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

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 Multi-Agent Based Modeling and Simulation Data Management and Analysis System for the Hospital Emergency Department

In the last decades, multi-agent based modeling and simulation systems have become more increasingly used to model the dynamic and the complex healthcare systems which contain many variabilities and uncertainties such as the hospital emergency departments (ED). Modeling and creating virtual societies almost identical and similar to the reality are considered as the strongest advantages of these agents systems. However, during the dynamic development of the artificial societies, a massive volume of data, which generally contains non-express and shrouded information and even knowledge, is involved. Therefore, dealing with this data, to study and to analyze the unclear relationships and the emerging phenomena, is a well-known weakness and bottleneck that the multi-agent systems is suffering from. In conjunction, data mining techniques are the most powerful tools that can help simulation experts to tackle this issue. This paper presents an ongoing research that combines the multi-agent based modeling and simulation systems and data mining techniques to develop a decision support system to improve the operation of the emergency department.

Development of an Emergency Response Management using Mobile Devices for Hospital Infrastructures Affected by Power Grid Failures

In the case of a partial or general power blackout in a hospital infrastructure, the most important issue becomes how to secure at maximum the patients' lives, especially those who are depending on electrical systems. In this paper, a novel web mobile-based evacuation support system has been developed. The proposed solution is consolidated by the improvement of several parameters such as communication quality, prioritization, staffing management and coordination. To evaluate the performance of the proposed solution, real tests were conducted in a hospital. The results showed that the proposed evacuation support system, compared to the classical solutions, is more efficient in terms of the actions execution time reduction and the information quality improvement.