined as ≥ 80% agreement. There was 100% response from all three rounds. The resulting formulated guidance showed good internal consistency, with a Cronbach alpha of > 0.8. There was 97.7% agreement that a standardised PPCRC would be advantageous to training and that, independent of speciality, there should be a common approach (95.5% agreement). Consensus was reached in multiple areas: 1. Experience and Exposure, 2. Access and context, 3. Curriculum Components, 4 Target Groups and Delivery, 5. Objective Metrics, Benchmarking and Assessment. Using the Delphi methodology, we achieved multispecialty consensus among trainees to develop and reach content validation for the requirements and components of a PPCRC. This guidance will benefit from further validation following implementation.

Autonomous surgical robotic systems and the liability dilemma.

Background: Advances in machine learning and robotics have allowed the development of increasingly autonomous robotic systems which are able to make decisions and learn from experience. This distribution of decision-making away from human supervision poses a legal challenge for determining liability. Methods: The iRobotSurgeon survey aimed to explore public opinion towards the issue of liability with robotic surgical systems. The survey included five hypothetical scenarios where a patient comes to harm and the respondent needs to determine who they believe is most responsible: the surgeon, the robot manufacturer, the hospital, or another party. Results: A total of 2,191 completed surveys were gathered evaluating 10,955 individual scenario responses from 78 countries spanning 6 continents. The survey demonstrated a pattern in which participants were sensitive to shifts from fully surgeon-controlled scenarios to scenarios in which robotic systems played a larger role in decision-making such that surgeons were blamed less. However, there was a limit to this shift with human surgeons still being ascribed blame in scenarios of autonomous robotic systems where humans had no role in decision-making. Importantly, there was no clear consensus among respondents where to allocate blame in the case of harm occurring from a fully autonomous system. Conclusions: The iRobotSurgeon Survey demonstrated a dilemma among respondents on who to blame when harm is caused by a fully autonomous surgical robotic system. Importantly, it also showed that the surgeon is ascribed blame even when they have had no role in decision-making which adds weight to concerns that human operators could act as "moral crumple zones" and bear the brunt of legal responsibility when a complex autonomous system causes harm.

A Delphi consensus statement for digital surgery.

The use of digital technology is increasing rapidly across surgical specialities, yet there is no consensus for the term 'digital surgery'. This is critical as digital health technologies present technical, governance, and legal challenges which are unique to the surgeon and surgical patient. We aim to define the term digital surgery and the ethical issues surrounding its clinical application, and to identify barriers and research goals for future practice. 38 international experts, across the fields of surgery, AI, industry, law, ethics and policy, participated in a four-round Delphi exercise. Issues were generated by an expert panel and public panel through a scoping questionnaire around key themes identified from the literature and voted upon in two subsequent questionnaire rounds. Consensus was defined if >70% of the panel deemed the statement important and <30% unimportant. A final online meeting was held to discuss consensus statements. The definition of digital surgery as the use of technology for the enhancement of preoperative planning, surgical performance, therapeutic support, or training, to improve outcomes and reduce harm achieved 100% consensus agreement. We highlight key ethical issues concerning data, privacy, confidentiality and public trust, consent, law, litigation and liability, and commercial partnerships within digital surgery and identify barriers and research goals for future practice. Developers and users of digital surgery must not only have an awareness of the ethical issues surrounding digital applications in healthcare, but also the ethical considerations unique to digital surgery. Future research into these issues must involve all digital surgery stakeholders including patients.

Artificial Intelligence Methods and Artificial Intelligence-Enabled Metrics for Surgical Education: A Multidisciplinary Consensus.

