Advancing the Science of AI in Healthcare Simulation
AI-enhanced technologies must be validated before entering patient care, and healthcare simulation is uniquely positioned to serve as the optimal testing ground. AI-HCS is a leading force in establishing practical pathways for integrating AI into healthcare and health professions education. Our Collaborative advances the field through evidence-based research, rigorous validation studies, benchmarking initiatives, and the development of standards that ensure the safe, effective, and responsible use of AI in healthcare simulation.
Our Research Agenda
Since our conception as a Collaborative in 2022, we have been working to create a field-wide research agenda. The 2024 Summit has identified the following research priorities.
Data Collection and Usage in AI Models
A deeper understanding of how data is collected, shared, and valued is essential for building generalizable, unbiased, and trustworthy AI models in simulation.
Interdisciplinary Collaboration and Resource Considerations
Effective AI simulation requires collaboration across disciplines and adequate infrastructural resources to ensure equitable and scalable implementation.
Actionable Research Goals and Collaboration Platforms
Clear problem definitions and collaborative research structures are needed to ensure reproducibility and accelerate progress in AI-driven simulation.
AI in Simulation-Based Healthcare Education and Research Agenda
AI offers transformative potential for assessment, program design, and research, requiring careful evaluation of validity, objectivity, and human–AI interactions.
AI as an Augmentation Tool in Education
AI should enhance—not replace—educators by providing personalized learning experiences, consistent feedback, and support for modernizing instructional methods.
Research Priorities and Public–Private Partnerships
Advancing AI in simulation depends on strong partnerships, thoughtful regulation, and user-centered design to support safe and effective adoption.
Mismatch Between Technology and Educational Needs
Closing the gap between AI capabilities and educational priorities requires collective identification of major instructional challenges and deliberate alignment with teaching needs.
Identified Research Priorities
Appendix I of the 2024 AI Healthcare Simulation Collaborative Summit outlines a list of specific research priorities.
Simulation-AI Outcomes Registry
A voluntary registry designed to correlate AI-enhanced simulation training with measurable clinical and operational outcomes across healthcare systems.
