Use of a modular ontology and a semantic annotation tool to describe the care pathway of patients with amyotrophic lateral sclerosis in a coordination network.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2021
Historique:
received: 03 07 2020
accepted: 11 12 2020
entrez: 6 1 2021
pubmed: 7 1 2021
medline: 4 5 2021
Statut: epublish

Résumé

The objective of this study was to describe the care pathway of patients with amyotrophic lateral sclerosis (ALS) based on real-life textual data from a regional coordination network, the Ile-de-France ALS network. This coordination network provides care for 92% of patients diagnosed with ALS living in Ile-de-France. We developed a modular ontology (OntoPaRON) for the automatic processing of these unstructured textual data. OntoPaRON has different modules: the core, medical, socio-environmental, coordination, and consolidation modules. Our approach was unique in its creation of fully defined concepts at different levels of the modular ontology to address specific topics relating to healthcare trajectories. We also created a semantic annotation tool specific to the French language and the specificities of our corpus, the Ontology-Based Semantic Annotation Module (OnBaSAM), using the OntoPaRON ontology as a reference. We used these tools to annotate the records of 928 patients automatically. The semantic (qualitative) annotations of the concepts were transformed into quantitative data. By using these pipelines we were able to transform unstructured textual data into structured quantitative data. Based on data processing, semantic annotations, sociodemographic data for the patient and clinical variables, we found that the need and demand for human and technical assistance depend on the initial form of the disease, the motor state, and the patient age. The presence of exhaustion in care management, is related to the patient's motor and cognitive state.

Identifiants

pubmed: 33406098
doi: 10.1371/journal.pone.0244604
pii: PONE-D-20-20582
pmc: PMC7787442
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0244604

Déclaration de conflit d'intérêts

Xavier Aimé works in the company Cogsonomy that he created. This commercial affiliation (Cogsonomy) does not alter our (all the authors) adherence to PLOS ONE policies on sharing data and materials.

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Auteurs

Sonia Cardoso (S)

Laboratoire d'Informatique Médicale et d'IngéInierie des Connaissances en e-Santé UMR-1142, Sorbonne Université, INSERM, Université Paris 13, Paris, France.

Pierre Meneton (P)

Laboratoire d'Informatique Médicale et d'IngéInierie des Connaissances en e-Santé UMR-1142, Sorbonne Université, INSERM, Université Paris 13, Paris, France.

Xavier Aimé (X)

Laboratoire d'Informatique Médicale et d'IngéInierie des Connaissances en e-Santé UMR-1142, Sorbonne Université, INSERM, Université Paris 13, Paris, France.
Cogsonomy, Nantes, France.

Vincent Meininger (V)

Ramsay General de Santé, Hôpital Peupliers, Paris, France.

David Grabli (D)

Département des maladies du Système Nerveux, Assistance Publique-Hôpitaux de Paris Pitié Salpêtrière, Paris, France.

Gilles Guezennec (G)

Laboratoire d'Informatique Médicale et d'IngéInierie des Connaissances en e-Santé UMR-1142, Sorbonne Université, INSERM, Université Paris 13, Paris, France.

Jean Charlet (J)

Laboratoire d'Informatique Médicale et d'IngéInierie des Connaissances en e-Santé UMR-1142, Sorbonne Université, INSERM, Université Paris 13, Paris, France.
Département de la Recherche Clinique et de l'Innovation, Assistance Publique-Hôpitaux de Paris, Paris, France.

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