Search

Action segmentation is a challenging task in high-level process analysis, typically performed on video or kinematic data obtained from various sensors. This work presents two contributions related to action segmentation on kinematic data. Firstly, we introduce two versions of Multi-Stage Temporal Convolutional Recurrent Networks (MS-TCRNet), specifically designed for kinematic data. The architectures consist of a prediction generator with intra-stage regularization and Bidirectional LSTM or GRU-based refinement stages. Secondly, we propose two new data augmentation techniques, World Frame Rotation and Hand Inversion, which utilize the strong geometric structure of kinematic data to improve algorithm performance and robustness. We evaluate our models on three datasets of surgical suturing tasks: the Variable Tissue Simulation (VTS) Dataset and the newly introduced Bowel Repair Simulation (BRS) Dataset, both of which are open surgery simulation datasets collected by us, as well as the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS), a well-known benchmark in robotic surgery. Our methods achieved state-of-the-art performance. code: https://github.com/AdamGoldbraikh/MS-TCRNet., Competing Interests: Conflicts of interest The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.

Abstract: Clinical touch is the cornerstone of the doctor-patient relationship and can impact patient experience and outcomes. In the current era, driven by an ever-increasing infusion of point-of-care technologies, physical exam skills have become undervalued. Moreover, touch and hands-on skills have been difficult to teach due to inaccurate assessments and difficulty with learning transfer through observation. In this article, the authors argue that haptics, the science of touch, provides a unique opportunity to explore new pathways to facilitate touch training. Furthermore, haptics can dramatically increase the density of touch-based assessments without increasing human rater burden-essential for realizing precision assessment. The science of haptics is reviewed, including the benefits of using haptics-informed language for objective structured clinical examinations. The authors describe how haptic devices and haptic language have and can be used to facilitate learning, communication, documentation and a much-needed reinvigoration of physical examination, and touch excellence at the point of care. The synergy of haptic devices, artificial intelligence, and virtual reality environments are discussed. The authors conclude with challenges of scaling haptic technology in medical education, such as cost and translational needs, and opportunities to achieve wider adoption of this transformative approach to precision education., (Copyright © 2023 the Association of American Medical Colleges.)

Abstract: The goal of medical education is to produce a physician workforce capable of delivering high-quality equitable care to diverse patient populations and communities. To achieve this aim amidst explosive growth in medical knowledge and increasingly complex medical care, a system of personalized and continuous learning, assessment, and feedback for trainees and practicing physicians is urgently needed. In this perspective, the authors build on prior work to advance a conceptual framework for such a system: precision education (PE).PE is a system that uses data and technology to transform lifelong learning by improving personalization, efficiency, and agency at the individual, program, and organization levels. PE "cycles" start with data inputs proactively gathered from new and existing sources, including assessments, educational activities, electronic medical records, patient care outcomes, and clinical practice patterns. Through technology-enabled analytics , insights are generated to drive precision interventions . At the individual level, such interventions include personalized just-in-time educational programming. Coaching is essential to provide feedback and increase learner participation and personalization. Outcomes are measured using assessment and evaluation of interventions at the individual, program, and organizational levels, with ongoing adjustment for repeated cycles of improvement. PE is rooted in patient, health system, and population data; promotes value-based care and health equity; and generates an adaptive learning culture.The authors suggest fundamental principles for PE, including promoting equity in structures and processes, learner agency, and integration with workflow (harmonization). Finally, the authors explore the immediate need to develop consensus-driven standards: rules of engagement between people, products, and entities that interact in these systems to ensure interoperability, data sharing, replicability, and scale of PE innovations., (Copyright © 2024 the Association of American Medical Colleges.)

Purpose: Successful implementation of precision education systems requires widespread adoption and seamless integration of new technologies with unique data streams that facilitate real-time performance feedback. This paper explores the use of sensor technology to quantify hands-on clinical skills. The goal is to shorten the learning curve through objective and actionable feedback., Method: A sensor-enabled clinical breast examination (CBE) simulator was used to capture force and video data from practicing clinicians (N = 152). Force-by-time markers from the sensor data and a machine learning algorithm were used to parse physicians' CBE performance into periods of search and palpation and then these were used to investigate distinguishing characteristics of successful versus unsuccessful attempts to identify masses in CBEs., Results: Mastery performance from successful physicians showed stable levels of speed and force across the entire CBE and a 15% increase in force when in palpation mode compared with search mode. Unsuccessful physicians failed to search with sufficient force to detect deep masses ( F [5,146] = 4.24, P = .001). While similar proportions of male and female physicians reached the highest performance level, males used more force as noted by higher palpation to search force ratios ( t [63] = 2.52, P = .014)., Conclusions: Sensor technology can serve as a useful pathway to assess hands-on clinical skills and provide data-driven feedback. When using a sensor-enabled simulator, the authors found specific haptic approaches that were associated with successful CBE outcomes. Given this study's findings, continued exploration of sensor technology in support of precision education for hands-on clinical skills is warranted., (Copyright © 2024 the Association of American Medical Colleges.)

This paper summarizes the proceedings of the joint European Surgical Association ESA/American Surgical Association symposium on Surgical Education that took place in Bordeaux, France, as part of the celebrations for 30 years of ESA scientific meetings. Three presentations on the use of quantitative metrics to understand technical decisions, coaching during training and beyond, and entrustable professional activities were presented by American Surgical Association members and discussed by ESA members in a symposium attended by members of both associations., Competing Interests: The authors report no conflicts of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Competing Interests: Declaration of competing interest I have no financial interests in the content of this manuscript.