BACKGROUND: Artificial intelligence (AI) methods and AI-enabled metrics hold tremendous potential to advance surgical education. Our objective was to generate consensus guidance on specific needs for AI methods and AI-enabled metrics for surgical education. STUDY DESIGN: The study included a systematic literature search, a virtual conference, and a 3-round Delphi survey of 40 representative multidisciplinary stakeholders with domain expertise selected through purposeful sampling. The accelerated Delphi process was completed within 10 days. The survey covered overall utility, anticipated future (10-year time horizon), and applications for surgical training, assessment, and feedback. Consensus was agreement among 80% or more respondents. We coded survey questions into 11 themes and descriptively analyzed the responses. RESULTS: The respondents included surgeons (40%), engineers (15%), affiliates of industry (27.5%), professional societies (7.5%), regulatory agencies (7.5%), and a lawyer (2.5%). The survey included 155 questions; consensus was achieved on 136 (87.7%). The panel listed 6 deliverables each for AI-enhanced learning curve analytics and surgical skill assessment. For feedback, the panel identified 10 priority deliverables spanning 2-year (n = 2), 5-year (n = 4), and 10-year (n = 4) timeframes. Within 2 years, the panel expects development of methods to recognize anatomy in images of the surgical field and to provide surgeons with performance feedback immediately after an operation. The panel also identified 5 essential that should be included in operative performance reports for surgeons. CONCLUSIONS: The Delphi panel consensus provides a specific, bold, and forward-looking roadmap for AI methods and AI-enabled metrics for surgical education.

Ethical implications of AI in robotic surgical training: A Delphi consensus statement.

CONTEXT: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them. OBJECTIVES: To provide ethical guidance on developing narrow AI applications for surgical training curricula. We define standardised approaches to developing AI driven applications in surgical training that address current recognised ethical implications of utilising AI on surgical data. We aim to describe an ethical approach based on the current evidence, understanding of AI and available technologies, by seeking consensus from an expert committee. EVIDENCE ACQUISITION: The project was carried out in 3 phases: (1) A steering group was formed to review the literature and summarize current evidence. (2) A larger expert panel convened and discussed the ethical implications of AI application based on the current evidence. A survey was created, with input from panel members. (3) Thirdly, panel-based consensus findings were determined using an online Delphi process to formulate guidance. 30 experts in AI implementation and/or training including clinicians, academics and industry contributed. The Delphi process underwent 3 rounds. Additions to the second and third-round surveys were formulated based on the answers and comments from previous rounds. Consensus opinion was defined as ≥ 80% agreement. EVIDENCE SYNTHESIS: There was 100% response from all 3 rounds. The resulting formulated guidance showed good internal consistency, with a Cronbach alpha of >0.8. There was 100% consensus that there is currently a lack of guidance on the utilisation of AI in the setting of robotic surgical training. Consensus was reached in multiple areas, including: 1. Data protection and privacy; 2. Reproducibility and transparency; 3. Predictive analytics; 4. Inherent biases; 5. Areas of training most likely to benefit from AI. CONCLUSIONS: Using the Delphi methodology, we achieved international consensus among experts to develop and reach content validation for guidance on ethical implications of AI in surgical training. Providing an ethical foundation for launching narrow AI applications in surgical training. This guidance will require further validation. PATIENT SUMMARY: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them.In this paper we provide guidance on ethical implications of AI in surgical training.

Critical analysis of quality of life and cost-effectiveness of enhanced recovery after surgery (ERAS) for patient's undergoing urologic oncology surgery: a systematic review.

PURPOSE: Enhanced recovery after surgery (ERAS) protocols have been implemented across a variety of disciplines to improve outcomes. Herein we describe the impact of ERAS on quality of life (QOL) and cost for patients undergoing urologic oncology surgery. METHODS: A systematic literature search using the MEDLINE, Scopus, Clinictrials.gov, and Cochrane Review databases for studies published between 1946 and 2020 was conducted. Articles were reviewed and assigned a risk of bias by two authors and were included if they addressed ERAS and either QOL or cost-effectiveness for patients undergoing urologic oncology surgery. RESULTS: The literature search yielded a total of 682 studies after removing duplicates, of which 10 (1.5%) were included in the review. Nine articles addressed radical cystectomy, while one addressed ERAS and QOL for laparoscopic nephrectomy. Six publications assessed the impact of ERAS on QOL domains. Questionnaires used for assessment of QOL varied across studies, and timing of administration was heterogeneous. Overall, ERAS improved patient QOL during early phases of recovery within the realms of bowel function, physical/social/cognitive functioning, sleep and pain control. Costs were assessed in 4 retrospective studies including 3 conducted in the United States and one from China all addressing radical cystectomy. Studies demonstrated either decreased costs associated with ERAS as a result of decreased length of stay or no change in cost based on ERAS implementation. CONCLUSION: While limited studies are published on the subject, ERAS implementation for radical cystectomy and laparoscopic nephrectomy improved patient-reported QOL during early phases of recovery. For radical cystectomy, there was a decreased or neutral overall financial cost associated with ERAS. Further studies assessing QOL and cost-effectiveness over the entire global period of care in a variety of urologic oncology surgeries are warranted.

