Treffer: Design of an ontology-based triage system for painful patients

Title:
Design of an ontology-based triage system for painful patients
Authors:
Saadi, Alexandre, Rogier, Alice, Burgun, Anita, Tsopra, Rosy
Contributors:
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), Centre 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)
Source:
MEDINFO 2021: One World. :81-85
Publisher Information:
CCSD; IOS Press, 2022.
Publication Year:
2022
Collection:
collection:INSERM
collection:EPHE
collection:INRIA
collection:INRIA-ROCQ
collection:APHP
collection:SANTE_PUB_INSERM
collection:LORIA2
collection:TESTALAIN1
collection:CORDELIERS
collection:INRIA2
collection:TDS-MACS
collection:PSL
collection:INRIA-PSL
collection:CHU-UNIV-PARIS5
collection:SORBONNE-UNIVERSITE
collection:SORBONNE-UNIV
collection:SU-SCIENCES
collection:TEST-DEV
collection:UNIV-PARIS
collection:UNIVERSITE-PARIS
collection:UP-SANTE
collection:EPHE-PSL
collection:SU-TI
collection:ALLIANCE-SU
collection:SUPRA_BIOLOGIE
Subject Terms:
Clinical Decision Support System, Chronic pain, Ontology, MESH: Chronic Pain, MESH: Humans, MESH: Referral and Consultation, MESH: Systematized Nomenclature of Medicine, MESH: Triage, [SDV.SPEE]Life Sciences [q-bio], Santé publique et épidémiologie, [INFO.INFO-DS]Computer Science [cs], Data Structures and Algorithms [cs.DS], [INFO.INFO-MO]Computer Science [cs], Modeling and Simulation, [SDV.MHEP.PHY]Life Sciences [q-bio], Human health and pathology, Tissues and Organs [q-bio.TO]
Original Identifier:
PUBMED: 35672975
HAL: hal-03694355
Document Type:
Buch bookPart<br />Book sections
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.3233/SHTI220036; info:eu-repo/semantics/altIdentifier/pmid/35672975
DOI:
10.3233/SHTI220036
Access URL:
https://hal.sorbonne-universite.fr/hal-03694355
https://hal.sorbonne-universite.fr/hal-03694355v1/document
https://hal.sorbonne-universite.fr/hal-03694355v1/file/209_SAADI_A_Medinfo2021_Final_Review1.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.03694355v1
Database:
HAL

Weitere Informationen

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.