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  1. Article ; Online: Surgical Artificial Intelligence in Urology: Educational Applications.

    Goldenberg, Mitchell G

    The Urologic clinics of North America

    2023  Volume 51, Issue 1, Page(s) 105–115

    Abstract: Surgical education has seen immense change recently. Increased demand for iterative evaluation of trainees from medical school to independent practice has led to the generation of an overwhelming amount of data related to an individual's competency. ... ...

    Abstract Surgical education has seen immense change recently. Increased demand for iterative evaluation of trainees from medical school to independent practice has led to the generation of an overwhelming amount of data related to an individual's competency. Artificial intelligence has been proposed as a solution to automate and standardize the ability of stakeholders to assess the technical and nontechnical abilities of a surgical trainee. In both the simulation and clinical environments, evidence supports the use of machine learning algorithms to both evaluate trainee skill and provide real-time and automated feedback, enabling a shortened learning curve for many key procedural skills and ensuring patient safety.
    MeSH term(s) Humans ; Urology/education ; Artificial Intelligence ; Educational Measurement ; Clinical Competence ; Simulation Training
    Language English
    Publishing date 2023-07-27
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 192293-2
    ISSN 1558-318X ; 0094-0143
    ISSN (online) 1558-318X
    ISSN 0094-0143
    DOI 10.1016/j.ucl.2023.06.003
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  2. Article ; Online: Editorial Comment.

    Goldenberg, Mitchell G

    The Journal of urology

    2022  Volume 208, Issue 2, Page(s) 422–423

    Language English
    Publishing date 2022-05-16
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 3176-8
    ISSN 1527-3792 ; 0022-5347
    ISSN (online) 1527-3792
    ISSN 0022-5347
    DOI 10.1097/JU.0000000000002691.01
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  3. Article ; Online: Re: Gopal Sharma, Milap Shah, Puneet Ahluwalia, et al. Development and Validation of a Nomogram Predicting Intraoperative Adverse Events During Robot-assisted Partial Nephrectomy. Eur Urol Focus 2023;9:345-51.

    Goldenberg, Mitchell G / Cacciamani, Giovanni E

    European urology focus

    2022  Volume 9, Issue 3, Page(s) 550–551

    MeSH term(s) Humans ; Robotics ; Nomograms ; Robotic Surgical Procedures/adverse effects ; Kidney Neoplasms/surgery ; Nephrectomy/adverse effects
    Language English
    Publishing date 2022-11-24
    Publishing country Netherlands
    Document type Letter
    ISSN 2405-4569
    ISSN (online) 2405-4569
    DOI 10.1016/j.euf.2022.10.015
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  4. Article ; Online: Evidence that surgical performance predicts clinical outcomes.

    Goldenberg, Mitchell G

    World journal of urology

    2019  Volume 38, Issue 7, Page(s) 1595–1597

    Abstract: Purpose: Assessment of surgeon performance in the operating room has been identified as a direct method of measuring surgical quality. Studies published in urology and other surgical disciplines have investigated this link directly by measuring surgeon ... ...

    Abstract Purpose: Assessment of surgeon performance in the operating room has been identified as a direct method of measuring surgical quality. Studies published in urology and other surgical disciplines have investigated this link directly by measuring surgeon and team performance using methodology supported by validity evidence. This article highlights the key findings of these studies and associated underlying concepts.
    Methods: ​Seminal literature from urology and related areas of research was used to inform this review of the performance-outcome relationship in surgery. Current efforts to further our understanding of this concept are discussed, including relevant quality improvement and educational interventions that utilize this relationship.
    Results: Evidence from multiple surgical specialties and procedures has established the association between surgeon skill and clinically significant patient outcomes. Novel methods of measuring performance utilize surgeon kinematics and artificial intelligence techniques to more reliably and objectively quantify surgical performance.
    Conclusions: Future directions include the use of this data to create interventions for quality improvement, as well as innovate the credentialing and recertification process for practicing surgeons.
    MeSH term(s) Clinical Competence ; Forecasting ; Humans ; Treatment Outcome ; Urologic Surgical Procedures/standards ; Urology/standards ; Work Performance
    Language English
    Publishing date 2019-06-29
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 380333-8
    ISSN 1433-8726 ; 0724-4983
    ISSN (online) 1433-8726
    ISSN 0724-4983
    DOI 10.1007/s00345-019-02857-w
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  5. Article: Improving access to surgical innovation in the community: Implementation of shared access model in Canadian healthcare.