Definition of a Structured Training Curriculum for Robot-assisted Radical Cystectomy with Intracorporeal Ileal Conduit in Male Patients: A Delphi Consensus Study Led by the ERUS Educational Board.

Robot-assisted radical cystectomy (RARC) continues to expand, and several surgeons start training for this complex procedure. This calls for the development of a structured training program, with the aim to improve patient safety during RARC learning curve. A modified Delphi consensus process was started to develop the curriculum structure. An online survey based on the available evidence was delivered to a panel of 28 experts in the field of RARC, selected according to surgical and research experience, and expertise in running training courses. Consensus was defined as ≥80% agreement between the responders. Overall, 96.4% experts completed the survey. The structure of the RARC curriculum was defined as follows: (1) theoretical training; (2) preclinical simulation-based training: 5-d simulation-based activity, using models with increasing complexity (ie, virtual reality, and dry- and wet-laboratory exercises), and nontechnical skills training session; (3) clinical training: modular console activity of at least 6 mo at the host center (a RARC case was divided into 11 steps and steps of similar complexity were grouped into five modules); and (4) final evaluation: blind review of a video-recorded RARC case. This structured training pathway will guide a starting surgeon from the first steps of RARC toward independent completion of a full procedure. Clinical implementation is urgently needed. PATIENT SUMMARY: Robot-assisted radical cystectomy (RARC) is a complex procedure. The first structured training program for RARC was developed with the goal of aiding surgeons to overcome the learning curve of this procedure, improving patients' safety at the same time.

Robotic-assisted minimally invasive esophagectomy (RAMIE) for esophageal cancer training curriculum-a worldwide Delphi consensus study.

BACKGROUND: Structured training protocols can safely improve skills prior initiating complex surgical procedures such as robotic-assisted minimally invasive esophagectomy (RAMIE). As no consensus on a training curriculum for RAMIE has been established so far it is our aim to define a protocol for RAMIE with the Delphi consensus methodology. METHODS: Fourteen worldwide RAMIE experts were defined and were enrolled in this Delphi consensus project. An expert panel was created and three Delphi rounds were performed starting December 2019. Items required for RAMIE included, but were not limited to, virtual reality simulation, wet-lab training, proctoring, and continued monitoring and education. After rating performed by the experts, consensus was defined when a Cronbach alpha of ≥0.80 was reached. If ≥80% of the committee reached a consensus an item was seen as fundamental. RESULTS: All Delphi rounds were completed by 12-14 (86-100%) participants. After three rounds analyzing our 49-item questionnaire, 40 items reached consensus for a training curriculum of RAMIE. CONCLUSION: The core principles for RAMIE training were defined. This curriculum may lead to a wider adoption of RAMIE and a reduction in time to reach proficiency.

Expert Consensus Recommendations for Robotic Surgery Credentialing.

OBJECTIVE: To define criteria for robotic credentialing using expert consensus. BACKGROUND: A recent review of institutional robotic credentialing policies identified significant variability and determined current policies are largely inadequate to ensure surgeon proficiency and may threaten patient safety. METHODS: Twenty-eight national robotic surgery experts were invited to participate in a consensus conference. After review of available institutional policies and discussion, the group developed a 91 proposed criteria. Using a modified Delphi process the experts were asked to indicate their agreement with the proposed criteria in three electronic survey rounds after the conference. Criteria that achieved 80% or more in agreement (consensus) in all rounds were included in the final list. RESULTS: All experts agreed that there is a need for standardized robotic surgery credentialing criteria across institutions that promote surgeon proficiency. Forty-nine items reached consensus in the first round, 19 in the second, and 8 in the third for a total of 76 final items. Experts agreed that privileges should be granted based on video review of surgical performance and attainment of clearly defined objective proficiency benchmarks. Parameters for ongoing outcome monitoring were determined and recommendations for technical skills training, proctoring, and performance assessment were defined. CONCLUSIONS: Using a systematic approach, detailed credentialing criteria for robotic surgery were defined. implementation of these criteria uniformly across institutions will promote proficiency of robotic surgeons and has the potential to positively impact patient outcomes.

