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Background Although numerous studies have established cognitive biases as contributors to surgical adverse events, their prevalence and impact in surgery are unknown. This review aimed to describe types of cognitive bias in surgery, their impact on surgical performance and patient outcomes, their source, and the mitigation strategies used to reduce their effect. Methods A literature search was conducted on 9 April and 6 December 2021 using MEDLINE, Embase, PsycINFO, Scopus, Web of Science, Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews. Included studies investigated how cognitive biases affect surgery and the mitigation strategies used to combat their impact. The National Institutes of Health tools were used to assess study quality. Inductive thematic analysis was used to identify themes of cognitive bias impact on surgical performance. Results Thirty-nine studies were included, comprising 6514 surgeons and over 200 000 patients. Thirty-one types of cognitive bias were identified, with overconfidence, anchoring, and confirmation bias the most common. Cognitive biases differentially influenced six themes of surgical performance. For example, overconfidence bias associated with inaccurate perceptions of ability, whereas anchoring bias associated with inaccurate risk–benefit estimations and not considering alternative options. Anchoring and confirmation biases associated with actual patient harm, such as never events. No studies investigated cognitive bias source or mitigation strategies. Conclusion Cognitive biases have a negative impact on surgical performance and patient outcomes across all points of surgical care. This review highlights the scarcity of research investigating the sources that give rise to cognitive biases in surgery and the mitigation strategies that target these factors.

Not all trainees reach technical competency even after completing surgical training. While assessment of technical skill is not part of the residency interview process, identifying under-performers early on may help identify opportunities for individualized, targeted training. The objectives of this study were to (1) create predictive learning curve (LC) models for each of 3 basic laparoscopic tasks to identify performers versus underperformers and (2) evaluate the use of LCs to identify underperformers during selection into surgical training.Predictive LC models were created for laparoscopic pattern cutting (PC), peg transfer (PT) and intra-corporeal knots (IC) over 40 repetitions by 65 novice trainees in 2014. Trainees were categorized as performers and underperformers. Receiver operator characteristic analysis determined the minimum number of repetitions required to predict individual LCs, which were then used to determine the proportion of underperformers.Technical performance was assessed onsite at the Canadian Residence Matching Service (CaRMS) interviews, after interview completion (January 2015).Applicants to general surgery (GS) and gynecology (OBGYN) participated in a skills assessment during.The PC, PT and IC tasks required a minimum of 8, 10, and 5 repetitions respectively, to predict overall performance. Predictive values for each task had excellent sensitivity and specificity: 1.00, 1.00 (PC); 1.00, 1.00 (PT); and 0.94, 1.00 (IC). Eighty applicants completed 8 PC repetitions; 16% were identified as underperformers.Individual LCs for three different laparoscopic tasks can be predicted with excellent sensitivity and specificity based on 10 repetitions or less. This information can be used to identify trainees who may have difficulty with laparoscopic technical skills early on.

Objective: Competency-based surgical education requires detailed and actionable feedback to ensure adequate and efficient skill development. Comprehensive operative capture systems such as the Operating Room Black Box (ORBB; Surgical Safety Technologies, Inc), which continuously records and synchronizes multiple sources of intraoperative data, have recently been integrated into hybrid rooms to provide targeted feedback to endovascular teams. The objective of this study is to develop step, error, and event frameworks to evaluate technical performance in elective endovascular aortic repair (EVAR) comprehensively captured by the ORBB (Surgical Safety Technologies, Inc; Toronto, Canada). Methods: This study is based upon a modified Delphi consensus process to create evaluation frameworks for steps, errors, and events in EVAR. International experts from Vascular Surgery and Interventional Radiology were identified, based on their records of publications and invited presentations, or serving on relevant journal editorial boards. In an initial open-ended survey round, experts were asked to volunteer a comprehensive list of steps, errors, and events for a standard EVAR of an infrarenal aorto-iliac aneurysm (AAA). In subsequent survey rounds, the identified items were presented to the expert panel to rate on a 5-point Likert scale. Delphi survey rounds were repeated until the process reached consensus with a predefined agreement threshold (Cronbach α>0.7). The final frameworks were constructed with items achieving an agreement (responses of 4 or 5) from greater than 70% of experts. Results: Of 98 invited proceduralists, 38 formed the expert consensus panel (39%), consisting of 29 vascular surgeons and 9 interventional radiologists, with 34% from North America and 66% from Europe. Consensus criteria were met following the third round of the Delphi consensus process (Cronbach α=0.82–0.93). There were 15, 32, and 25 items in the error, step, and event frameworks, respectively (within-item agreement=74%–100%). Conclusion: A detailed evaluation tool for the procedural steps, errors, and events in infrarenal EVAR was developed. This tool will be validated on recorded procedures in future work: It may focus skill development on common errors and hazardous steps. This tool might be used to provide high-quality feedback on technical performance of trainees and experienced surgeons alike, thus promoting surgical mastery.

