Real time patient scheduling orchestration for improving key performance indicators in a hospital emergency department

Faiza Ajmi (), Faten Ajmi (), Sarah Ben Othman, Hayfa Zgaya-Biau, Mariagrazia Dotoli, Jean-Marie Renard () and Slim Hammadi ()
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Faiza Ajmi: CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique, UCL FGES - Université Catholique de Lille - Faculté de gestion, économie et sciences - ICL - Institut Catholique de Lille - UCL - Université catholique de Lille, LITL - Laboratoire Interdisciplinaire des transitions de Lille - UCL FGES - Université Catholique de Lille - Faculté de gestion, économie et sciences - ICL - Institut Catholique de Lille - UCL - Université catholique de Lille - JUNIA - JUNIA - UCL - Université catholique de Lille
Faten Ajmi: CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Sarah Ben Othman: CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Hayfa Zgaya-Biau: CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Mariagrazia Dotoli: Polytechnic University of Bari / Politecnico di Bari
Jean-Marie Renard: CERIM - Centre d'Etudes et de Recherche en Informatique Médicale [Lille]
Slim Hammadi: CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique

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Abstract: Healthcare systems worldwide are increasingly subject to in-depth analysis. Problems in healthcare systems are of concern to the general public. For example, overcrowding in emergency departments creates several issues including longer waiting times, more frequent medical errors, a longer length of stay and worsened performance indicators. Overcrowding situations reduce the availability of staff and material resources, and therefore deteriorate the quality of care. The main cause of the overcrowding in emergency departments is the permanent interferences between the scheduled patients, unscheduled patients and urgent and unscheduled patients arriving at the emergency department. The objective of the present study is to develop an innovative decision support system that minimizes these interferences, while taking into account the perturbations that can occur throughout the day. The research's ultimate goal is to improve the performance indicators via two processes: the first is a memetic algorithm based on a four dimensional hypercube genetic algorithm and local search techniques, and the second is based on a multi-agent system which dynamically orchestrates the patient pathway (given by the scheduling algorithm). In order to test and validate our approach, experiments are designed with real data from the adult emergency department at Lille University Medical Center. Simulations showed that with our approach we were able to reduce the waiting time of patients by 28.12%.

Keywords: Emergency department; dynamic scheduling; memetic algorithm; multi-agent system; orchestration; four dimensional hypercube algorithm. (search for similar items in EconPapers)
Date: 2024
Note: View the original document on HAL open archive server: https://hal.science/hal-05210456v1
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Published in Journal of computational science, 2024, 82, pp.102422. ⟨10.1016/j.jocs.2024.102422⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05210456

DOI: 10.1016/j.jocs.2024.102422

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