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Design of an ontology-based triage system for painful patients

Authors :
Saadi, Alexandre
Rogier, Alice
Burgun, Anita
Tsopra, Rosy
Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138))
École Pratique des Hautes Études (EPHE)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)
Health data- and model- driven Knowledge Acquisition (HeKA)
Inria de Paris
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138))
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)-École Pratique des Hautes Études (EPHE)
Hôpital Européen Georges Pompidou [APHP] (HEGP)
Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)
École pratique des hautes études (EPHE)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)-École pratique des hautes études (EPHE)
SAADI, Alexandre
Source :
MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation, MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation, 290, IOS Press; IOS Press, pp.81-85, 2022, Studies in Health Technology and Informatics, ⟨10.3233/SHTI220036⟩
Publication Year :
2022
Publisher :
HAL CCSD, 2022.

Abstract

International audience; Objective: Waiting time for a consultation for chronic pain is a widespread health problem. This paper present the design of an ontology use to assess patients referred to a consultation for chronic pain. Methods: We designed OntoDol, an ontology of pain domain for patient triage based on priority degrees. Terms were extracted from clinical practice guidelines and mapped to SNOMED-CT concepts through the Python module Owlready2. Selected SNOMED-CT concepts, relationships, and the TIME ontology, were implemented in the ontology using Protégé. Decision rules were implemented with SWRL. We evaluated OntoDol on 5 virtual cases. Results: OntoDol contains 762 classes, 92 object properties and 18 SWRL rules to assign patients to 4 categories of priority. OntoDol was able to assert every case and classify them in the right category of priority. Conclusion: Further works will extend OntoDol to other diseases and assess OntoDol with real world data from the hospital.

Details

Language :
English
Database :
OpenAIRE
Journal :
MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation, MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation, 290, IOS Press; IOS Press, pp.81-85, 2022, Studies in Health Technology and Informatics, ⟨10.3233/SHTI220036⟩
Accession number :
edsair.dedup.wf.001..de540886a090a914c027d64fec0a5141