用混合仿真模型模拟急诊科，验证其可复现真实运行效果。
Multi-Agent Systems in Emergency Departments: Validation Study on a ED Digital Twin
- 构建基于离散事件与代理的混合模型，灵活模拟不同规模急诊科。
- 模型关键指标与文献数据匹配，验证了其对真实动态的还原能力。
- 集成多智能体系统，自动探索资源分配策略，适合医疗管理研究者。
急诊科面临患者护理与资源配置挑战。本文提出一种融合离散事件模拟（DES）与代理建模（ABM）的混合模型，用于在高度可配置的急诊科环境中探索优化策略。模型参数基于真实研究，涵盖急诊科规模、患者负荷和人员配置。通过将模型的关键绩效指标与文献中已知数值对比，验证了其表达能力。随后，引入已被科学证实和实践验证的资源优化策略。将模型结果与实际记录对比，表明该DES-ABM仿真能有效复现干预下的真实急诊科动态。最后，集成一个概念验证级多智能体系统（MAS），基于急诊事件记录的时间账本，自主探索资源分配策略。该模块化框架为急诊科资源优化研究提供有力工具。
原文摘要 · Abstract (English)
Emergency departments (ED) face challenges in patient care and resource management. We propose to explore optimization strategies in a realistic and flexible model and develop a hybrid Discrete Event Simulation (DES) and Agent-Based Model (ABM) simulating highly configurable ED environments. We specifically focus on the validation of the modeling approach. We derive configurations for ED sizes, patient load, and staffing from real-world studies. We then validate the model expressivity by matching its key performance indicators and metrics with their values known from literature. We proceed by implementing scientifically established and practice-proven resource optimization strategies. Comparing the documented real-world outcomes with our model's results demonstrates that the DES-ABM based simulation can effectively replicate real-world ER dynamics under interventions. We lastly integrate a Proof-of-Concept multi-agent system (MAS) that can autonomously explore resource allocation strategies within the simulated ER environment based on a temporal ledger of ED event records. This modular DES-ABM-MAS framework offers a powerful tool to explore resource optimization strategies in emergency departments.
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