Presentation
Building a Simulation-Based Evaluation Framework for AI-Enabled Medical Devices
DescriptionHealth systems are increasingly faced with evaluating digital and AI-enabled medical devices before clear clinical use cases, risk models, or usability data exist. This panel introduces a simulation-based framework designed to streamline the intake, triage, and evaluation of human factors (HF) projects for such technologies. Drawing on experience from Mayo Clinic’s Multidisciplinary Simulation Center and AI Validation and Stewardship Program, the framework integrates four pillars: (1) intake and scoping, (2) simulation modality mapping, (3) evidence and data strategy, and (4) AI-aware evaluation.
Real-world examples—including early evaluation of a connected stethoscope platform—illustrate how simulated-use accelerates readiness for machine learning features while maintaining regulatory alignment (IEC 62366-1/ISO 14971). Panelists will demonstrate how partnership between simulation and HF can anticipate usability and workflow challenges, mitigate automation bias, and prepare devices for safe AI integration. The discussion will include tools and strategies that simulation and HF professionals can adapt for their own organizations, providing actionable resources and deeper system-integration insight.
Takeaway Points
• Simulation-based frameworks can make AI-enabled medical device testing faster, more consistent, and regulation-ready.
• Reusable tooling to enhance efficiency and cross-study comparability.
• Collaboration among simulation, HF, and AI teams strengthens clinician trust and post-deployment safety.
• Practical case study—including resources and governance hooks—enable attendees to replicate or scale similar AI-readiness programs.
Real-world examples—including early evaluation of a connected stethoscope platform—illustrate how simulated-use accelerates readiness for machine learning features while maintaining regulatory alignment (IEC 62366-1/ISO 14971). Panelists will demonstrate how partnership between simulation and HF can anticipate usability and workflow challenges, mitigate automation bias, and prepare devices for safe AI integration. The discussion will include tools and strategies that simulation and HF professionals can adapt for their own organizations, providing actionable resources and deeper system-integration insight.
Takeaway Points
• Simulation-based frameworks can make AI-enabled medical device testing faster, more consistent, and regulation-ready.
• Reusable tooling to enhance efficiency and cross-study comparability.
• Collaboration among simulation, HF, and AI teams strengthens clinician trust and post-deployment safety.
• Practical case study—including resources and governance hooks—enable attendees to replicate or scale similar AI-readiness programs.
Moderators
Senior Digital Strategist
Event Type
Discussion Panel
TimeTuesday, March 243:30pm - 4:30pm EDT
LocationMorgan