    Goldenberg, Mitchell G / Kerbel, Brent / Singal, Rajiv K

    Canadian Urological Association journal = Journal de l'Association des urologues du Canada

    2022  Volume 13, Issue 9, Page(s) E300–E302

    Language English
    Publishing date 2022-11-07
    Publishing country Canada
    Document type Letter
    ZDB-ID 2431403-1
    ISSN 1911-6470
    ISSN 1911-6470
    DOI 10.5489/cuaj.5248
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  6. Article ; Online: From box ticking to the black box: the evolution of operating room safety.

    Goldenberg, Mitchell G / Elterman, Dean

    World journal of urology

    2019  Volume 38, Issue 6, Page(s) 1369–1372

    Abstract: Purpose: Efforts to improve the safety of patients in the operating room have focused on mitigating harm through the standardization of system, team, and human level factors. This article highlights existing and future methods for enhancing safety in ... ...

    Abstract Purpose: Efforts to improve the safety of patients in the operating room have focused on mitigating harm through the standardization of system, team, and human level factors. This article highlights existing and future methods for enhancing safety in the perioperative setting, and the theory and principles that underpin them.
    Methods: Evidence surrounding the development and implementation of select surgical safety interventions is discussed.
    Results: Work in human factors and engineering that has inspired safety interventions such as the WHO Safety Checklist, and more recently operating room recorders, represents a movement away from traditional, retrospective or reactive methods of studying surgical safety, to prospective and proactive ones.
    Conclusions: Future work will examine the effectiveness of these interventions for improving patient outcomes and minimizing iatrogenic harm.
    MeSH term(s) Checklist ; Humans ; Intraoperative Complications/prevention & control ; Operating Rooms ; Patient Safety/standards ; Postoperative Complications/prevention & control ; Urologic Surgical Procedures/standards
    Language English
    Publishing date 2019-07-30
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 380333-8
    ISSN 1433-8726 ; 0724-4983
    ISSN (online) 1433-8726
    ISSN 0724-4983
    DOI 10.1007/s00345-019-02886-5
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  7. Article ; Online: Multi-Modal Deep Learning for Assessing Surgeon Technical Skill.

    Kasa, Kevin / Burns, David / Goldenberg, Mitchell G / Selim, Omar / Whyne, Cari / Hardisty, Michael

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 19

    Abstract: This paper introduces a new dataset of a surgical knot-tying task, and a multi-modal deep learning model that achieves comparable performance to expert human raters on this skill assessment task. Seventy-two surgical trainees and faculty were recruited ... ...

    Abstract This paper introduces a new dataset of a surgical knot-tying task, and a multi-modal deep learning model that achieves comparable performance to expert human raters on this skill assessment task. Seventy-two surgical trainees and faculty were recruited for the knot-tying task, and were recorded using video, kinematic, and image data. Three expert human raters conducted the skills assessment using the Objective Structured Assessment of Technical Skill (OSATS) Global Rating Scale (GRS). We also designed and developed three deep learning models: a ResNet-based image model, a ResNet-LSTM kinematic model, and a multi-modal model leveraging the image and time-series kinematic data. All three models demonstrate performance comparable to the expert human raters on most GRS domains. The multi-modal model demonstrates the best overall performance, as measured using the mean squared error (MSE) and intraclass correlation coefficient (ICC). This work is significant since it demonstrates that multi-modal deep learning has the potential to replicate human raters on a challenging human-performed knot-tying task. The study demonstrates an algorithm with state-of-the-art performance in surgical skill assessment. As objective assessment of technical skill continues to be a growing, but resource-heavy, element of surgical education, this study is an important step towards automated surgical skill assessment, ultimately leading to reduced burden on training faculty and institutes.
    MeSH term(s) Algorithms ; Clinical Competence ; Deep Learning ; Humans ; Surgeons ; Suture Techniques/education
    Language English
    Publishing date 2022-09-27
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s22197328
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  8. Article ; Online: A Novel Method of Setting Performance Standards in Surgery Using Patient Outcomes.

