A Customizable Agent-Based Simulation Framework for Emergency Departments

Emergency Departments (EDs) face increasing complexity due to rising patient demand, resource constraints, and the need for efficient service coordination. Traditional simulation models, while useful, cannot be easily adapted to a different hospital environments, making it difficult to transfer and...

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Detalles Bibliográficos
Autores: Mesas Cervilla, Francisco|||0009-0007-9399-6298, Taboada González, Manuel, Rexachs, Dolores|||0000-0001-5500-850X, Epelde, Francisco|||0000-0001-5547-4025, Wong, Álvaro|||0000-0002-8394-9478, Luque, Emilio|||0000-0002-2884-3232
Tipo de recurso: capítulo de libro
Fecha de publicación:2025
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:dnet:uabarcelona_::cf1576a5a3d2d2bbd6c52a44bbc3d7fd
Acceso en línea:https://ddd.uab.cat/record/318331
https://dx.doi.org/urn:doi:10.1007/978-3-031-97635-3_6
Access Level:acceso embargado
Palabra clave:Adaptive Healthcare Modeling
Agent Based Modeling
Emergency Departments
Modular Simulation Framework
Resource Optimization
Descripción
Sumario:Emergency Departments (EDs) face increasing complexity due to rising patient demand, resource constraints, and the need for efficient service coordination. Traditional simulation models, while useful, cannot be easily adapted to a different hospital environments, making it difficult to transfer and scale solutions. Based on previous work, with a simulator working in a hospital, this work describes a modular Agent-Based Modeling and Simulation (ABMS) approach for increasing flexibility adaptation and reuse in ED simulations. The proposed technique, which deconstructs existing models into individual components, will allow hospitals with different workflows and operational constraints to construct customized simulations. To validate this methodology, we develop a structured, modular framework using NetLogo and Python. The suggested metasystem enables adaptive simulation-based decision assistance for emergency departments, which improves resource allocation and operational planning.