This paper summarizes key points of the 2023 Southeastern Surgical Congress Laws Lecture. The focus of the presentation was on the use of advanced engineering technology to quantify surgical mastery. New concepts relating to the visual-haptic loop, mastery and perception, and mastery and technical decisions were introduced and shown in an empirical fashion to have relevance in procedural outcomes in a simulated setting. The major takeaway point is that surgical mastery can be quantified using advanced engineering technology, and this process will help to shorten the learning curve., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Competing Interests: The authors report no conflicts of interest.

Background: Our aim was to identify gender and racial disparities in presidential leadership for national medical and surgical organizations., Methods: We located publicly sourced information on national medical organizations. Years between or since the first diverse presidents were analyzed using descriptive statistics and Mann Whitney U tests., Results: Sixty-seven national medical and surgical organizations were surveyed. 70.8% (n = 34) diversified via gender first (White-female), whereas 26.1% (n = 14) had racial diversity first. Organizations with gender diversity first followed with an African American male president sooner than organizations who first diversified by race (14.7 ± 11.8 v. 27.6 ± 11.3 years, p = 0.018). No significant difference was observed for the third tier of diversification., Conclusions: Significant gender and racial leadership disparities in national medical organizations are still present. It is notable that organizations with female leaders had a shorter timeline to racial diversity. These findings help to inform strategies to promote and increase diversity, equity, and inclusion in national leadership., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to disclose., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Objectives: Surgeon preferences such as instrument and suture selection and idiosyncratic approaches to individual procedure steps have been largely viewed as minor differences in the surgical workflow. We hypothesized that idiosyncratic approaches could be quantified and shown to have measurable effects on procedural outcomes., Methods: At the American College of Surgeons (ACS) Clinical Congress, experienced surgeons volunteered to wear motion tracking sensors and be videotaped while evaluating a loop of porcine intestines to identify and repair 2 preconfigured, standardized enterotomies. Video annotation was used to identify individual surgeon preferences and motion data was used to quantify surgical actions. χ 2 analysis was used to determine whether surgical preferences were associated with procedure outcomes (bowel leak)., Results: Surgeons' (N=255) preferences were categorized into 4 technical decisions. Three out of the 4 technical decisions (repaired injuries together, double-layer closure, corner-stitches vs no corner-stitches) played a significant role in outcomes, P <0.05. Running versus interrupted did not affect outcomes. Motion analysis revealed significant differences in average operative times (leak: 6.67 min vs no leak: 8.88 min, P =0.0004) and work effort (leak-path length=36.86 cm vs no leak-path length=49.99 cm, P =0.001). Surgeons who took the riskiest path but did not leak had better bimanual dexterity (leak=0.21/1.0 vs no leak=0.33/1.0, P =0.047) and placed more sutures during the repair (leak=4.69 sutures vs no leak=6.09 sutures, P =0.03)., Conclusions: Our results show that individual preferences affect technical decisions and play a significant role in procedural outcomes. Future analysis in more complex procedures may make major contributions to our understanding of contributors to procedure outcomes., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: The goal of this work is to use multi-camera video to classify open surgery tools as well as identify which tool is held in each hand. Multi-camera systems help prevent occlusions in open surgery video data. Furthermore, combining multiple views such as a top-view camera covering the full operative field and a close-up camera focusing on hand motion and anatomy may provide a more comprehensive view of the surgical workflow. However, multi-camera data fusion poses a new challenge: A tool may be visible in one camera and not the other. Thus, we defined the global ground truth as the tools being used regardless their visibility. Therefore, tools that are out of the image should be remembered for extensive periods of time while the system responds quickly to changes visible in the video., Methods: Participants (n = 48) performed a simulated open bowel repair. A top-view and a close-up cameras were used. YOLOv5 was used for tool and hand detection. A high-frequency LSTM with a 1-second window at 30 frames per second (fps) and a low-frequency LSTM with a 40-second window at 3 fps were used for spatial, temporal, and multi-camera integration., Results: The accuracy and F1 of the six systems were: top-view (0.88/0.88), close-up (0.81,0.83), both cameras (0.9/0.9), high-fps LSTM (0.92/0.93), low-fps LSTM (0.9/0.91), and our final architecture the multi-camera classifier(0.93/0.94)., Conclusion: Since each camera in a multi-camera system may have a partial view of the procedure, we defined a 'global ground truth.' Defining this at the data labeling phase emphasized this requirement at the learning phase, eliminating the need for any heuristic decisions. By combining a system with a high fps and a low fps from the multiple camera array, we improved the classification abilities of the global ground truth., (© 2022. CARS.)

