Root Cause Analysis Training for Healthcare Professionals With AI-Powered Virtual Simulation: A Proof-of-Concept

2025-08-06

AI Summary

Current root cause analysis (RCA) training for healthcare professionals is resource-intensive, inconsistently implemented, and suffers from limited scalability—hindering systematic competency development. To address these challenges, this study introduces an AI-driven 3D immersive simulation training system that instantiates a virtual intensive care unit (ICU) environment. Users collaboratively investigate and report adverse events with intelligent, emotionally expressive virtual agents featuring natural language interaction, affective text-to-speech (TTS), and real-time generative character animation. This work represents the first integration of large language models (LLMs), affective TTS, and dynamic procedural animation to deliver personalized, context-aware feedback and high-fidelity presence. A deployable prototype has been developed for high-risk clinical settings. Subsequent empirical evaluation will assess its efficacy in enhancing RCA proficiency and fostering a robust patient safety culture.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search

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.

Problem

• High resource demands limit RCA training in healthcare
• Insufficient training leads to inconsistent RCA implementation
• Need for cost-effective, scalable RCA training solutions

Innovation

• AI-powered 3D simulation game for RCA training
• Natural interactions with avatars using LLMs
• Formative and summative feedback via LLM