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Integrating Artificial Intelligence-Based Simulation into Serious Illness Conversation Training: A Pilot Medical
Lori A Herbst1,2, Daniel Kadden3,4, Danielle E Weber2,5
1Department of Anesthesia, Division of Palliative Medicine, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.
Journal of Palliative Medicine
|June 10, 2026
Summary
Artificial intelligence (AI) offers a new way for medical students to practice serious illness conversations (SICs). This pilot study found AI tools can provide valuable practice and feedback for these crucial discussions.
Area of Science:
- Medical Education
- Artificial Intelligence in Healthcare
- Communication Skills Training
Background:
- Serious illness conversations (SICs) are crucial in medical care but challenging for trainees.
- Current educational methods for SICs are often time- and resource-intensive.
- Trainee discomfort with SICs necessitates innovative training solutions.
Purpose of the Study:
- To explore the utility of artificial intelligence (AI) technology for practicing serious illness conversations (SICs).
- To evaluate AI-driven feedback on student performance in simulated SICs.
- To assess the feasibility of AI as a training tool for advance care planning (ACP).
Main Methods:
- Eleven medical students utilized an AI platform (2-Sigma) for SIC practice.
- Students engaged in 27 simulated cases based on an Advance Care Planning (ACP) curriculum.
- Transcripts of student-AI interactions were analyzed for interaction patterns, AI responses, and feedback quality.
Main Results:
- Students applied ACP curriculum skills during AI-driven SIC practice.
- AI responses demonstrated emotional awareness and effectively managed negative affect.
- AI feedback covered key SIC components but showed variability in specificity.
Conclusions:
- AI technology shows promise as a supplementary tool for practicing SIC skills.
- AI simulation can enhance trainee confidence and competence in serious illness communication.
- Further research is warranted to optimize AI feedback for SIC training.