This study aimed to assess the relationship between surgeons' leadership style and team behavior in the hybrid operating room through video coding. Secondly, possible fluctuations in leadership styles and team behavior during operative phases were studied.Leadership is recognized as a key component to successful team functioning in high-risk industries. The 'full range of leadership' theory is commonly used to evaluate leadership, marking transformational, transactional and passive. Few studies have examined the effects of these leadership styles on team behavior in surgery and/or their fluctuations during surgery.A single-center study included patients planned for routine endovascular procedures. A medical data capture system was used to allow post-hoc video coding through Behavior Anchored Rating Scales. Multilevel statistical analysis was performed to assess possible correlations between leadership style and three team behavior indicators (speaking up, knowledge sharing, collaboration) on an operative phase level.Twenty-two cases were analyzed (47 hours recording). Transformational leadership is positively related to the extent to which team members work together (γ=0.20, P0.001), share knowledge (γ=0.45, P0.001) and speak up (γ=0.64, P0.001). Passive leadership is significantly positively correlated with speaking up (γ=0.29, P=0.004). Leadership style and team behavior clearly fluctuate during a procedure, with similar patterns across different types of endovascular procedures.Consistent with other professional fields, surgeons' transformational leadership enhances team behavior, especially during the most complex operative phases. This suggests that encouraging surgeons to learn and actively implement a transformational leadership style is meaningful to enhance patient safety and team performance.

BACKGROUND: The hybrid room (HR) is a complex, high-risk environment, requiring teams (surgeons, anesthesiologists, nurses, technolo-gists) to master various skills, including the 'As Low As Reasonably Achievable' principle of radiation safety. This prospective single center cohort reports the first use of the Operating Room Black Box (ORBB) in a HR. This medical data recording system captures procedural and audio-visual data to facilitate structured team performance analysis.METHODS: Patients planned for endovascular repair of an infrarenal abdominal aortic aneurysm (EVAR) or treatment of symptomatic iliac-femoral-popliteal atherosclerotic disease (Peripheral Vascular Interventions or PVI) were included. Validated measures and established assess-ment tools were used to assess (non-)technical skills, radiation safety performance and environmental distractions. RESULTS: Six EVAR and sixteen PVI procedures were captured. Technical performance for one EVAR was rated 19/35 on the procedure -specific scale, below the 'acceptable' score of 21. Technical skills were rated above acceptable in all PVI procedures. Shared decision making and leadership were rated highly in 12/22 cases, whereas surgical communication and nurses' task management were rated low in 14/22 cases. Team members rarely stepped back from the C-arm during digital subtraction angiography. Radiation safety behavior was scored below 'accept-able' in 14/22 cases. A median (interquartile range) number of 12 (6-23) auditory distractions was observed per procedure. CONCLUSIONS: The ORBB facilitates holistic workplace-based assessment of endovascular performance in a HR by combining objec-tive assessment parameters and rating scale-based evaluations. Strengths and weaknesses were identified in team members' (non-)technical and radiation safety practices. This technology has the potential to improve vascular surgical practice, though human input remains crucial. (NCT04854278)

Intraoperative adverse events lead to patient injury and death, and are increasing. Early warning systems (EWSs) have been used to detect patient deterioration and save lives. However, few studies have used EWSs to monitor surgical performance and caution about imminent technical errors. Previous (non-surgical) research has investigated neural activity to predict future motor errors using electroencephalography (EEG). The present proof-of-concept cohort study investigates whether EEG could predict technical errors in surgery.In a large academic hospital, three surgical fellows performed 12 elective laparoscopic general surgeries. Audiovisual data of the operating room and the surgeon's neural activity were recorded. Technical errors and epochs of good surgical performance were coded into events. Neural activity was observed 40 s prior and 10 s after errors and good events to determine how far in advance errors were detected. A hierarchical regression model was used to account for possible clustering within surgeons. This prospective, proof-of-concept, cohort study was conducted from July to November 2021, with a pilot period from February to March 2020 used to optimize the technique of data capture and included participants who were blinded from study hypotheses.Forty-five technical errors, mainly due to too little force or distance (n = 39), and 27 good surgical events were coded during grasping and dissection. Neural activity representing error monitoring (p = .008) and motor uncertainty (p = .034) was detected 17 s prior to errors, but not prior to good surgical performance.These results show that distinct neural signatures are predictive of technical error in laparoscopic surgery. If replicated with low false-alarm rates, an EEG-based EWS of technical errors could be used to improve individualized surgical training by flagging imminent unsafe actions-before errors occur and cause patient harm.

