Root Cause Analysis Training for Healthcare Professionals With AI-Powered Virtual Simulation: A Proof-of-Concept
August 06, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Yuqi Hu, Qiwen Xiong, Zhenzhen Qin, Brandon Watanabe, Yujing Wang, Mirjana Prpa, Ilmi Yoon
arXiv ID
2508.04904
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Root Cause Analysis (RCA) is a critical tool for investigating adverse events in healthcare and improving patient safety. However, existing RCA training programs are often limited by high resource demands, leading to insufficient training and inconsistent implementation. To address this challenge, we present an AI-powered 3D simulation game that helps healthcare professionals develop RCA skills through interactive, immersive simulations. This approach offers a cost-effective, scalable, and accessible alternative to traditional training. The prototype simulates an RCA investigation following a death in the ICU, where learners interview five virtual avatars representing ICU team members to investigate the incident and complete a written report. The system enables natural, life-like interactions with avatars via large language models (LLMs), emotional text-to-speech, and AI-powered animations. An additional LLM component provides formative and summative feedback to support continual improvement. We conclude by outlining plans to empirically evaluate the system's efficacy.
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