AI integration for simulation recording and debriefing platforms in healthcare training : a narrative literature review

Abstract

This thesis investigates how artificial intelligence (AI) and data analytics can be integrated into simulation recording and debriefing platforms for healthcare training. A narrative review was conducted to examine current AI applications, support for educators, and future development directions. The findings show that AI can support transcription, summarization, performance analysis, and multimodal assessment, while evidence of direct improvements in educational outcomes remains limited. AI is currently most valuable as a tool supporting educators without replacing them, particularly by reducing the workload of reviewing and analysing simulation data. The review also identifies challenges in data privacy, transparency, interoperability, trust, and organizational readiness. Based on these findings, this thesis proposes a three-horizon practical roadmap that offers practical guidance for developing and adopting AI-enabled simulation recording and debriefing platforms in healthcare education. The roadmap includes three horizons, providing the sequences of AI development from simple, low-risk capabilities to more advanced multimodal applications.