    Goldenberg, Mitchell G / Grantcharov, Teodor P

    Annals of surgery

    2017  Volume 269, Issue 1, Page(s) 79–82

    Abstract: Objective: To describe a novel, outcome-based method of standard setting that differentiates between clinical outcomes rather than arbitrary educational goals.: Background: Standard setting methods used in assessments of procedural skill are ... ...

    Abstract Objective: To describe a novel, outcome-based method of standard setting that differentiates between clinical outcomes rather than arbitrary educational goals.
    Background: Standard setting methods used in assessments of procedural skill are currently not evidence-driven or outcome-based. This represents a potential obstacle for the broad implementation of these evaluations in summative assessments such as certification and credentialing.
    Methods: The concept is based on deriving a receiver operating characteristic curve from a regression model that incorporates measures of intraoperative surgeon performance and confounding patient characteristics. This allows the creation of a performance standard that best predicts a clinically significant outcome of interest. The discovery cohort used to create the predictive model was derived from pilot data that used the Global Evaluative Assessment of Robotic Skill assessment tool to predict patient urinary continence 3 months following robotic-assisted radical prostatectomy.
    Results: A receiver operating characteristic curve with an area under the curve of 0.75 was created from predicted probability statistic generated by the predictive model. We chose a predicted probability of 0.35, based on an optimal tradeoff in sensitivity and specificity (Youden Index). Rearranging the regression equation, we determined the performance score required to predict a 35%, patient-adjusted probability of postoperative urinary incontinence.
    Conclusions: This novel methodology is context, patient, and assessment-specific. Current standard setting methods do not account for the heterogeneity of the clinical environment. Workplace-based assessments in competency-based medical education require standards that are credible to the educator and the trainee. High-stakes assessments must ensure that surgeons have been evaluated to a standard that prioritizes satisfactory patient outcomes and safety.
    MeSH term(s) Clinical Competence/standards ; Follow-Up Studies ; Humans ; Incidence ; Male ; Middle Aged ; Ontario/epidemiology ; Patient Reported Outcome Measures ; Postoperative Complications/epidemiology ; Prostate/surgery ; Prostatectomy/education ; Prostatectomy/methods ; Retrospective Studies ; Robotic Surgical Procedures/education ; Surgeons/education ; Urinary Incontinence/epidemiology
    Language English
    Publishing date 2017-11-28
    Publishing country United States
    Document type Journal Article
    ZDB-ID 340-2
    ISSN 1528-1140 ; 0003-4932
    ISSN (online) 1528-1140
    ISSN 0003-4932
    DOI 10.1097/SLA.0000000000002562
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  9. Article ; Online: Psychology and learning: The role of the clinical learning environment.

    Caverzagie, Kelly J / Goldenberg, Mitchell G / Hall, Jena M

    Medical teacher

    2019  Volume 41, Issue 4, Page(s) 375–379

    Abstract: The clinical learning environment for the postgraduate education of physicians significantly influences the learning process and the outcomes of learning. Two critical aspects of the learning environment, when viewed through a psychology lens are (1) ... ...

