Multi-Agent Systems in Emergency Departments: Validation Study on a ED Digital Twin

TL;DR

This paper presents a validated hybrid simulation model combining Discrete Event Simulation and Agent-Based Modeling to optimize resource management in emergency departments, demonstrating effective replication of real-world dynamics.

Contribution

It introduces a modular DES-ABM framework validated against real-world data and integrates a multi-agent system for autonomous resource strategy exploration.

Findings

Model accurately replicates ED performance metrics from literature.

Simulation effectively evaluates resource optimization strategies.

Multi-agent system autonomously explores resource allocation options.

Abstract

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.