| Autor: |
Maala, Khouloud Fakhfakh, Ben-Othman, Sarah, Jourdan, Laetitia, Smith, Grégoire, Renard, Jean-Marie, Hammadi, Slim, Biau, Hayfa Zgaya |
| Předmět: |
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| Zdroj: |
Medinfo; 2021, Vol. 290, p947-951, 5p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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