We report for the first time the use of the Operating Room Black Box (ORBB) to track checklist compliance, engagement, and quality.Implementation of operative checklists is associated with improved outcomes. Compliance is difficult to monitor. Most studies report either no assessment of checklist compliance or deployed in-person short-term assessment. The ORBB a novel artificially intelligence-driven data analytic platform affords the opportunity to assess checklist compliance without disrupting surgical workflow.This was a retrospective review of prospectively collected ORBB data. Operative cases included elective surgery at a quaternary referral center. Cases were analyzed as prepolicy change (first 9 months) or as a postpolicy change (last 9 months). Measures of checklist compliance, engagement, and quality were assessed.There were 3879 cases that were performed and monitored for checklist compliance between August 15, 2020, and February 20, 2022. The overall scores for compliance, engagement, and quality were 81%, 84%, and 67% respectively. When broken down by phase, the scores for time-out were compliance 100%, engagement 98%, and quality 61%. Scores for the debrief phase were 81% for compliance, 98% for engagement, and 66% for quality. After a hospital policy change, the debrief scores improved significantly (85%; P0.001 for compliance, 88%; P0.001 for engagement and 71%; P0.001 for quality).ORBB provides the unprecedented ability to assess not only compliance with surgical safety checklists but also engagement and quality. Utilization of this technology allows the assessment of compliance in near real time and to accurately address safety threats that may arise from noncompliance.

Introduction. The operating room (OR) Black Box is an innovative technology that captures and compiles extensive real-time data from the OR, allowing identification and analysis of factors that influence intraoperative procedures and performances – ultimately improving patient safety. Implementation of this kind of technology is still an emerging research area and prone to face challenges. Methods. Observational study running from May 2017 to May 2021 conducted at Copenhagen University Hospital – Rigshospitalet, Denmark, involving 152 OR staff and 306 patients. Feasibility of the OR Black Box was assessed in accordance with Bowen’s framework with 8 focus areas. Results. The OR Black Box had a high level of acceptability among stakeholders with 100% participation from management, 93% from OR staff, and 98% from patients. The implementation process improved over time, and an average of 80% of the surgeries conducted were captured. The practical aspects such as numerous formal and informal meetings, ethical and legal approval, recruitment of patients were acceptable, albeit time-consuming. The OR Black Box was adopted without any changes in scheduled surgery program, but capturing hours were adjusted to match the surgery program and relocation of OR staff declining to provide consent was possible. Conclusions. Implementation of the OR Black Box was feasible yet challenging. Management, nearly all staff, and patients embraced the initiative; however, ongoing evaluation, information meetings, and commitment from stakeholders are required and crucial to sustain momentum, continue implementation and expansion. Ideas from this study can be useful in the implementation of similar initiatives.

Background Currently, evaluating surgical technical performance is inefficient and subjective [1,2,3,4] and the established rubrics for assessing surgical ability are open to interpretation. To power programs for surgical training and Maintenance of Certification (MOC), a reliable and validated solution is required. To this end, we draw upon recent advances in machine learning and propose a framework for objective and scalable assessment of technical proficiency.Methods Different machine learning models were trained to predict surgical performance on the public EndoVis19 and JIGSAWS datasets. The most important features were extracted by probing each machine learning model, and these features form the basis of the proposed algorithm. We internally tested the performance of this model on proprietary datasets from Surgical Safety Technologies (SST) and the University of Texas Southwestern (UTSW). The performance of these models was assessed according to various statistical techniques such as precision, recall, f1-scores and the area under the receiver operating characteristic curve (AUC). Results OR Vision is a statistically-driven multi-stage machine learning tool that quantifies surgical skill objectively and explainably. Instrument motion, control, and coordination are quantified in terms of 150 objective metrics, extracted from tool motion tracked by the deep learning model. The N most highly correlated of these metrics (p

