Browsing by Author "Sachdeva, Ajit K."

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    Artificial Intelligence Methods and Artificial Intelligence-Enabled Metrics for Surgical Education: A Multidisciplinary Consensus
    (Wolters Kluwer, 2022) Vedula, S. Swaroop; Ghazi, Ahmed; Collins, Justin W.; Pugh, Carla; Stefanidis, Dimitrios; Meireles, Ozanan; Hung, Andrew J.; Schwaitzberg, Steven; Levy, Jeffrey S.; Sachdeva, Ajit K.; Collaborative for Advanced Assessment of Robotic Surgical Skills; Surgery, School of Medicine
    Background: Artificial intelligence (AI) methods and AI-enabled metrics hold tremendous potential to advance surgical education. Our objective was to generate consensus guidance on specific needs for AI methods and AI-enabled metrics for surgical education. Study design: The study included a systematic literature search, a virtual conference, and a 3-round Delphi survey of 40 representative multidisciplinary stakeholders with domain expertise selected through purposeful sampling. The accelerated Delphi process was completed within 10 days. The survey covered overall utility, anticipated future (10-year time horizon), and applications for surgical training, assessment, and feedback. Consensus was agreement among 80% or more respondents. We coded survey questions into 11 themes and descriptively analyzed the responses. Results: The respondents included surgeons (40%), engineers (15%), affiliates of industry (27.5%), professional societies (7.5%), regulatory agencies (7.5%), and a lawyer (2.5%). The survey included 155 questions; consensus was achieved on 136 (87.7%). The panel listed 6 deliverables each for AI-enhanced learning curve analytics and surgical skill assessment. For feedback, the panel identified 10 priority deliverables spanning 2-year (n = 2), 5-year (n = 4), and 10-year (n = 4) timeframes. Within 2 years, the panel expects development of methods to recognize anatomy in images of the surgical field and to provide surgeons with performance feedback immediately after an operation. The panel also identified 5 essential that should be included in operative performance reports for surgeons. Conclusions: The Delphi panel consensus provides a specific, bold, and forward-looking roadmap for AI methods and AI-enabled metrics for surgical education.
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    The Blue Ribbon Committee II Report and Recommendations on Surgical Education and Training in the United States: 2024
    (Wolters Kluwer, 2024) Stain, Steven C.; Ellison, Christopher; Farmer, Diana L.; Flynn, Timothy C.; Freischlag, Julie A.; Matthews, Jeffrey B.; Newman, Rachel W.; Chen, Xiaodong; Stefanidis, Dimitrios; Britt, L. D.; Buyske, Jo; Fisher, Karen; Sachdeva, Ajit K.; Turner, Patricia L.; Blue Ribbon Committee II; Surgery, School of Medicine
    Objective: An expert panel made recommendations to optimize surgical education and training based on the effects of contemporary challenges. Background: The inaugural Blue Ribbon Committee (BRC I) proposed sweeping recommendations for surgical education and training in 2004. In light of those findings, a second BRC (BRC II) was convened to make recommendations to optimize surgical training considering the current landscape in medical education. Methods: BRC II was a panel of 67 experts selected on the basis of experience and leadership in surgical education and training. It was organized into subcommittees which met virtually over the course of a year. They developed recommendations, along with the Steering Committee, based on areas of focus and then presented them to the entire BRC II. The Delphi method was chosen to obtain consensus, defined as ≥80% agreement among the panel. Cronbach α was computed to assess the internal consistency of 3 Delphi rounds. Results: Of the 50 recommendations, 31 obtained consensus in the following aspects of surgical training (# of consensus recommendation/# of proposed): Workforce (1/5); Medical Student Education (3/8); Work Life Integration (4/6); Resident Education (5/7); Goals, Structure, and Financing of Training (5/8); Education Support and Faculty Development (5/6); Research Training (7/9); and Educational Technology and Assessment (1/1). The internal consistency was good in Rounds 1 and 2 and acceptable in Round 3. Conclusions: BRC II used the Delphi approach to identify and recommend 31 priorities for surgical education in 2024. We advise establishing a multidisciplinary surgical educational group to oversee, monitor, and facilitate implementation of these recommendations.