Background: We explored the feasibility and surgeons' perceptions of the utility of a longitudinal skills performance database., Methods: A 10-station surgical skills assessment center was established at a national scientific meeting. Skills assessment volunteers (n = 189) completed a survey including opinions on practicing surgeons' skills evaluation, ethics, and interest in a longitudinal database. A subset (n = 23) participated in a survey-related interview., Results: Nearly all participants reported interest in a longitudinal database and most believed there is an ethical obligation for such assessments to protect the public. Several interviewees specified a critical role for both formal and informal evaluation is to first create a safe and supportive environment., Conclusions: Participants support the construction of longitudinal skills databases that allow information sharing and establishment of professional standards. In a constructive environment, structured peer feedback was deemed acceptable to enhance and diversify surgeon skills. Large scale skills testing is feasible and scientific meetings may be the ideal location., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose: The use of motion sensors is emerging as a means for measuring surgical performance. Motion sensors are typically used for calculating performance metrics and assessing skill. The aim of this study was to identify surgical gestures and tools used during an open surgery suturing simulation based on motion sensor data., Methods: Twenty-five participants performed a suturing task on a variable tissue simulator. Electromagnetic motion sensors were used to measure their performance. The current study compares GRU and LSTM networks, which are known to perform well on other kinematic datasets, as well as MS-TCN++, which was developed for video data and was adapted in this work for motion sensors data. Finally, we extended all architectures for multi-tasking., Results: In the gesture recognition task the MS-TCN++ has the highest performance with accuracy of [Formula: see text] and F1-Macro of [Formula: see text], edit distance of [Formula: see text] and F1@10 of [Formula: see text] In the tool usage recognition task for the right hand, MS-TCN++ performs the best in most metrics with an accuracy score of [Formula: see text], F1-Macro of [Formula: see text], F1@10 of [Formula: see text], and F1@25 of [Formula: see text]. The multi-task GRU performs best in all metrics in the left-hand case, with an accuracy of [Formula: see text], edit distance of [Formula: see text], F1-Macro of [Formula: see text], F1@10 of [Formula: see text], and F1@25 of [Formula: see text]., Conclusion: In this study, using motion sensor data, we automatically identified the surgical gestures and the tools used during an open surgery suturing simulation. Our methods may be used for computing more detailed performance metrics and assisting in automatic workflow analysis. MS-TCN++ performed better in gesture recognition as well as right-hand tool recognition, while the multi-task GRU provided better results in the left-hand case. It should be noted that our multi-task GRU network is significantly smaller and has achieved competitive results in the rest of the tasks as well., (© 2022. CARS.)

Purpose: The goal of this study was to develop a new reliable open surgery suturing simulation system for training medical students in situations where resources are limited or in the domestic setup. Namely, we developed an algorithm for tools and hands localization as well as identifying the interactions between them based on simple webcam video data, calculating motion metrics for assessment of surgical skill., Methods: Twenty-five participants performed multiple suturing tasks using our simulator. The YOLO network was modified to a multi-task network for the purpose of tool localization and tool-hand interaction detection. This was accomplished by splitting the YOLO detection heads so that they supported both tasks with minimal addition to computer run-time. Furthermore, based on the outcome of the system, motion metrics were calculated. These metrics included traditional metrics such as time and path length as well as new metrics assessing the technique participants use for holding the tools., Results: The dual-task network performance was similar to that of two networks, while computational load was only slightly bigger than one network. In addition, the motion metrics showed significant differences between experts and novices., Conclusion: While video capture is an essential part of minimal invasive surgery, it is not an integral component of open surgery. Thus, new algorithms, focusing on the unique challenges open surgery videos present, are required. In this study, a dual-task network was developed to solve both a localization task and a hand-tool interaction task. The dual network may be easily expanded to a multi-task network, which may be useful for images with multiple layers and for evaluating the interaction between these different layers., (© 2022. CARS.)

