Sharing health big data for research - A design by use cases: the INSHARE platform approach

Guillaume Bouzillé (1) , Richard Westerlynck (2) , Gautier Defossez (3) , Dalel Bouslimi (4, 5) , Sahar Bayat (6, 7, 8, 9) , Christine Riou (10, 1) , Yann Busnel (11, 2) , Clara Le Guillou (12) , Jean-Michel Cauvin (4) , Christian Jacquelinet (13) , Patrick Pladys (1) , Emmanuel Oger (10, 14) , Eric Stindel (4) , Pierre Ingrand (15) , Gouenou Coatrieux (4, 5) , Marc Cuggia (1)

1 LTSI - Laboratoire Traitement du Signal et de l'Image
2 IMT Atlantique - SRCD - Département Systèmes Réseaux, Cybersécurité et Droit du numérique
3 Unité d'épidémiologie, biostatistique et registre général des cancers de Poitou-Charentes
4 LaTIM - Laboratoire de Traitement de l'Information Medicale
5 ITI - Département Image et Traitement Information
6 LIM - Laboratoire d'Informatique Médicale
7 EHESP - École des Hautes Études en Santé Publique [EHESP]
8 METIS - Département Méthodes quantitatives en santé publique
9 REPERES - Recherche en Pharmaco-épidémiologie et Recours aux Soins
10 CIC - Centre d'Investigation Clinique [Rennes]
11 DIONYSOS - Dependability Interoperability and perfOrmance aNalYsiS Of networkS
12 UMET - Unité Matériaux et Transformations - UMR 8207
13 DGMS - Direction générale en charge de la politique médicale et scientifique [
14 Service de Pharmacologie [Rennes]
15 CIC 1402 - CIC Poitiers – Centre d'investigation clinique de Poitiers

Sharing and exploiting efficiently Health Big Data (HBD) lead to tackle great challenges: data protection and governance taking into account legal, ethical and deontological aspects which enables a trust, transparent and win-to-win relationship between researchers, citizen and data providers. Lack of interoperability: data are compartmentalized and are so syntactically and semantically heterogeneous. Variable data quality with a great impact on data management and statistical analysis. The objective of the INSHARE project is to explore, through an experimental proof of concept, how recent technologies could overcome such issues. It aims at demonstrating the feasibility and the added value of an IT platform based on CDW, dedicated to collaborative HBD sharing for medical research. METHOD: The consortium includes 6 data providers: 2 academic hospitals, the SNIIRAM (the French national reimbursement database) and 3 national or regional registries. The platform is designed following a 3 steps approach: (1) to analyze use cases, needs and requirements (2). To define data sharing governance and secure access to the platform, (3) To define the platform specifications. RESULT: 3 use cases (healthcare trajectory analysis, epidemiologic registry enrichment, signal detection) were analyzed to design the platform. corresponding to 5 studies and using 11 data sources. The governance was derived from the SCANNER model and adapted to data sharing. As a result, the platform architecture integrates the following tools and services: Data repository and hosting, semantic integration services, data processing, aggregate computing, data quality and integrity monitoring, Id linking, Multisource query builder, Visualization and data export services, data governance, study management service and security including data watermarking..

Mots clés: Information Storage and Retrieval; Data sharing; Registries/statistics & numerical data

Domaines: Ingénierie biomédicale

Guillaume Bouzillé, Richard Westerlynck, Gautier Defossez, Dalel Bouslimi, Sahar Bayat, et al.. Sharing health big data for research - A design by use cases: the INSHARE platform approach. MEDINFO 2017 : 16th World Congress on Medical and Health Informatics, Aug 2017, Hangzhou, China. ⟨10.3233/978-1-61499-830-3-303⟩. ⟨hal-01535703⟩