An Agent-Based Decision Support System for Hospitals Emergency Departments

Taboada, Manel; Cabrera, Eduardo; Iglesias, Ma Luisa; Epelde, Francisco; Luque, Emilio

doi:10.1016/j.procs.2011.04.203

Cited by 67 publications

(38 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As detailed below, we follow the analysis of Taboada et al [10] that introduces two distinct types of agents for an emergency department. We have active agents that represent individuals and passive agents that represent services and other reactive systems.…”

Section: Agent Modelmentioning

confidence: 99%

“…To get started, we make a metamodel of a FAM based on basic assumptions about what processes go on in and around the department with inspiration from the work by Taboada et al [10] about a conventional emergency department. We will revise this model based on data from interviews and observations from an actual FAM; for this purpose we have a collaboration agreement with the hospitals in the capital area of Denmark.…”

Section: Modeling a Fam In Aortamentioning

confidence: 99%

“…We will revise this model based on data from interviews and observations from an actual FAM; for this purpose we have a collaboration agreement with the hospitals in the capital area of Denmark. Based on the descriptions of a FAM in [2] and the scenario described in [10] we assume that the FAM scenario consists of the following stages:…”

Section: Modeling a Fam In Aortamentioning

confidence: 99%

“…Inspired by the approach for agent simulation of an emergency department by Taboada et al [10], we propose an approach in which we distinguish between three types of agents in the hospital organization: those are the active, the passive, and the external agents. For modeling the relationship between the agents we use AORTA, a logical framework for agent organizations developed by Jensen, Dignum and Villadsen [6].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An Approach for Hospital Planning with Multi-Agent Organizations

Larsen

Villadsen

2017

Rough Sets

View full text Add to dashboard Cite

Abstract. The background for this paper is a development that the Danish hospitals are undertaking which requires the establishment of a common emergency department. It is uncertain exactly what and how many resources the department needs and so resources are assigned dynamically as seen necessary by the staff. Such dynamic adjustments pose a challenge in predicting what consequences these adjustments may lead to. We propose an approach to deal with this challenge that applies simulation with intelligent agents and logics for organizational reasoning. We present some of the expected obstacles with this approach and potential ways to overcome them.

show abstract

Section: Agent Modelmentioning

confidence: 99%

Section: Modeling a Fam In Aortamentioning

confidence: 99%

Section: Modeling a Fam In Aortamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Approach for Hospital Planning with Multi-Agent Organizations

Larsen

Villadsen

2017

Rough Sets

View full text Add to dashboard Cite

show abstract

“…Cabrera et al (2012) uses exhaustive search optimization to find the optimal staff configuration. Taboada et al (2011) have studied the impact of staff experience (a senior member finishes its tasks faster than a junior member) over patient throughput and changes on the frequency of patient arrivals and staff levels. Zeltyn et al (2011) combine simulation and analytical formulae to solve staff scheduling problems.…”

Section: Related Workmentioning

confidence: 99%

REDSim: A spatial agent-based simulation for studying emergency departments

Centeno¹,

Martin²,

Sweeney³

2013

2013 Winter Simulations Conference (WSC)

View full text Add to dashboard Cite

Faced with a mismatch between demand and resources, Emergency Department (ED) administrators and staff need to gauge the impacts of staff decision processes in lieu of increasing resource levels. In this paper we present REDSim, a spatial agent-based simulation framework for studying emergency departments. REDSim focuses on quantifying the impacts of staff decision processes, such as patient selection, on the length of stay, waiting and boarding times, and other variables. We show REDSim's effectiveness by comparing four patient selection strategies: longest waiting, shortest distance, random, and highest acuity. REDSim showed that although patient length of stay is not significantly reduced (1.4%) the throughput increases 17% when providers select the closest instead of the highest acuity patient for the next task.

show abstract

Multi‐Criteria Approach Using Discrete Event Simulation to Balance Staff Workload and Reduce Patient Wait Time

2024

Connected Innovation and Technology X.0 1

View full text Add to dashboard Cite

An Agent-Based Decision Support System for Hospitals Emergency Departments

Cited by 67 publications

References 7 publications

An Approach for Hospital Planning with Multi-Agent Organizations

An Approach for Hospital Planning with Multi-Agent Organizations

REDSim: A spatial agent-based simulation for studying emergency departments

Multi‐Criteria Approach Using Discrete Event Simulation to Balance Staff Workload and Reduce Patient Wait Time

Contact Info

Product

Resources

About