Objective: The aim of this study was to describe the development and evaluation of a structured department wide cultural competency curriculum., Summary Background Data: Despite numerous organizational policies and statements, social injustice and bias still exist. Our department committed to assist individuals of the entire department to develop foundational knowledge and skills to combat implicit bias and systemic racism through the creation of a cultural competency curriculum. The purpose of this manuscript is to detail our curriculum and the evaluation of its effectiveness., Methods: Using a well-established curriculum development framework, a cultural competency curriculum was developed focusing on knowledge, skills and attitudes at the individual level, for all members of the department. The curriculum was implemented through 6-hour-long sessions over a 9-week period. Effectiveness was assessed through a post curriculum survey., Results: Twenty percent of the respondents had experienced bias based on race, ethnicity, or sexual orientation in the past 12 months, whereas 30% had experienced bias based on sex. Seventy-one percent independently explored related topics. The curriculum was overall well received and generally achieved the goals and objectives., Conclusion: Using a standard curriculum development framework, an effective department-wide cultural competency curriculum can be developed and implemented., Competing Interests: The authors report no conflicts of interests., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: The American College of Surgeon (ACS), American Surgical Association (ASA), Association of Women Surgeons (AWS), and Society of Black Academic Surgeons (SBAS) partnered to gain insight into whether inequities found in surgical society presidents may be present earlier., Methods: ACS, ASA, AWS, and SBAS presidents' CVs were assessed for demographics and scholastic achievements at the time of first faculty appointment. Regression analyses controlling for age were performed to determine relative differences across societies., Results: 66 of the 68 presidents' CVs were received and assessed (97% response rate). 50% of AWS future presidents were hired as Instructors rather than Assistant professors, compared to 29.4% of SBAS, 25% of ASA and 29.4% of ACS. The future ACS, ASA, and SBAS presidents had more total publications than the AWS presidents, but similar numbers of 1st and Sr. author publications., Conclusion: Gender inequities in academic surgeon hiring practices and perceived scholastic success may be present at first hire., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: The growing interest in analysis of surgical video through machine learning has led to increased research efforts; however, common methods of annotating video data are lacking. There is a need to establish recommendations on the annotation of surgical video data to enable assessment of algorithms and multi-institutional collaboration., Methods: Four working groups were formed from a pool of participants that included clinicians, engineers, and data scientists. The working groups were focused on four themes: (1) temporal models, (2) actions and tasks, (3) tissue characteristics and general anatomy, and (4) software and data structure. A modified Delphi process was utilized to create a consensus survey based on suggested recommendations from each of the working groups., Results: After three Delphi rounds, consensus was reached on recommendations for annotation within each of these domains. A hierarchy for annotation of temporal events in surgery was established., Conclusions: While additional work remains to achieve accepted standards for video annotation in surgery, the consensus recommendations on a general framework for annotation presented here lay the foundation for standardization. This type of framework is critical to enabling diverse datasets, performance benchmarks, and collaboration., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Currently, there is significant variability in the development, implementation and overarching goals of video review for assessment of surgical performance., Methods: This paper evaluates the current methods in which video review is used for evaluation of surgical performance and identifies which processes are critical for successful, widespread implementation of video-based assessment., Results: Despite the advances in video capture technology and growing interest in video-based assessment, there is a notable gap in the implementation and longitudinal use of formative and summative assessment using video., Conclusion: Validity, scalability and discoverability are current but removable barriers to video-based assessment., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: To comprehensively assess the level of achievement and demographics of national surgical society presidents., Background: Data on the accomplishments needed to rise to positions of national surgical leadership is scarce and merit alone does not always yield such opportunities. Recognizing the shortcomings of sex and ethnic diversity within academic surgical leadership, the American College of Surgeon (ACS), American Surgical Association (ASA), Association of Women Surgeons (AWS), and the Society of Black Academic Surgeons (SBAS) partnered to address these challenges by performing a comprehensive assessment of their presidents over the last 16 years., Methods: ACS, ASA, AWS, and SBAS presidents' CVs, at the time of their presidential term, were assessed for demographics and scholastic achievements. Regression analyses controlling for age were performed to determine relative differences across societies., Results: A total of 62 of the 64 presidents' CVs were received and assessed (97% response rate). There was a large discrepancy in the average age in years of ACS (70) and ASA (66) presidents compared to the AWS (51) and SBAS (53) presidents. For the ACS and ASA cohort, 87% were male and 83% were White, collectively. After controlling for age (52), the AWS and SBAS presidents' scholastic achievements were comparable to the ACS (and ASA) cohort in 9 and 12 of the 15 accessed metrics, respectively., Conclusion: The ACS and ASA presidents' CVs displayed unsurpassed scholastic achievement, and although not equivalent, both the AWS and the SBAS presidents had comparable attainment. These findings further substantiate that women and ethnic minority surgeons are deserving of additional national leadership consideration as organized medicine pursues a more diverse and reflective physician workforce.

Operative video has great potential to enable instant replays of critical surgical decisions for training and quality review. Recently, artificial intelligence (AI) has shown early promise as a method of enabling efficient video review, analysis, and segmentation. Despite the progress with AI analysis of surgical videos, more work needs to be done to improve the accuracy and efficiency of AI-driven video analysis. At a recent consensus conference held on July 10-11, 2020, 8 research teams shared their work using AI for surgical video analysis. Four of the teams showcased the utility of wearable technology in providing objective surgical metrics. Data from these technologies were shown to pinpoint important cognitive and motor actions during operative tasks and procedures. The results support the utility of wearable technology to facilitate efficient and accurate video analysis and segmentation., Competing Interests: Disclosure: The authors declare that they have nothing to disclose., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc.)

Objectives: Artificial intelligence (AI) has numerous applications in surgical quality assurance. We assessed AI accuracy in evaluating the critical view of safety (CVS) and intraoperative events during laparoscopic cholecystectomy. We hypothesized that AI accuracy and intraoperative events are associated with disease severity., Methods: One thousand fifty-one laparoscopic cholecystectomy videos were annotated by AI for disease severity (Parkland Scale), CVS achievement (Strasberg Criteria), and intraoperative events. Surgeons performed focused video review on procedures with ≥1 intraoperative events (n = 335). AI versus surgeon annotation of CVS components and intraoperative events were compared. For all cases (n = 1051), intraoperative-event association with CVS achievement and severity was examined using ordinal logistic regression., Results: Using AI annotation, surgeons reviewed 50 videos/hr. CVS was achieved in ≤10% of cases. Hepatocystic triangle and cystic plate visualization was achieved more often in low-severity cases (P < 0.03). AI-surgeon agreement for all CVS components exceeded 75%, with higher agreement in high-severity cases (P < 0.03). Surgeons agreed with 99% of AI-annotated intraoperative events. AI-annotated intraoperative events were associated with both disease severity and number of CVS components not achieved. Intraoperative events occurred more frequently in high-severity versus low-severity cases (0.98 vs 0.40 events/case, P < 0.001)., Conclusions: AI annotation allows for efficient video review and is a promising quality assurance tool. Disease severity may limit its use and surgeon oversight is still required, especially in complex cases. Continued refinement may improve AI applicability and allow for automated assessment., Competing Interests: The authors report no conflicts of interest., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Background: This paper explores a method for assessing intraoperative performance by modeling how surgeons integrate skills and knowledge through discourse., Methods: Senior residents (N = 11) were recorded while performing a simulated laparoscopic ventral hernia (LVH) repair. Audio transcripts were coded for five discourse elements related to knowledge, skills, and operative independence. Epistemic network analysis was used to model the ordered integration of the five discourse elements., Results: Participants with poorer hernia repair outcomes had stronger connections between the discourse elements operative planning and asking for information or advice (Operative planning), while participants with better hernia repair outcomes had stronger connections between the discourse elements giving assistant instructions and identifying errors (Operative management): (p = .006; Cohen's d = 2.79)., Conclusion: Participants with better hernia repair outcomes engaged in more operative management communication during the simulated procedure. This ability to integrate multiple operative steps and verbally communicate them significantly correlated with better operative outcomes., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Purpose: Forearm and distal radius fractures are among the most common fractures in children. Many fractures are definitively treated with closed reduction and casting, however, the risk for re-displacement is high (7% to 39%). Proper cast application and the three-point moulding technique are modifiable factors that improve the ability of a cast to maintain the fracture reduction. Many providers univalve the cast to accommodate swelling. This study describes how the location of the univalve cut impacts the pressure at three-point mould sites for a typical dorsally displaced distal radius fracture., Methods: We placed nine force-sensing resistors on an arm model to collect pressure data at the three-point mould sites. Sensory inputs were sampled at 15 Hz. Cast padding and a three-point moulded short arm fibreglass cast was applied. The cast was then univalved on the dorsal, volar, radial or ulnar aspect. Pressure recordings were obtained throughout the procedure., Results: A total of 24 casts were analyzed. Casts univalved in the sagittal plane (dorsal or volar surface) retained up to 16% more pressure across the three moulding sites compared with casts univalved in the coronal plane (radial or ulnar border)., Conclusion: Maintaining pressure at the three-point mould prevents loss of reduction at the fracture site. This study shows that univalving the cast dorsally or volarly results in less pressure loss at moulding sites. This should improve the chances of maintaining fracture reductions when compared with radial or ulnar cuts in the cast. Sagittal plane univalving of forearm casts is recommended., (Copyright © 2020, The author(s).)

