A Simulation Decision Support System for the Healthcare Emergency Department Optimization

2021 ◽  
pp. 367-386
Author(s):  
Manel Saad Saoud ◽  
Abdelhak Boubetra ◽  
Safa Attia
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Healthcare Systems ◽  
Agent Based Modeling ◽  
Simulation Methods ◽  
Agent Based ◽  
Effectiveness Of Care ◽  
Systems Simulation ◽  
Simulation Systems

Agent-based modeling and simulation methods have demonstrated efficiency in modeling and analyzing the dynamics of the healthcare systems. Simulation has become a crucial tool that facilitates understanding these systems that involve different and heterogeneous components interacting in diverse and complex ways. However, during the dynamic evolutions of these societies, the agents involve a massive amount of data that contain non-explicit and unknown information. The analysis of these data to study and discover the hidden relationships and the emerging phenomena is a well-known difficulty in the simulation systems. The call for powerful tools such as the data mining techniques to support the simulations analysis is the best solution that can be used to tackle this issue. The aim of this chapter is to develop a decision support system based on the integration of simulation systems and knowledge extraction techniques, to design a decisive tool to help healthcare managers to improve the quality and the effectiveness of care provided to the emergency departments.

A Simulation Decision Support System for the Healthcare Emergency Department Optimization

2018 ◽  
pp. 347-367
Author(s):  
Manel Saad Saoud ◽  
Abdelhak Boubetra ◽  
Safa Attia
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Healthcare Systems ◽  
Agent Based Modeling ◽  
Simulation Methods ◽  
Agent Based ◽  
Effectiveness Of Care ◽  
Systems Simulation ◽  
Simulation Systems

Agent-based modeling and simulation methods have demonstrated efficiency in modeling and analyzing the dynamics of the healthcare systems. Simulation has become a crucial tool that facilitates understanding these systems that involve different and heterogeneous components interacting in diverse and complex ways. However, during the dynamic evolutions of these societies, the agents involve a massive amount of data that contain non-explicit and unknown information. The analysis of these data to study and discover the hidden relationships and the emerging phenomena is a well-known difficulty in the simulation systems. The call for powerful tools such as the data mining techniques to support the simulations analysis is the best solution that can be used to tackle this issue. The aim of this chapter is to develop a decision support system based on the integration of simulation systems and knowledge extraction techniques, to design a decisive tool to help healthcare managers to improve the quality and the effectiveness of care provided to the emergency departments.

A Simulation Knowledge Extraction-based Decision Support System for the Healthcare Emergency Department

2016 ◽  
Vol 11 (2) ◽  
pp. 19-37 ◽  
Author(s):  
Manel Saad Saoud ◽  
Abdelhak Boubetra ◽  
Safa Attia
Keyword(s):  
Emergency Department ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Performance Enhancement ◽  
Healthcare Systems ◽  
Knowledge Extraction ◽  
Agent Based ◽  
The Public ◽  
Critical Unit

Nowadays, healthcare systems services have become a serious concern for many countries across the world. Due to its complexity and Variability the Emergency Department (ED) is considered the most critical unit of the hospital and the healthcare systems in general. Increasing the patient satisfaction, reducing as much as possible the patient's waiting time and the patient's length of stay, and optimizing the resources utilization are the overriding preoccupation for any ED manager. To support the performance enhancement in the ED, simulation studies have profusely been involved. In this paper the authors describe a decision support system based on the combination of a simulation and a temporal knowledge extraction model for the operation improvement of the emergency department in the public hospital Lakhdar Bouzidi in Bordj Bou Arreridj (Algeria). Their methodology points out how agent-based modeling simulation can benefit from data mining analysis methods to provide a powerful decision support system that can help managers to improve the functioning of the ED.

A Simulation Knowledge Extraction-Based Decision Support System for the Healthcare Emergency Department

2020 ◽  
pp. 192-212
Author(s):  
Manel Saad Saoud ◽  
Abdelhak Boubetra ◽  
Safa Attia
Keyword(s):  
Emergency Department ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Performance Enhancement ◽  
Healthcare Systems ◽  
Knowledge Extraction ◽  
Agent Based ◽  
The Public ◽  
Critical Unit

Nowadays, healthcare systems services have become a serious concern for many countries across the world. Due to its complexity and Variability the Emergency Department (ED) is considered the most critical unit of the hospital and the healthcare systems in general. Increasing the patient satisfaction, reducing as much as possible the patient's waiting time and the patient's length of stay, and optimizing the resources utilization are the overriding preoccupation for any ED manager. To support the performance enhancement in the ED, simulation studies have profusely been involved. In this paper the authors describe a decision support system based on the combination of a simulation and a temporal knowledge extraction model for the operation improvement of the emergency department in the public hospital Lakhdar Bouzidi in Bordj Bou Arreridj (Algeria). Their methodology points out how agent-based modeling simulation can benefit from data mining analysis methods to provide a powerful decision support system that can help managers to improve the functioning of the ED.

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