Virtual Interactive Surgical Skills Classroom: A Parallel-group, Non-inferiority, Adjudicator-blinded, Randomised Controlled Trial (VIRTUAL).

OBJECTIVE: This study evaluated the efficacy of virtual classroom training (VCT) in comparison to face-to-face training (FFT) and non-interactive computer-based learning (CBL) for basic surgical skills training. DESIGN: This was a parallel-group, non-inferiority, prospective randomised controlled trial with three intervention groups conducted in 2021. There were three intervention groups with allocation ratio 1:1:1. Outcome adjudicators were blinded to intervention assignment. Interventions consisted of 90-minute training sessions. VCT was delivered via the BARCO weConnect platform, FFT was provided in-person by expert instructors and CBL was carried out by participants independently. The primary outcome was post-intervention Objective Structured Assessment of Technical Skills score, adjudicated by two experts and adjusted for baseline proficiency. The assessed task was to place three interrupted sutures with hand-tied knots. SETTING: This multicentre study recruited from five medical schools in London. PARTICIPANTS: Inclusion criteria were medical student status and access to a personal computer and smartphone. One hundred fifty-nine eligible individuals applied online. Seventy-two participants were randomly selected and stratified by subjective and objective suturing experience prior to permuted block randomization. RESULTS: Twenty-four participants were allocated to each intervention, all were analysed per-protocol. The sample was 65.3% female with mean age 21.3 (SD 2.1). VCT was non-inferior to FFT (adjusted difference 0.44, 95% CI: -0.54 to 1.75, delta 0.675), VCT was superior to CBL (adjusted difference 1.69, 95% CI: 0.41-2.96) and FFT was superior to CBL (adjusted difference 1.25, 95% CI: 0.20-2.29). The costs per-attendee associated with VCT, FFT and CBL were £22.15, £39.69 and £16.33 respectively. Instructor hours used per student for VCT and FFT were 0.25 and 0.75, respectively. CONCLUSIONS: VCT provides greater accessibility and resource efficiency compared to FFT, with similar educational benefit. VCT has the potential to improve global availability and accessibility of surgical skills training.

An Assessment Tool to Provide Targeted Feedback to Robotic Surgical Trainees: Development and Validation of the End-To-End Assessment of Suturing Expertise (EASE).

Purpose: To create a suturing skills assessment tool that comprehensively defines criteria around relevant sub-skills of suturing and to confirm its validity. Materials and Methods: 5 expert surgeons and an educational psychologist participated in a cognitive task analysis (CTA) to deconstruct robotic suturing into an exhaustive list of technical skill domains and sub-skill descriptions. Using the Delphi methodology, each CTA element was systematically reviewed by a multi-institutional panel of 16 surgical educators and implemented in the final product when content validity index (CVI) reached ≥0.80. In the subsequent validation phase, 3 blinded reviewers independently scored 8 training videos and 39 vesicourethral anastomoses (VUA) using EASE; 10 VUA were also scored using Robotic Anastomosis Competency Evaluation (RACE), a previously validated, but simplified suturing assessment tool. Inter-rater reliability was measured with intra-class correlation (ICC) for normally distributed values and prevalence-adjusted bias-adjusted Kappa (PABAK) for skewed distributions. Expert (≥100 prior robotic cases) and trainee (<100 cases) EASE scores from the non-training cases were compared using a generalized linear mixed model. Results: After two rounds of Delphi process, panelists agreed on 7 domains, 18 sub-skills, and 57 detailed sub-skill descriptions with CVI ≥ 0.80. Inter-rater reliability was moderately high (ICC median: 0.69, range: 0.51-0.97; PABAK: 0.77, 0.62-0.97). Multiple EASE sub-skill scores were able to distinguish surgeon experience. The Spearman's rho correlation between overall EASE and RACE scores was 0.635 (p=0.003). Conclusions: Through a rigorous CTA and Delphi process, we have developed EASE, whose suturing sub-skills can distinguish surgeon experience while maintaining rater reliability.

Pituitary society expert Delphi consensus: operative workflow in endoscopic transsphenoidal pituitary adenoma resection.