Background: Surgeons from under-represented backgrounds are less likely to receive academic tenure and obtain leadership positions. Our objective was to query the curriculum vitaes (CVs) of SBAS leadership to develop a benchmarking tool to promote and guide careers in academic surgery., Methods: CVs from academic leaders were reviewed for academic productivity at early career stages-the first 5-and 10-years. Variables queried: peer-reviewed publications, grant funding, surgical societal involvement, invited lectureships and visiting professorships., Results: Of 20 CVs, 41 leadership positions including 13 SBAS Presidents were identified. At 5- and 10-years, respectively, the academic productivity increased: 20.6 and 52.3 publications; 4.7 and 9.7 grants; 18 and 42.6 lectures/professorships., Conclusion: The CV benchmarking tool may be a useful framework for aspiring academic surgeons to track their progress relative to successful SBAS members. Creative strategies like these, paired with faculty mentorship and sponsorship are necessary to improve the ethnic diversity in academic surgery., Competing Interests: Declaration of competing interest None., (Copyright © 2020. Published by Elsevier Inc.)

Background: Traditional checklist metrics for surgical performance can miss key intraoperative decisions that impact procedural outcomes. Error-based assessments may help identify important metrics for evaluating operative performance and resident readiness for independent practice., Methods: This study utilized human factors error analysis and error management theory to investigate a previously collected video database of resident performance during a simulated laparoscopic ventral hernia (LVH) repair on a table-top simulator using standard laparoscopic tools and mesh. Errors were deconstructed and coded using a structured observation tool and video analysis software. Error detection events and error recovery events were categorized for each operative step of the ventral hernia repair., Results: Residents made a total of 314 errors (M = 15.7, SD = 4.96). There were more technical errors (63%) than cognitive errors (37%) and more commission errors (69%) than omission errors (30%). Almost half (47%) of all errors went completely undetected by the residents for the entire LVH repair. Of the errors that residents attempted to recover (n = 136), 86.0% were successfully recovered. Technical errors were four times more likely to be successfully recovered than cognitive errors (p = .020)., Conclusions: Our results revealed specific details regarding residents' error management strategies and provides validity evidence for the use of human factors error frameworks in surgical performance assessments. Practice in simulation-based learning environments may improve resident decision-making and error management opportunities by providing a structured experience where errors are explicitly characterized and used for training and feedback. Error management training may play a major role in equipping residents and junior faculty with the skills required for independent, high-quality operative performance., Competing Interests: Declaration of competing interest Carla Pugh, Anne-Lise D’Angelo, Rebecca Ray, Jacob Greenberg, Caprice Greenberg, Douglas Wiegmann, Katherine Law and Elaine Cohen have no conflicts of interest or financial ties to disclose. Funding for this study was provided through the US Army Medical Research Acquisition Activity grant entitled “Psycho-Motor and Error Enabled Simulations: Modeling Vulnerable Skills in the Pre-Mastery Phase” W81XWH-13-1-008 and the National Institutes of Health grant #1F32EB017084-01 entitled “Automated Performance Assessment System: A New Era in Surgical Skills Assessment”. The funding source had no involvement in study design; collection, analysis, and interpretation of data; in writing of the report; and in the decision to submit the article for publication., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Skill assessment in surgery traditionally has relied on the expert observation and qualitative scoring. Our novel study design demonstrates how analysis of performance in sensorimotor tasks and bench-top surgical simulators can provide inferences about the technical proficiency as well as the training history of surgeons., Methods: We examined metrics for basic sensorimotor tasks in a virtual reality interface as well as motion metrics in clinical scenario simulations. As indicators of the training level, we considered survey responses from surgery residents, including the number of postgraduation years (PGY, four levels), research years (RY, three levels), and clinical years (CY, three levels). Next, we performed a linear discriminant analysis with cross-validation (90% training, 10% testing) to relate the training levels to the selected metrics., Results: Using combined metrics from all stations, we found greater than chance predictions for each survey category, with an overall accuracy of 43.4 ± 2.9% for identifying the level for post-graduate years, 79.1 ± 1.0% accuracy for research training years, and 64.2 ± 1.0% for clinical training years. Our main finding was that combining metrics from all stations resulted in more accurate predictions than using only sensorimotor or clinical scenario tasks. In addition, we found that metrics related to the ability to cope with changes in the task environment were the most important predictors of training level., Conclusions: These results suggest that each simulator-type provided crucial information for evaluating surgical proficiency. The methods developed in this paper could improve evaluations of a surgeon's clinical proficiency as well as training potential in terms of basic sensorimotor ability.

