Fuzzy Ontology for Patient Emergency Department Triage

EasyChair Preprint 5893

Abstract

Triage in emergency department (ED) is adopted procedure in several countries using different emergency severity index systems. The objective is to subdivide patients into categories of increasing acuity to allow for prioritization and re-duce emergency department congestion. However, while several studies have focused on improving the triage system and managing medical resources, the classification of patients depends strongly on nurse's subjective judgment and thus is prone to human errors. So, it is crucial to set up a system able to model, classify and reason about vague, incomplete and uncertain knowledge. Thus, we propose in this paper a novel fuzzy ontology based on a new Fuzzy Emergency Severity Index (F-ESI_2.0) to improve the accuracy of current triage systems. Therefore, we model some fuzzy relevant medical subdomains that influence the patient's condition. Our approach is based on continuous structured and un-structured textual data over more than two years collected during patient visits to the ED of the Lille University Hospital Center (LUHC) in France. The result-ing fuzzy ontology is able to model uncertain knowledge and organize the pa-tient's passage to the ED by treating the most serious patients first. Evaluation results shows that the resulting fuzzy ontology is a complete domain ontology which can improve current triage system failures.

Keyphrases: fuzzy ontology, medical ontology, patient triage, uncertainty

@booklet{EasyChair:5893,
  author    = {Khouloud Fakhfakh and Sarah Ben Othman and Laetitia Jourdan and Grégoire Smith and Jean Marie Renard and Slim Hammadi and Hayfa Zgaya-Biau},
  title     = {Fuzzy Ontology for Patient Emergency Department Triage},
  howpublished = {EasyChair Preprint 5893},
  year      = {EasyChair, 2021}}