Transforming French Electronic Health Records into the Observational Medical Outcome Partnership's Common Data Model: A Feasibility Study

Author:

Lamer Antoine1,Depas Nicolas1,Doutreligne Matthieu2,Parrot Adrien34,Verloop David5,Defebvre Marguerite-Marie5,Ficheur Grégoire1,Chazard Emmanuel1,Beuscart Jean-Baptiste1

Affiliation:

1. Univ. Lille, CHU Lille, ULR 2694-METRICS: Évaluation des Technologies de Santé et des Pratiques Médicales, F-59000 Lille, France

2. Bureau Etat de Santé de la Population, Ministère des Affaires Sociales et de la Santé, Direction de la Recherche, des Etudes et des Statistiques - Observation de la Santé et de l'Assurance Maladie, Paris, France

3. Université Paris Descartes, Paris, France

4. Web INnovation Données-Direction des Systèmes d’Information, Assistance Publique - Hôpitaux de Paris, Paris, France

5. Service Etudes et Statistiques, ARS Hauts-de-France, Lille, France

Abstract

Abstract Background Common data models (CDMs) enable data to be standardized, and facilitate data exchange, sharing, and storage, particularly when the data have been collected via distinct, heterogeneous systems. Moreover, CDMs provide tools for data quality assessment, integration into models, visualization, and analysis. The observational medical outcome partnership (OMOP) provides a CDM for organizing and standardizing databases. Common data models not only facilitate data integration but also (and especially for the OMOP model) extends the range of available statistical analyses. Objective This study aimed to evaluate the feasibility of implementing French national electronic health records in the OMOP CDM. Methods The OMOP's specifications were used to audit the source data, specify the transformation into the OMOP CDM, implement an extract–transform–load process to feed data from the French health care system into the OMOP CDM, and evaluate the final database. Results Seventeen vocabularies corresponding to the French context were added to the OMOP CDM's concepts. Three French terminologies were automatically mapped to standardized vocabularies. We loaded nine tables from the OMOP CDM's “standardized clinical data” section, and three tables from the “standardized health system data” section. Outpatient and inpatient data from 38,730 individuals were integrated. The median (interquartile range) number of outpatient and inpatient stays per patient was 160 (19–364). Conclusion Our results demonstrated that data from the French national health care system can be integrated into the OMOP CDM. One of the main challenges was the use of international OMOP concepts to annotate data recorded in a French context. The use of local terminologies was an obstacle to conceptual mapping; with the exception of an adaptation of the International Classification of Diseases 10th Revision, the French health care system does not use international terminologies. It would be interesting to extend our present findings to the 65 million people registered in the French health care system.

Funder

Agence Régionale de Santé (ARS) Hauts-de-France

Publisher

Georg Thieme Verlag KG

Subject

Health Information Management,Computer Science Applications,Health Informatics

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