Operationalizing AI in Orthopaedic Practice: Governance, Integration, and Future Clinical Applications
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Operationalizing AI in Orthopaedic Practice: Governance, Integration, and Future Clinical Applications
Wednesday, October 1, 2025
1:00 - 2:00 pm ET
Cost:
Members - Free
Non-Members - $50
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This panel examines the responsible use of AI in orthopedic clinics and ASCs with emphasis on governance, procurement, and practical value-based implementation. Faculty will review privacy and security requirements (HIPAA/BAA, data minimization/retention, auditability, human-in-the-loop oversight, model monitoring and drift), emerging policies, and outline a procurement framework for orthopedic practices, including due-diligence criteria (SOC 2/ISO controls, PHI handling, EHR/FHIR connectivity, data-use terms, service levels, total cost of ownership). A concise market map will situate major categories—ambient documentation, patient messaging & PROMs, scheduling and ASC coordination, revenue cycle/prior auth, and analytics—alongside an evidence-informed discussion of current capabilities and limitations of large language models. The session will highlight evaluation methods, live demonstrations of use cases, governance, and ROI measures.
Hosted by the Department of Orthopaedic Surgery, Duke University School of Medicine. Educational content only
Learning Objectives
- Describe governance requirements for AI use in orthopaedic practice, including PHI protection, BAAs, data retention, human oversight, and model monitoring/drift management.
- Apply a vendor due-diligence and procurement checklist (security attestations, audit logs, EHR/FHIR integration, data-use/ownership terms, support model, and TCO).
- Differentiate high-yield clinical and operational use cases (e.g., ambient scribe, inbox management, PROMs, scheduling/ASC coordination, ambient documentation) and the current limits of LLM-based tools.
- Select appropriate evaluation and ROI measures (documentation time, throughput, no-show rate, call handling, prior-auth time, PROM completion) and incorporate equity/safety considerations (bias, hallucination, data leakage) into ongoing oversight.
- Understand the promise and shortcomings of generative AI today, what is possible, what isn’t and what the future holds.
Hosted by the Department of Orthopaedic Surgery at Duke University School of Medicine
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For more information, contact info@aaoe.net.
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Registration Options
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Registration Options
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Price |
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Non-Member Registration
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$50.00 |
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Member Registration
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Product Add-ons
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| Webinar Enhancements View Product | $29.00 |
Paul Bruning, DHA
Division Administrator, Department of Orthopaedics at Duke University
Dr. Bruning is the Division Administrative Director for Sports Medicine, Hand, and the Sports Sciences Institute, Department of Orthopedics, Duke University School of Medicine. He has been within the orthopedic field for over 35 years. Dr. Bruning has served on the Board of Directors for the AAOE, ATPPS, BONES of Florida, and been the Advocacy Council Chair for AAOE.
David Claxton
Senior IT Consultant, Duke University
David Claxton is a Senior IT Consultant specializing in AI and technology enablement at Duke Health. With over a decade of experience—including a two-year stint in the startup world—David brings a unique blend of enterprise insight and innovation agility to his work. He plays a pivotal role in advancing ambient technologies, digital workflows, and strategic AI integrations across clinical and operational domains. His recent initiatives include leading the rollout of Abridge’s ambient listening technology to over 2,000 clinicians. David is a trusted collaborator among clinical leaders and digital strategists, known for his ability to translate complex technical solutions into scalable, patient-centered innovations.
Christian Pena, MD
Department of Orthopaedics at Duke University
Michael Pencina PhD
Professor of Biostatistics and Bioinformatics, Duke University
Michael J. Pencina, PhD, is Duke Health's chief data scientist and serves as vice dean for data science, director of Duke AI Health, and professor of biostatistics and bioinformatics at the Duke University School of Medicine. His work bridges fields of data science, health care, and AI, and contributes to Duke’s national leadership in responsible health AI. He partners with leaders to develop data science strategies for Duke Health that span and connect academic research and clinical care. Dr. Pencina is an internationally recognized authority in the evaluation of AI algorithms. He co-founded and co-leads the national Coalition for Health AI (CHAI), a multi-stakeholder effort whose mission is to develop best practices to drive high-quality health care by promoting implementation of innovative, credible, and transparent health AI systems. He serves in a leadership capacity for the Trustworthy & Responsible AI Network (TRAIN), an organization Duke co-founded with leading health care and technology organizations to develop tools and technologies that promote adoption of high-quality, novel and safe health AI solutions for patient care and research. Thomson Reuters/Clarivate Analytics acknowledges Dr. Pencina as one of the world’s "highly cited researchers" in clinical medicine and social sciences, with over 450 publications cited 150,000 times.