Background: Interest is growing in simulation-based continuing medical education courses for practicing surgeons. However, little research has explored the instruction employed during these courses. This study examines instruction practices used during an annual simulation-based continuing medical education course., Methods: Audio-video data were collected from surgeon instructors (n = 12) who taught a simulated laparoscopic hernia repair continuing medical education course across 2 years. Surgeon learners (n = 58) were grouped by their self-reported laparoscopic and hernia repair experience. Instructors' transcribed dialogue was automatically coded for 5 types of responses to the following questions: anecdotes, confirming, correcting, guidance, and what not to do. Differences in these responses were measured against the progress of the simulations and across learners with different experience levels. Postcourse interviews with instructors were conducted for additional qualitative validation., Results: Performing t tests of instructor responses revealed that they were significantly more likely to answer in forms coded as anecdotes when responding to relative experts and in forms coded as what not to do when responding to novices. Linear regressions of each code against normalized progressions of each simulation revealed a significant relationship between progression through a simulation and frequency of the what not to do code for less-experienced learners. Postcourse interviews revealed that instructors continuously assess participants throughout a session and modify their teaching strategies., Conclusion: Instructors significantly modified the focus of their teaching as a function both of their learners' self-reported experience levels, their assessment of learner needs, and learner progression through the training sessions., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: Computer vision was used to predict expert performance ratings from surgeon hand motions for tying and suturing tasks., Summary Background Data: Existing methods, including the objective structured assessment of technical skills (OSATS), have proven reliable, but do not readily discriminate at the task level. Computer vision may be used for evaluating distinct task performance throughout an operation., Methods: Open surgeries was videoed and surgeon hands were tracked without using sensors or markers. An expert panel of 3 attending surgeons rated tying and suturing video clips on continuous scales from 0 to 10 along 3 task measures adapted from the broader OSATS: motion economy, fluidity of motion, and tissue handling. Empirical models were developed to predict the expert consensus ratings based on the hand kinematic data records., Results: The predicted versus panel ratings for suturing had slopes from 0.73 to 1, and intercepts from 0.36 to 1.54 (Average R2 = 0.81). Predicted versus panel ratings for tying had slopes from 0.39 to 0.88, and intercepts from 0.79 to 4.36 (Average R2 = 0.57). The mean square error among predicted and expert ratings was consistently less than the mean squared difference among individual expert ratings and the eventual consensus ratings., Conclusions: The computer algorithm consistently predicted the panel ratings of individual tasks, and were more objective and reliable than individual assessment by surgical experts.