    Abstract The clinical learning environment for the postgraduate education of physicians significantly influences the learning process and the outcomes of learning. Two critical aspects of the learning environment, when viewed through a psychology lens are (1) constructs from psychology relevant to learning, such as cognitive load theory and learner self-efficacy; and (2) psychological attributes of the context in which learning occurs such as psychological safety and "Just Culture". In this paper, we address selected psychological aspects of the clinical learning environment, with a particular focus on the establishment and sustainment of psychological safety in the clinical learning environment for physicians. Psychological safety is defined as individuals' perceptions that they can speak out in the learning or working context without consequences for their professional standing or risks to their status on work teams or groups. We close with seven critical strategies for use by educators, learners, health systems leaders, and other stakeholders to contribute to a clinical environment that optimizes learning. These dimensions can also provide avenues for future research to enhance the community's understanding of psychological constructs operating in the clinical learning environment.
    MeSH term(s) Clinical Competence/standards ; Environment ; Group Processes ; Health Personnel/education ; Health Personnel/psychology ; Humans ; Learning ; Motivation ; Resilience, Psychological ; Self Efficacy ; Social Environment ; Workplace/psychology
    Language English
    Publishing date 2019-02-14
    Publishing country England
    Document type Journal Article
    ZDB-ID 424426-6
    ISSN 1466-187X ; 0142-159X
    ISSN (online) 1466-187X
    ISSN 0142-159X
    DOI 10.1080/0142159X.2019.1567910
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  10. Article ; Online: Can video games enhance surgical skills acquisition for medical students? A systematic review.

    Gupta, Arnav / Lawendy, Bishoy / Goldenberg, Mitchell G / Grober, Ethan / Lee, Jason Y / Perlis, Nathan

    Surgery

    2021  Volume 169, Issue 4, Page(s) 821–829

    Abstract: Objective: To systematically assess literature examining the impact of being a gamer or participating in video-game-based training on surgical skills acquisition amongst medical students.: Background: Video games and surgical procedures share similar ...

    Abstract Objective: To systematically assess literature examining the impact of being a gamer or participating in video-game-based training on surgical skills acquisition amongst medical students.
    Background: Video games and surgical procedures share similar skills such as visuospatial abilities and hand-eye coordination; therefore, video games can be a valuable tool for surgical training amongst medical students. However, comprehensive, up-to-date systematic reviews are necessary to confirm.
    Methods: A systematic literature search of PubMed, MEDLINE, and EMBASE was performed in April 2020 with no limits set on the date of publication. Observational and randomized controlled studies were included. Quality and bias were assessed using the Newcastle-Ottawa Scale for nonrandomized studies and the Grading of Recommendations Assessment, Development and Evaluation system for randomized studies.
    Results: A total of 575 participants from 16 studies were included. The most common surgical skills tested were laparoscopy (n = 283, from 8 studies) and robotic surgery (n = 199, from 5 studies). A history of gaming and video-game-based training were associated with improved metrics in robotic surgery and laparoscopy, respectively. Neither was beneficial in arthroscopy or bronchoscopy. Studies using the Wii U and Underground reported significant improvement in overall laparoscopic performance.
    Conclusion: Video games demonstrate potential as adjunctive training in surgical skill education, with a history of gaming and video-game-based training being beneficial in robotic surgery and laparoscopy, respectively. Methodological heterogeneity amongst included studies limit the ability to make conclusive decisions; thus, future studies with long-term follow-up, larger sample sizes, outcomes stratified by video-game characteristics, and up-to-date technology are necessary.
    MeSH term(s) Clinical Competence ; Education, Medical ; General Surgery/education ; Humans ; Robotic Surgical Procedures ; Simulation Training ; Students, Medical ; Surgeons ; Video Games
    Language English
    Publishing date 2021-01-05
    Publishing country United States
    Document type Journal Article ; Meta-Analysis ; Systematic Review
    ZDB-ID 202467-6
    ISSN 1532-7361 ; 0039-6060
    ISSN (online) 1532-7361
    ISSN 0039-6060
    DOI 10.1016/j.surg.2020.11.034
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