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

Sonia Cardoso; Pierre Meneton; Xavier Aimé; Vincent Meininger; David Grabli; Gilles Guezennec; Jean Charlet

doi:10.1371/journal.pone.0244604

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

PLoS One. 2021 Jan 6;16(1):e0244604. doi: 10.1371/journal.pone.0244604. eCollection 2021.

Authors

Sonia Cardoso¹, Pierre Meneton¹, Xavier Aimé^{1

2}, Vincent Meininger³, David Grabli⁴, Gilles Guezennec¹, Jean Charlet^{1

5}

Affiliations

¹ Laboratoire d'Informatique Médicale et d'IngéInierie des Connaissances en e-Santé UMR-1142, Sorbonne Université, INSERM, Université Paris 13, Paris, France.
² Cogsonomy, Nantes, France.
³ Ramsay General de Santé, Hôpital Peupliers, Paris, France.
⁴ Département des maladies du Système Nerveux, Assistance Publique-Hôpitaux de Paris Pitié Salpêtrière, Paris, France.
⁵ Département de la Recherche Clinique et de l'Innovation, Assistance Publique-Hôpitaux de Paris, Paris, France.

Abstract

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.

Publication types

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

MeSH terms

Amyotrophic Lateral Sclerosis / therapy*
Delivery of Health Care*
France
Humans
Language
Natural Language Processing*

Grants and funding

Xavier Aimé works in the company Cogsonomy that he created: This company’s sole role is to finance training and other project management assistance for Xavier Aimé. Cogsonomy did not play a role in the study design, data collection and analysis, decision to publish, preparation of the manuscript and only provided financial support in the form of authors’ salaries and/or research materials. The funders (universities, hospitals) provided support in the form of salaries for authors [SC, PM, VM, DG, GG, JC], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.