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Méthodes d’ordonnancement et d’orchestration dynamique des tâches de soins pour optimiser la prise en charge des patients dans les urgences hospitalières

Abstract : The emergency department is an important care service that represents the hospital's bottleneck. Emergencies often face overcrowding problems in many countries worldwide. One of the causes of the emergency department overcrowding is the permanent interference between three types of arriving patients: already programmed patients, non-programmed patients and urgent non-programmed patients. The aim of this thesis is to contribute to the study and development a decision support system to improve patient management in both normal and overcrowding situation. Two main processes have been developed. A rolling-horizon scheduling process using a memetic algorithm with the integration of controlled genetic operators to determine an optimal schedule for patient. The second dynamic orchestration process, based on communicating agents, takes into account the dynamic and uncertain nature of the emergency environment by continually updating this schedule for patient. This orchestration monitoring in real time the workflow of the patient pathway improves step by step the performance indicators during the execution. Through agent behaviors and communication protocols, the proposed system has established a direct real-time link between the required performances and the effective actions in order to decrease the overcrowding impact. The experimental results in this thesis, implemented at the Regional University Hospital Center (RUHC) of Lille, justify the interest of the application of our approaches to improve the performance indicators thanks to the agents driven patient pathway workflows during their execution.
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Submitted on : Wednesday, December 4, 2019 - 11:14:09 AM
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Faten Ajmi. Méthodes d’ordonnancement et d’orchestration dynamique des tâches de soins pour optimiser la prise en charge des patients dans les urgences hospitalières. Automatique / Robotique. Ecole Centrale de Lille, 2019. Français. ⟨NNT : 2019ECLI0009⟩. ⟨tel-02393018⟩

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