IntroductionComprehensive data capture systems such as the Operating Room Black Box (OR Black Box) are becoming more widely implemented to access quality data in the complex environment of the OR. Prior to installing an OR Black Box, we assessed perceptions on safety attitudes, impostor phenomenon and privacy concerns around digital information sharing among healthcare professionals in the OR. A parallel survey was conducted in Canada, hence, this study also discusses cultural and international differences when implementing new technology in healthcare.MethodsA cross-sectional survey using three previously validated questionnaires (Safety Attitudes Questionnaire (SAQ), Clance Impostor Phenomenon Scale, Dispositional Privacy Concern) was distributed through Research Electronic Data Capture to 145 healthcare professionals from the OR (July to December 2019). Analysis of variance and analysis of covariance were used to test for differences.Results124 responded (86%): 100 completed the survey (69%) (38 nurses, 10 anaesthesiologists, 36 obstetricians/gynaecologists, 16 residents). Significant variability in all six SAQ domains, safety climate and teamwork being the lowest ranked and job satisfaction ranked highest for all groups. The SAQ varied in all domains in Canada. Moderate to frequent impostor phenomenon was experienced by 71% predominantly among residents (p=0.003). 72% in the Canadian study. Residents were most comfortable with digital information sharing (pConclusionsThe different healthcare professional groups had diverse perceptions about safety culture, but were mainly concerned about safety climate and teamwork in the OR. Impostor phenomenon decreased with age. All groups were unconcerned about digital information sharing. The Canadian study had similar findings in terms of impostor phenomenon, but a variety within the SAQ and were more concerned about data safety, which could be due to medical litigation per se and is not widespread in Scandinavia compared with North America.

Recording in the operating room is an important tool to help surgical teams improve their performance. This is becoming more feasible using the Operating Room Black Box, a comprehensive data capture platform. Operating room (OR) staff, however, may voice reasonable concerns as recording initiatives are implemented. The objective of this study was to assess pre-implementation attitudes of OR staff toward operative recording and explore the relationship of these attitudes to the themes of (1) safety culture, (2) impostor syndrome, and (3) privacy concerns.This cross-sectional survey study measured staff members' beliefs and opinions of operative recording and used three previously validated tools (safety attitudes questionnaire, clance impostor phenomenon scale, and dispositional privacy concern) to assess personal and professional factors. Concepts were correlated using Pearson's correlation coefficient.Forty-three staff members participated in this study, with a response rate of 45% (n = 43/96, 20/22 nurses, 9/11 gynecologists, 14/63 anesthesiologists). Opinions of operative data capture were generally positive (5-point Likert scale, mean = 3.81, SD = 0.91). Nurses tended to have more favorable opinions of the OR Black Box as compared to gynecologists and anesthesiologists, though this did not reach statistical significance (4.15 vs. 3.67 vs 3.43, p = 0.06). Impostor syndrome characteristics correlated with concerns about litigation related to recording (r = - 0.32, p = 0.04).There are personal and professional attributes of the OR team that impact perceptions of the OR Black Box and implications around privacy and litigation. Addressing these concerns may facilitate successful implementation of the OR Black Box and improve team communication and patient safety in the OR.

Device-related interruptions in the operating room (OR) may create stress among health care providers and delays. Although non-technical skills (NTS) of the OR teams, such as situational awareness and communication, are expected to influence device-related interruptions, empirical data on this relationship are limited.We performed a prospective cohort study of 144 consecutive elective laparoscopic operations during 13 months. A data capture system called the OR Black Box® was used to characterize device-related interruptions, NTS, and distractions. Device-related interruptions were classified according to a priori established categories. Positive and negative NTS instances were identified according to validated measurement tools specific for nurses and surgeons. We assessed the relationship between NTS and device-related interruptions after adjusting for potential confounders.A total of 86 device-related interruptions occurred in 48 of 144 operations (33%). They were most frequently classified as device failure (54%) followed by improper assembly (19%) and disconnection (14%). Medians of 1 [interquartile range (IQR) 0-3] and 1 (IQR 0-2) negative NTS instance per operation were demonstrated by nurses and surgeons, respectively. Medians of 28 (IQR 15-38) and 40 (IQR 28-118) positive NTS instances per operation were demonstrated by nurses and surgeons. In a multivariable analysis, a higher frequency of negative NTS instances demonstrated by nurses was associated with device-related interruptions after risk adjustment (Odds Ratio 1.33, p = 0.02).In elective laparoscopic operations, an increased likelihood of device-related interruptions in the OR was associated with more frequent negative NTS demonstrations by nursing teams.