PURPOSE: Surgical workflow analysis seeks to systematically break down operations into hierarchal components. It facilitates education, training, and understanding of surgical variations. There are known educational demands and variations in surgical practice in endoscopic transsphenoidal approaches to pituitary adenomas. Through an iterative consensus process, we generated a surgical workflow reflective of contemporary surgical practice. METHODS: A mixed-methods consensus process composed of a literature review and iterative Delphi surveys was carried out within the Pituitary Society. Each round of the survey was repeated until data saturation and > 90% consensus was reached. RESULTS: There was a 100% response rate and no attrition across both Delphi rounds. Eighteen international expert panel members participated. An extensive workflow of 4 phases (nasal, sphenoid, sellar and closure) and 40 steps, with associated technical errors and adverse events, were agreed upon by 100% of panel members across rounds. Both core and case-specific or surgeon-specific variations in operative steps were captured. CONCLUSIONS: Through an international expert panel consensus, a workflow for the performance of endoscopic transsphenoidal pituitary adenoma resection has been generated. This workflow captures a wide range of contemporary operative practice. The agreed "core" steps will serve as a foundation for education, training, assessment and technological development (e.g. models and simulators). The "optional" steps highlight areas of heterogeneity of practice that will benefit from further research (e.g. methods of skull base repair). Further adjustments could be made to increase applicability around the world.

Development and validation of non-guided bladder-neck and neurovascular-bundle dissection modules of the RobotiX-Mentor® full-procedure robotic-assisted radical prostatectomy virtual reality simulation.

BACKGROUND: Full-procedure virtual reality (VR) simulator training in robotic-assisted radical prostatectomy (RARP) is a new tool in surgical education. METHODS: Description of the development of a VR RARP simulation model, (RobotiX-Mentor®) including non-guided bladder neck (ngBND) and neurovascular bundle dissection (ngNVBD) modules, and assessment of face, content, and construct validation of the ngBND and ngNVBD modules by robotic surgeons with different experience levels. RESULTS: Simulator and ngBND/ngNVBD modules were rated highly by all surgeons for realism and usability as training tool. In the ngBND-task construct, validation was not achieved in task-specific performance metrics. In the ngNVBD, task-specific performance of the expert/intermediately experienced surgeons was significantly better than that of novices. CONCLUSIONS: We proved face and content validity of simulator and both modules, and construct validity for generic metrics of the ngBND module and for generic and task-specific metrics of the ngNVBD module.

Objective assessment of intraoperative skills for robot-assisted radical prostatectomy (RARP): results from the ERUS Scientific and Educational Working Groups Metrics Initiative.

OBJECTIVE: To develop and seek consensus from procedure experts on the metrics that best characterise a reference robot-assisted radical prostatectomy (RARP) and determine if the metrics distinguished between the objectively assessed RARP performance of experienced and novice urologists, as identifying objective performance metrics for surgical training in robotic surgery is imperative for patient safety. MATERIALS AND METHODS: In Study 1, the metrics, i.e. 12 phases of the procedure, 81 steps, 245 errors and 110 critical errors for a reference RARP were developed and then presented to an international Delphi panel of 19 experienced urologists. In Study 2, 12 very experienced surgeons (VES) who had performed >500 RARPs and 12 novice urology surgeons performed a RARP, which was video recorded and assessed by two experienced urologists blinded as to subject and group. Percentage agreement between experienced urologists for the Delphi meeting and Mann-Whitney U- and Kruskal-Wallis tests were used for construct validation of the newly identified RARP metrics. RESULTS: At the Delphi panel, consensus was reached on the appropriateness of the metrics for a reference RARP. In Study 2, the results showed that the VES performed ~4% more procedure steps and made 72% fewer procedure errors than the novices (P = 0.027). Phases VIIa and VIIb (i.e. neurovascular bundle dissection) best discriminated between the VES and novices. LIMITATIONS: VES whose performance was in the bottom half of their group demonstrated considerable error variability and made five-times as many errors as the other half of the group (P = 0.006). CONCLUSIONS: The international Delphi panel reached high-level consensus on the RARP metrics that reliably distinguished between the objectively scored procedure performance of VES and novices. Reliable and valid performance metrics of RARP are imperative for effective and quality assured surgical training.