Automated Generation of Individual and ...
Type de document :
Article dans une revue scientifique: Article original
DOI :
PMID :
URL permanente :
Titre :
Automated Generation of Individual and Population Clinical Pathways with the OMOP Common Data Model
Auteur(s) :
Boudis, F. [Auteur]
Clement, G. [Auteur]
Bruandet, Amelie [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Lamer, Antoine [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Clement, G. [Auteur]
Bruandet, Amelie [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Lamer, Antoine [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Titre de la revue :
Studies in Health Technology and Informatics
Nom court de la revue :
Stud Health Technol Inform
Numéro :
281
Pagination :
p. 218-222
Date de publication :
2021
ISSN :
1879-8365
Discipline(s) HAL :
Sciences du Vivant [q-bio]
Résumé en anglais : [en]
Introduction. Clinical pathways represents the sequence of interventions
from which the patients benefit during their encounters with health care structures.
There are several complex issues which make it difficult to ...
Lire la suite >Introduction. Clinical pathways represents the sequence of interventions from which the patients benefit during their encounters with health care structures. There are several complex issues which make it difficult to represent these pathways (e.g. high numbers of patients, heterogeneity of variables). Methods. We developed a tool to automate the representation of clinical pathways, from an individual and population points of view, and based on the OMOP CDM. The tool implemented the Sankey diagram in three stages: (i) data extraction, (ii) generation of individual sequence of steps and (iii) aggregation of sequence to obtain the population-level diagram. We tested the tool with three surgery procedures : the total hip replacement, the coronary bypass and the transcatheter aortic valve implantation. Results. The tool provided different ways of visualizing pathways depending on the question asked: a pathway before a surgery, the pathway of deceased patients or the complete pathway with different steps of interest. Discussion. We proposed a tool automating the representation of the clinical pathways, and reducing complexity of visualization. Representations are detailed from an individual and population points of view. It has been tested with three surgical procedures. The tool functionalities will be extended to cover a greater number of use cases.Lire moins >
Lire la suite >Introduction. Clinical pathways represents the sequence of interventions from which the patients benefit during their encounters with health care structures. There are several complex issues which make it difficult to represent these pathways (e.g. high numbers of patients, heterogeneity of variables). Methods. We developed a tool to automate the representation of clinical pathways, from an individual and population points of view, and based on the OMOP CDM. The tool implemented the Sankey diagram in three stages: (i) data extraction, (ii) generation of individual sequence of steps and (iii) aggregation of sequence to obtain the population-level diagram. We tested the tool with three surgery procedures : the total hip replacement, the coronary bypass and the transcatheter aortic valve implantation. Results. The tool provided different ways of visualizing pathways depending on the question asked: a pathway before a surgery, the pathway of deceased patients or the complete pathway with different steps of interest. Discussion. We proposed a tool automating the representation of the clinical pathways, and reducing complexity of visualization. Representations are detailed from an individual and population points of view. It has been tested with three surgical procedures. The tool functionalities will be extended to cover a greater number of use cases.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
CHU Lille
CHU Lille
Date de dépôt :
2023-11-15T06:32:22Z
2023-12-20T10:37:38Z
2023-12-20T10:37:38Z
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