Medical educators have acknowledged the importance of simulation training in developing procedural skills. While simulation training in other disciplines has benefitted from evaluations of users' skill acquisition, the majority of medical training simulators continue to be developed from overly simplified descriptions of procedures, such as techniques prescribed by existing instructional material. Our objective was to use a modeling framework to characterize the skill of various users in applying junctional tourniquets in order to design an effective training simulator. We recorded 46 medical first responders performing training exercises applying a junctional tourniquet and used coded video and sensor data to identify the hierarchy of actions they performed in the process. The model provides several insights into trainee performance, such as the way in which advanced users perform more tasks in parallel, or areas where advanced users employ situational awareness to identify ways they can deviate from recommended protocol to improve outcomes. The model successfully identifies variations in tourniquet application technique that correlates with improvement on clinically relevant metrics including application speed, pressure applied, and tourniquet placement stability. This methodology can improve medical training simulations by indicating changes during the course of learning a new task, such as helpful deviations from instructional protocol., (© Association of Military Surgeons of the United States 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Given their variegated backgrounds, surgeons taking continuing medical education (CME) courses possess different learning needs. This study examines the relationship between surgeons' levels of experience and the questions they asked in a simulation-based CME course., Methods: We analyzed transcribed audio-video data collected from surgeons participating in a simulated laparoscopic hernia repair CME course and identified four types of questions learners posed to their instructors. Linear regressions compared how often these questions were asked versus self-reported operative experience., Results: Both Requesting Guidance and Requesting Confirmation were inversely proportional to experience, whereas Asking About a Specific Case was directly proportional to experience. Requesting Instructor Preference exhibited no significant correlation with experience., Conclusion: Practicing surgeons with relatively less experience tend to ask for confirmation and guidance, whereas those with greater experience tend to focus on specific hypothetical scenarios. This data can be used to tailor instruction based on learners' self-reported experience level., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: This project involved the development and evaluation of a new visual bleeding feedback (VBF) system for tourniquet training. We hypothesized that dynamic VBF during junctional tourniquet training would be helpful and well received by trainees., Materials and Methods: We designed the VBF to simulate femoral bleeding. Medical students (n = 15) and emergency medical service (EMS) members (n = 4) were randomized in a single-blind, crossover study to the VBF or without feedback groups. Poststudy surveys assessing VBF usefulness and recommendations were conducted along with participants' reported confidence using a 7-point Likert scale. Data from the different groups were compared using Wilcoxon signed-rank and rank-sum tests., Results: Participants rated the helpfulness of the VBF highly (6.53/7.00) and indicated they were very likely to recommend the VBF simulator to others (6.80/7.00). Pre- and post-VBF confidence were not statistically different (P = 0.59). Likewise, tourniquet application times for VBF and without feedback before crossover were not statistically different (P = 0.63). Although participant confidence did not change significantly from beginning to end of the study (P = 0.46), application time was significantly reduced (P = 0.001)., Conclusions: New tourniquet learners liked our VBF prototype and found it useful. Although confidence did not change over the course of the study for any group, application times improved. Future studies using outcomes of this study will allow us to continue VBF development as well as incorporate other quantitative measures of task performance to elucidate VBF's true benefit and help trainees achieve mastery in junctional tourniquet skills., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: This paper explores a method for assessing intraoperative performance by modeling how surgeons integrate psychomotor, procedural, and cognitive skills to manage errors., Methods: Audio-video data were collected from general surgery residents (N = 45) performing a simulated laparoscopic ventral hernia repair. Errors were identified using a standard checklist, and speech was coded for elements related to error recognition and management. Epistemic network analysis (ENA) was used to model the integration of error management skills., Results: There was no correlation between number or type of errors committed and operative outcome. However, ENA models showed significant differences in the integration of error management skills between high-performing and low-performing residents., Conclusion: These results suggest that error checklists and surgeons' speech can be used to model the integration of psychomotor, procedural, and cognitive aspects of intraoperative performance. Moreover, ENA can identify and quantify this integration, providing insight on performance gaps in both individuals and populations., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: The human haptic system uses a set of reproducible and subconscious hand maneuvers to identify objects. Similar subconscious maneuvers are used during medical palpation for screening and diagnosis. The goal of this work was to develop a mathematical model that can be used to describe medical palpation techniques., Methods: Palpation data were measured using a two-dimensional array of force sensors. A novel algorithm for estimating the hand position from force data was developed. The hand position data were then modeled using multivariate autoregressive models. Analysis of these models provided palpation direction and frequency as well as palpation type. The models were tested and validated using three different data sets: simulated data, a simplified experiment in which participant followed a known pattern, and breast simulator palpation data., Results: Simulated data showed that the minimal error in estimating palpation direction and frequency is achieved when the sampling frequency is five to ten times the palpation frequency. The classification accuracy was for the simplified experiment and for the breast simulator data., Conclusion: Proper palpation is one of the vital components of many hands-on clinical examinations. In this study, an algorithm for characterizing medical palpation was developed. The algorithm measured palpation frequency and direction for the first time and provided classification of palpation type., Significance: These newly developed models can be used for quantifying and assessing clinical technique, and consequently, lead to improved performance in palpation-based exams. Furthermore, they provide a general tool for the study of human haptics.

