Risk Management Education Program - Online Registration

Register for AI in Clinical Practice: EMR Integration, Legal Implications and the Road Ahead

Presented by John Sly, Esq.

Live In-Person

This 2-hour course for physicians, healthcare administrators, and legal professionals explores the intersection of artificial intelligence (AI) and medical malpractice, equipping participants with strategies to harness AI safely while minimizing liability. Beginning with foundational concepts—distinguishing AI, machine learning (ML), and natural language processing (NLP)—and types of tools like chatbots and decision-support systems, the session examines standalone AI applications (e.g., symptom checkers like Babylon) and their risks, including misinformation and patient safety gaps. It delves into AI integration in electronic medical records (EMRs), such as Epic’s ambient scribes, and workflow challenges like alert fatigue. Legal frameworks, including the 21st Century Cures Act’s interoperability mandates, the Information Blocking Rule’s obligations, and emerging liabilities (e.g., vendor vs. provider responsibility for AI failures), are analyzed alongside best practices for documentation, clinician overrides, and preserving judgment. The course concludes with future trends, such as AI agents and evolving FDA regulations on Software as a Medical Device (SaMD), fostering proactive risk management in an AI-driven landscape.

Learning Objectives

By the end of this course, participants will be able to:

  • Define key AI concepts (e.g., AI vs. ML vs. NLP) and identify types of clinical tools (e.g., chatbots, embedded algorithms) to evaluate their appropriate use.
  • Assess risks of standalone AI tools in clinical settings, such as diagnostic errors from symptom checkers, and implement safeguards against misinformation.
  • Explain AI-EMR integrations (e.g., ambient scribes, risk prediction) and their impacts on workflows, including strategies to combat alert fatigue.
  • Outline the 21st Century Cures Act, Cures Rule, and Information Blocking provisions, including obligations for AI transparency and interoperability.
  • Analyze emerging malpractice issues, such as liability for AI reliance, informed consent for algorithmic decisions, and standards of care under medical board scrutiny.
  • Apply best practices for AI risk mitigation, including documentation of tool use, override policies, and maintaining clinical oversight, while anticipating trends like regulatory changes in SaMD.

5774 - AI in Clinical Practice: EMR Integration, Legal Implications and the Road Ahead

June 11, 2026
6:00 pm - 8:00 pm

Columbia

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