Ontology for Overcrowding Management in ...
Document type :
Article dans une revue scientifique: Article original
DOI :
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Title :
Ontology for Overcrowding Management in Emergency Department.
Author(s) :
Fakhfakh Maala, Khouloud [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université Lille Nord (France)
Ben Othman, Sarah [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Jourdan, Laetitia [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Smith, Grégoire [Auteur]
Université Lille Nord (France)
Renard, Jean-Marie [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Université Lille Nord (France)
Hammadi, Slim [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Zgaya Biau, Hayfa [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université Lille Nord (France)
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université Lille Nord (France)
Ben Othman, Sarah [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Jourdan, Laetitia [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Smith, Grégoire [Auteur]
Université Lille Nord (France)
Renard, Jean-Marie [Auteur]

METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Université Lille Nord (France)
Hammadi, Slim [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Zgaya Biau, Hayfa [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université Lille Nord (France)
Journal title :
Studies in Health Technology and Informatics
Abbreviated title :
Stud Health Technol Inform
Volume number :
290
Pages :
947-951
Publication date :
2022-06-14
ISSN :
1879-8365
HAL domain(s) :
Sciences du Vivant [q-bio]
English abstract : [en]
Emergency department (ED) overcrowding is an ongoing problem worldwide. Scoring systems are available for the detection of this problem. This study aims to combine a model that allows the detection and management of ...
Show more >Emergency department (ED) overcrowding is an ongoing problem worldwide. Scoring systems are available for the detection of this problem. This study aims to combine a model that allows the detection and management of overcrowding. Therefore, it is crucial to implement a system that can reason model, rank ED resources and ED performance indicators based on environmental factors. Thus, we propose in this paper a new domain ontology (EDOMO) based on a new overcrowding estimation score (OES) to detect critical situations, specify the level of overcrowding and propose solutions to deal with these situations. Our approach is based on a real database created during more than four years from the Lille University Hospital Center (LUHC) in France. The resulting ontology is capable of modeling complete domain knowledge to enable semantic reasoning based on SWRL rules. The evaluation results show that the EDOMO is complete that can enhance the functioning of the ED.Show less >
Show more >Emergency department (ED) overcrowding is an ongoing problem worldwide. Scoring systems are available for the detection of this problem. This study aims to combine a model that allows the detection and management of overcrowding. Therefore, it is crucial to implement a system that can reason model, rank ED resources and ED performance indicators based on environmental factors. Thus, we propose in this paper a new domain ontology (EDOMO) based on a new overcrowding estimation score (OES) to detect critical situations, specify the level of overcrowding and propose solutions to deal with these situations. Our approach is based on a real database created during more than four years from the Lille University Hospital Center (LUHC) in France. The resulting ontology is capable of modeling complete domain knowledge to enable semantic reasoning based on SWRL rules. The evaluation results show that the EDOMO is complete that can enhance the functioning of the ED.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
CHU Lille
CHU Lille
Submission date :
2023-11-15T03:56:59Z
2024-01-15T15:05:48Z
2024-01-15T15:05:48Z
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