Background: This study explores the long-term effectiveness of a newly developed clinical skills curriculum., Methods: Students (N = 40) were exposed to a newly developed, simulation-based, clinical breast exam (CBE) curriculum. The same students returned one year later to perform the CBE and were compared to a convenience sample of medical students (N = 15) attending a national conferences. All students were given a clinical vignette and performed the CBE. CBE techniques were video recorded. Chi-squared tests were used to assess differences in CBE technique., Results: Students exposed to a structured curriculum performed physical examination techniques more consistent with national guidelines than the random, national student sample. Structured curriculum students were more organized, likely to use two hands, a linear search pattern, and include the nipple-areolar complex during the CBE compared to national sample (p < 0.01)., Conclusions: Students exposed to a structured skills curriculum more consistently performed the CBE according to national guidelines. The variability in technique compared with the national sample of students calls for major improvements in adoption and implementation of structured skills curricula., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: Epistemic Network Analysis (ENA) is a technique for modeling and comparing the structure of connections between elements in coded data. We hypothesized that connections among team discourse elements as modeled by ENA would predict the quality of team performance in trauma simulation., Methods: The Modified Non-technical Skills Scale for Trauma (T-NOTECHS) was used to score a simulation-based trauma team resuscitation. Sixteen teams of 5 trainees participated. Dialogue was coded using Verbal Response Modes (VRM), a speech classification system. ENA was used to model the connections between VRM codes. ENA models of teams with lesser T-NOTECHS scores (n = 9, mean = 16.98, standard deviation [SD] = 1.45) were compared with models of teams with greater T-NOTECHS scores (n = 7, mean = 21.02, SD = 1.09)., Results: Teams had different patterns of connections among VRM speech form codes with regard to connections among questions and edifications (meanHIGH = 0.115, meanLOW = -0.089; t = 2.21; P = .046, Cohen d = 1.021). Greater-scoring groups had stronger connections between stating information and providing acknowledgments, confirmation, or advising. Lesser-scoring groups had a stronger connection between asking questions and stating information. Discourse data suggest that this pattern reflected increased uncertainty. Lesser-scoring groups also had stronger connections from edifications to disclosures (revealing thoughts, feelings, and intentions) and interpretations (explaining, judging, and evaluating the behavior of others)., Conclusion: ENA is a novel and valid method to assess communication among trauma teams. Differences in communication among higher- and lower-performing teams appear to result from the ways teams use questions. ENA allowed us to identify targets for improvement related to the use of questions and stating information by team members., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: Residents engaging in dedicated research experiences may return to clinical training with less surgical skill. The study aims were 1) to evaluate faculty perceptions of residents skills decay during dedicated research fellowships, and 2) to compare faculty and resident perceptions of residents skills decay., Methods: Faculty and residents were surveyed on resident research practices and perceptions of resident skills decay., Results: Faculty thought residents returning from research demonstrate less technical skill (Median = 4; 5-point Likert scale, 1 = Strongly disagree, 5 = Strongly agree), demonstrate less confidence (Median = 4), and require more instruction (Median = 4). Both faculty and residents perceived the largest skill reduction in complex procedures, technical surgical skills, and knowledge of procedure steps (p < 0.05)., Conclusion: While dedicated research experiences provide valuable academic experience, there is a cost to clinical skills retention and confidence specifically in the areas of complex operative procedures and technical surgical skills., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Introduction: Laparoscopic inguinal hernia repair has been shown to have significant benefits when compared to open inguinal hernia repair, yet remains underutilized in the United States. The traditional model of short, hands-on, cognitive courses to enhance the adoption of new techniques fails to lead to significant levels of practice implementation for most surgeons. We hypothesized that a comprehensive program would facilitate the adoption of laparoscopic inguinal hernia repair (TEP) for practicing surgeons., Methods: A team of experts in simulation, coaching, and hernia care created a comprehensive training program to facilitate the adoption of TEP. Three surgeons who routinely performed open inguinal hernia repair with greater than 50 cases annually were recruited to participate in the program. Coaches were selected based on their procedural expertise and underwent formal training in surgical coaching. Participants were required to evaluate all aspects of the educational program and were surveyed out to one year following completion of the program to assess for sustained adoption of TEP., Results: All three participants successfully completed the first three steps of the seven-step program. Two participants completed the full course, while the third dropped out of the program due to time constraints and low case volume. Participant surgeons rated Orientation (4.7/5), GlovesOn training (5/5), and Preceptored Cases (5/5) as highly important training activities that contributed to advancing their knowledge and technical performance of the TEP procedure. At one year, both participants were performing TEPs for "most of their cases" and were confident in their ability to perform the procedure. The total cost of the program including all travel, personal coaching, and simulation was $8638.60 per participant., Discussion: Our comprehensive educational program led to full and sustained adoption of TEP for those who completed the course. Time constraints, travel costs, and case volume are major considerations for successful completion; however, the program is feasible, acceptable, and affordable.

Background: The aim of this study was to assess performance measurement validity of our newly developed robotic surgery task trainer. We hypothesized that residents would exhibit wide variations in their intercohort performance as well as a measurable difference compared to surgeons in fellowship training., Materials and Methods: Our laboratory synthesized a model of a pelvic tumor that simulates unexpected bleeding. Surgical residents and fellows of varying specialties completed a demographic survey and were allowed 20 minutes to resect the tumor using the da Vinci robot and achieve hemostasis. At a standardized event in the simulation, venous bleeding began, and participants attempted hemostasis using suture ligation. A motion tracking system, using electromagnetic sensors, recorded participants' hand movements. A postparticipation Likert scale survey evaluated participants' assessment of the model's realism and usefulness., Results: Three of the seven residents (postgraduate year 2-5), and the fellow successfully resected the tumor in the allotted time. Residents showed high variability in performance and blood loss (125-700 mL) both within their cohort and compared to the fellow (150 mL blood). All participants rated the model as having high realism and utility for trainees., Conclusions: The results support that our bleeding pelvic tumor simulator has the ability to discriminate resident performance in robotic surgery. The combination of motion, decision-making, and blood loss metrics offers a multilevel performance assessment, analyzing both technical and decision-making abilities., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: Develop new performance evaluation standards for the clinical breast examination (CBE)., Summary Background Data: There are several, technical aspects of a proper CBE. Our recent work discovered a significant, linear relationship between palpation force and CBE accuracy. This article investigates the relationship between other technical aspects of the CBE and accuracy., Methods: This performance assessment study involved data collection from physicians (n = 553) attending 3 different clinical meetings between 2013 and 2014: American Society of Breast Surgeons, American Academy of Family Physicians, and American College of Obstetricians and Gynecologists. Four, previously validated, sensor-enabled breast models were used for clinical skills assessment. Models A and B had solitary, superficial, 2 cm and 1 cm soft masses, respectively. Models C and D had solitary, deep, 2 cm hard and moderately firm masses, respectively. Finger movements (search technique) from 1137 CBE video recordings were independently classified by 2 observers. Final classifications were compared with CBE accuracy., Results: Accuracy rates were model A = 99.6%, model B = 89.7%, model C = 75%, and model D = 60%. Final classification categories for search technique included rubbing movement, vertical movement, piano fingers, and other. Interrater reliability was (k = 0.79). Rubbing movement was 4 times more likely to yield an accurate assessment (odds ratio 3.81, P < 0.001) compared with vertical movement and piano fingers. Piano fingers had the highest failure rate (36.5%). Regression analysis of search pattern, search technique, palpation force, examination time, and 6 demographic variables, revealed that search technique independently and significantly affected CBE accuracy (P < 0.001)., Conclusions: Our results support measurement and classification of CBE techniques and provide the foundation for a new paradigm in teaching and assessing hands-on clinical skills. The newly described piano fingers palpation technique was noted to have unusually high failure rates. Medical educators should be aware of the potential differences in effectiveness for various CBE techniques.