While the operating room (OR) has significantly benefited from aviation strategies to improve safety, the rate of avoidable human errors remains relatively high. One key aviation strategy that has yet to be formally established in the OR is the "sterile cockpit" rule, which prohibits all non-essential behaviours during critical moments of a flight. Applying this rule to the OR may enhance patient safety, but the critical moments of surgery need to be defined first.This study used a modified Delphi methodology to determine critical moments during surgery according to OR team members across institutions, professions, and specialties. Analysis occurred after each round. The stopping criterion was consensus on 80% of survey items or no change in the mean score for any individual item between two consecutive rounds.The first round included 304 respondents. Of these, 115 completed the second-round survey, and 75 completed all three rounds (27 nurses, 29 anesthesiologists, 19 surgeons). Critical moments obtained by consensus were: induction of anesthesia; emergence from anesthesia; preoperative briefing; final counts at the end of the procedure; anesthesiologist- or surgeon-relevant intraoperative event; handovers; procedure-specific high-risk surgical moments; crisis resource management situations; medication and equipment preparation; and key medication administration.By defining the most critical moments of surgery, future research can determine the relative importance of behaviour and actions at each stage and target interventions to these stages.RéSUMé: CONTEXTE: Alors que la salle d’opération (SOP) bénéficie considérablement des stratégies de l’aviation pour améliorer la sécurité, le taux d’erreurs humaines évitables y demeure relativement élevé. L’une des stratégies clés de l’aviation qui doit encore être mise en place de manière formelle en SOP est la règle de la « cabine de pilotage stérile », qui interdit tout comportement non essentiel pendant les moments critiques d’un vol. L’application de cette règle à la SOP pourrait améliorer la sécurité des patients, mais les moments critiques d’une chirurgie doivent d’abord être définis. MéTHODE: Cette étude a utilisé une méthodologie Delphi modifiée afin de déterminer les moments critiques pendant une chirurgie selon les membres des équipes de SOP en provenance de différentes institutions, professions et spécialités. Une analyse a eu lieu après chaque itération. Le critère d’arrêt était un consensus sur 80 % des items du sondage ou aucun changement dans la note moyenne obtenue pour n’importe quel item individuel entre deux itérations consécutives. RéSULTATS: La première série a inclus 304 répondants. Parmi ceux-ci, 115 ont complété le deuxième sondage, et 75 ont complété les trois séries de questions (27 infirmiers/infirmières, 29 anesthésiologistes, 19 chirurgiens/chirurgiennes). Les moments critiques retenus par consensus étaient : l’induction de l’anesthésie; l’émergence de l’anesthésie; le temps d’arrêt préopératoire; les décomptes finaux à la fin de l’intervention; les événements peropératoires importants pour l’anesthésiologiste ou le chirurgien; les transferts; les moments chirurgicaux à risque élevé spécifiques à l’intervention; les situations de gestion de crise des ressources; la préparation des médicaments et du matériel; et l’administration de médicaments clés. CONCLUSION: En définissant les moments les plus critiques de la chirurgie, les recherches futures pourront déterminer l’importance relative des comportements et des actes à chaque étape et cibler les interventions en fonction de ces étapes.

BACKGROUND A large proportion of surgical patient harm is preventable; yet, our ability to systematically learn from these incidents and improve clinical practice remains limited. The Operating Room Black Box was developed to address the need for comprehensive assessments of clinical performance in the operating room. It captures synchronized audio, video, patient, and environmental clinical data in real time, which are subsequently analyzed by a combination of expert raters and software-based algorithms. Despite its significant potential to facilitate research and practice improvement, there are many potential implementation challenges at the institutional, clinician, and patient level. This paper summarizes our approach to implementation of the Operating Room Black Box at a large academic Canadian center. OBJECTIVE We aimed to contribute to the development of evidence-based best practices for implementing innovative technology in the operating room for direct observation of the clinical performance by using the case of the Operating Room Black Box. Specifically, we outline the systematic approach to the Operating Room Black Box implementation undertaken at our center. METHODS Our implementation approach included seeking support from hospital leadership; building frontline support and a team of champions among patients, nurses, anesthesiologists, and surgeons; accounting for stakeholder perceptions using theory-informed qualitative interviews; engaging patients; and documenting the implementation process, including barriers and facilitators, using the consolidated framework for implementation research. RESULTS During the 12-month implementation period, we conducted 23 stakeholder engagement activities with over 200 participants. We recruited 10 clinician champions representing nursing, anesthesia, and surgery. We formally interviewed 15 patients and 17 perioperative clinicians and identified key themes to include in an information campaign run as part of the implementation process. Two patient partners were engaged and advised on communications as well as grant and protocol development. Many anticipated and unanticipated challenges were encountered at all levels. Implementation was ultimately successful, with the Operating Room Black Box installed in August 2018, and data collection beginning shortly thereafter. CONCLUSIONS This paper represents the first step toward evidence-guided implementation of technologies for direct observation of performance for research and quality improvement in surgery. With technology increasingly being used in health care settings, the health care community should aim to optimize implementation processes in the best interest of health care professionals and patients.

