Show Notes
Digital surgery has morphed from buzzword into ubiquitous high-impact technology. In this episode, the BTK MIS team steps into the rapidly evolving ecosystem of cameras, sensors, robotics, and software that are turning surgical operations into structured, analyzable datasets. From AI segmentation to real-time telepresence, don’t miss this opportunity to catch up on what’s new and what’s next, what’s exciting and what’s terrifying, just on the horizon of your surgical career. Hosts: · James Jung, MD, PhD, Assistant Professor of Surgery, Duke University · Jacob Greenberg, MD, EdM, MIS Division Chief and Vice Chair for Education, Duke University · Zachary Weitzner, MD, Minimally Invasive and Bariatric Surgery Fellow, Duke University, @ZachWeitznerMD · Joey Lew, MD, MFA, Surgical resident PGY-3, Duke University, @lew__actually Learning Goals: By the end of this episode, listeners will be able to: · Define “digital surgery” and describe its core components, including video capture, instrumentation, robotics, data analytics, and system connectivity. · Discuss current and emerging applications of digital surgery in surgical education, including video-based self-assessment, procedural segmentation, and structured feedback models. · Describe how digital tools can be used to improve OR efficiency and resource utilization, including instrumentation usage, operative time analysis, and workflow optimization. · Summarize current telepresence and teleproctoring technologies and their clinical use cases, including augmented reality–based collaboration across institutions and geographic boundaries. · Identify key ethical, legal, and operational challenges in digital and tele-surgery, including credentialing, cross-state licensure, liability, and trust in remote expertise. · Discuss how digital surgery may reshape surgical training and competency-based assessment, including implications for autonomy, deliberate practice, and feedback frequency. · Recognize future directions of digital surgery integration, including predictive analytics, simulation using patient-specific imaging, and AI-assisted intraoperative decision support. References:
Balvardi S, Semsar-Kazerooni K, Kaneva P, et al. Validity of video-based general and procedure-specific self-assessment tools for surgical trainees in laparoscopic cholecystectomy. Surg Endosc. 2023;37(3):2281-2289. doi:10.1007/s00464-022-09466-6 [https://pubmed.ncbi.nlm.nih.gov/36307525/]
Hospital Utilizes Intraoperative Idle Time Metrics to Improve Surgical Safety and Efficiency. Theator | The Surgical Intelligence Company. Accessed March 20, 2026. https://theator.io/customer-story/hospital-utilizes-intraoperative-idle-time-metrics-to-improve-surgical-safety-and-efficiency/
Campbell KK, Abreu AA, Zeh HJ, et al. Using OR Black Box Technology to Determine Quality Improvement Outcomes for In-situ Timeout and Debrief Simulation. Ann Surg. 2026;283(1):122. doi:10.1097/SLA.0000000000006438 [https://pubmed.ncbi.nlm.nih.gov/38317208/]
Al Abbas AI, Meier J, Daniel W, et al. Impact of team performance on the surgical safety checklist on patient outcomes: an operating room black box analysis. Surg Endosc. 2024;38(10):5613-5622. doi:10.1007/s00464-024-11064-7 [https://pubmed.ncbi.nlm.nih.gov/39069926/]
Proximie’s telepresence platform helps surgeons across the globe grow and exchange experience in real-time. World Health Expo Insights. Accessed March 20, 2026. https://www.worldhealthexpo.com/insights/telemedicine/proximie-s-telepresence-platform-helps-surgeons-across-the-globe-grow-and-exchange-experience-in-real-time
Hassan AE, Desai SK, Georgiadis AL, Tekle WG. Augmented reality enhanced tele-proctoring platform to intraoperatively support a neuro-endovascular surgery fellow. Interv Neuroradiol. 2022;28(3):277-282. doi:10.1177/15910199211035304 [https://pubmed.ncbi.nlm.nih.gov/34538166/]
SAGES Digital Surgery Working Group; Ali JT, Yang G, Green CA, Reed BL, Madani A, Ponsky TA, Hazey J, Rothenberg SS
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