Towards an Agent-Based Simulation of Hospital Emergency Departments

Stainsby, Hayden D.; Taboada, Manel; Luque, Emilio

doi:10.1109/scc.2009.53

Cited by 40 publications

(25 citation statements)

References 12 publications

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“…Basic rules governing the actions of the individual agents are defined, in an attempt to understand micro level behavior. The macro level behavior, that of the system as a whole, emerges as a result of the actions of these basic building blocks, from which an understanding of the reasons for system level behavior can be derived [18].…”

Section: Related Workmentioning

confidence: 99%

Optimization of Healthcare Emergency Departments by Agent-Based Simulation

Cabrera

Taboada²,

Iglesias³

et al. 2011

Procedia Computer Science

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This paper presents an Agent-Based modeling and simulation to design a decision support system (DSS) for the operation of Healthcare Emergency Departments (ED). This DSS aims to aid EDs managers in setting up strategies and management guidelines to optimize the operation of EDs. This ongoing research is being performed by the Research Group on Individual Oriented Modeling (IoM) of CAOS in the University Autonoma of Barcelona (UAB) in close collaboration with Hospital ED Staff. The simulation main objective is to optimize the performance of such complex and dynamic Healthcare ED. Optimization is performed to find the optimal ED staff configuration, which consists of doctors, triage nurses, and admission personnel, i.e. a multidimensional problem. Two different indexes, to minimize patient waiting time, and to maximize patient throughput, were proposed and tested and their results obtained appying an exhaustive search technique, yield promising results and better understanding of the problem.

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Section: Related Workmentioning

confidence: 99%

Optimization of Healthcare Emergency Departments by Agent-Based Simulation

Cabrera

Taboada²,

Iglesias³

et al. 2011

Procedia Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…System engineering process was poorly reported in the founded literature apart from [26] which was published in a computing conference and described the iterative process of designing and modelling that was done. Interestingly , [17] have stated their iterative process to be as the called it ' cycles'.…”

Section: Engineering Processmentioning

confidence: 99%

Simulation Modelling in Healthcare: Challenges and Trends

Almagooshi

2015

Procedia Manufacturing

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In this paper, we describe simulation models in healthcare that have been developed in the past two decades. Simulation systems, ranging from simulation of patient flow in emergency rooms to simulation of populations with a specific chronic diseases, are reviewed. Simulation types included discrete event simulation (DES) and agent based simulation (ABS). A trend of variability and scalability were identified, and discussed in terms of platform used to develop the model, data sources, and computational power needed to run the simulation. In the synthesis of simulation models, programming languages and products emerged as clusters. Design models and systems engineering development processes are examined with a focus on requirements discovery, models and scenarios of simulation. Graphic user interfaces in the simulation tools in healthcare are reviewed in terms of visual design and human factors. Furthermore, interaction modes and trends of information visualization techniques used for the simulations are reported. Agent-based simulation models in particular were reviewed, and findings suggest agent characteristics varied across literature researched in aspects such as socio-demographic design considerations.

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“…ABS has been also applied in healthcare. Stainsby, Taboada, and Luque (2009) have used agents to model hospital emergency departments; Sibbel and Urban (2001) have integrated agent-based approaches into classical simulation systems to enable better hospital management. The reader is referred to Mustafee et al (2010) and Katsaliaki and Mustafee (2011) for further discussion on ABS in the context of healthcare (including its application compared to other simulation techniques like discrete-event simulation, Monte Carlo simulation and system dynamics).…”

Section: Agent-based Simulation (Abs)mentioning

confidence: 99%

Proximity-based modelling of cross-contamination through agent-based simulation: a feasibility study

et al. 2013

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Proximity-based modelling methodology enables mathematical representation of a real system that is characterised by the existence of entities that come into physical contact. Healthcare systems can benefit from this methodology since physical proximity between entities (e.g., patients, clinical items like surgical equipment and blood units) can result in the spread of infectious diseases and cross-contamination. The existing analytical techniques, which are mainly based on differential equations, are unsuitable for representing the fine-grained, micro-world view of the entity interactions that we intend to model. We therefore extend Agent-Based Simulation (ABS) by enabling individual agents to be aware of the physical location of the other agents being modelled in a 3-Dimensional space -this is a perquisite for our proximitybased modelling methodology. To demonstrate the feasibility of our approach we experiment with a scenario wherein boxes of degradable clinical items, modelled as agents, are stored in close proximity. We use Cutting and Packing Optimisation (CPO) algorithms from literature to define the arrangement of these agents in the 3-D space and to make the individual agents "location-aware". An ABS model then simulates crosscontamination by modelling the spread of contaminants amongst the agents confined in the well-defined space. Our approach can be used to model analogous situations wherein physical proximity between entities in the underlying system is a necessary condition for entity interactions.

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Towards an Agent-Based Simulation of Hospital Emergency Departments

Cited by 40 publications

References 12 publications

Optimization of Healthcare Emergency Departments by Agent-Based Simulation

Optimization of Healthcare Emergency Departments by Agent-Based Simulation

Simulation Modelling in Healthcare: Challenges and Trends

Proximity-based modelling of cross-contamination through agent-based simulation: a feasibility study

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