To validate the Non-Technical Skills for Surgeons (NOTSS) system for assessment of the collective surgical teams' nontechnical skills after observing recordings of actual OR environment.The NOTSS system is a widely accepted tool to measure nontechnical skills of individual surgeons, and has mostly been used in the simulated setting. Surgical procedures are rarely performed by a single surgeon, but by a surgical team of attending surgeons, surgical assistants, and surgical trainees. Therefore, assessment of nontechnical skills may benefit from holistic assessment of the collective surgical teams.Five trained participants assessed surgical team and attending surgeon using the NOTSS system after watching ten 20-minute long videos obtained from live OR. A set of reference ratings was provided by a multidisciplinary expert committee. We performed analyses to assess system sensitivity; examine inter-rater reliability of ratings; investigate concurrent construct validity; and assess feasibility and acceptability of using the NOTSS system to measure surgical team performance.There was adequate system sensitivity when comparing participants' and reference ratings. Inter-rater reliability among the participants' ratings was good except for decision-making category. The level of inter-rater reliability was similar when rating teams and attending surgeons. There was strong positive correlation between teams' and attending surgeons' NOTSS ratings at category [Pearson coefficient 0.86, 95% confidence interval (CI) 0.82-0.89] and element levels (0.83, 95% CI 0.80-0.85), demonstrating evidence of concurrent construct validity. The participants felt that the use of NOTSS system to measure teams' nontechnical skills was acceptable and feasible to a fair extent.The NOTSS system, although developed for assessment of individual surgeons, is a useful tool for observing and rating surgical teams.

At its 2009 annual symposium, chaired by Dr. William (Bill) Pollett, the Canadian Association of University Surgeons brought together speakers with expertise in surgery and medical education to discuss the role of surgical simulation for improving surgical training and safety. Dr. Daniel Jones, of Harvard University and the 2009 Charles Tator Lecturer, highlighted how simulation has been used to teach advanced laparoscopic surgery. He also outlined how the American College of Surgeons is moving toward competency assessments as a requirement before surgeons are permitted to perform laparoscopic surgery on patients. Dr. Teodor Grantcharov, from the University of Toronto, highlighted the role of virtual reality simulators in laparoscopic surgery as well as box trainers. Dr. Peter Brindley from the University of Alberta, although a strong proponent of simulation, cautioned against an overzealous adoption without addressing its current limitations. He also emphasized simulation’s value in team training and crisis resource management training. Dr. Chris de Gara, also from the University of Alberta, questioned to what extent simulators should be used to determine competency. He raised concerns that if technical skills are learned in isolation, they may become “decontextualized,” and therefore simulation might become counterproductive. He outlined how oversimplification can have an “enchanting” effect, including a false sense of security. As a result, simulation must be used appropriately and along the entire education continuum. Furthermore, far more needs to be done to realize its role in surgical safety.

The present study was designed to investigate whether there is a correlation between manual skills in laparoscopic procedures and manual skills in flexible endoscopy.In a prospective study using laparoscopy and endoscopy simulators (MIST-VR, and GI-Mentor II), 24 consecutive subjects (gastrointestinal surgeons, novice and experienced gastroenterologists, and untrained subjects) were asked to perform laparoscopic and endoscopic tasks. Their performance was assessed by the simulators' software and by observers blinded to the levels of subjects' experience. Performance in experienced vs inexperienced subjects was compared. Score pairs of three parameters--time, errors, and economy of movement--were also compared.Experienced subjects performed significantly better than inexperienced subjects on both tasks in terms of time, errors, and economy of movement (p0.05). All three performance parameters in laparoscopy and endoscopy correlated significantly (p0.02).Both simulators can distinguish between experienced and inexperienced subjects. Observed skills in simulated laparoscopy correlate with skills in simulated flexible endoscopy. This finding may have an impact on the design of training programs involving both procedures.