ORCID Profile
0000-0001-9408-0109
Current Organisations
Université de Sherbrooke
,
INSERM
,
Centre de recherche sur le vieillissement
,
Centre Hospitalier Universitaire de Sherbrooke
,
Centre interdisciplinaire de recherche en informatique de la santé de l'Université de Sherbrooke (CIRIUS)
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Publisher: Elsevier BV
Date: 10-2017
DOI: 10.1016/J.IJMEDINF.2017.06.006
Abstract: The Learning Health System (LHS) requires integration of research into routine practice. 'eSource' or embedding clinical trial functionalities into routine electronic health record (EHR) systems has long been put forward as a solution to the rising costs of research. We aimed to create and validate an eSource solution that would be readily extensible as part of a LHS. The EU FP7 TRANSFoRm project's approach is based on dual modelling, using the Clinical Research Information Model (CRIM) and the Clinical Data Integration Model of meaning (CDIM) to bridge the gap between clinical and research data structures, using the CDISC Operational Data Model (ODM) standard. Validation against GCP requirements was conducted in a clinical site, and a cluster randomised evaluation by site nested into a live clinical trial. Using the form definition element of ODM, we linked precisely modelled data queries to data elements, constrained against CDIM concepts, to enable automated patient identification for specific protocols and pre-population of electronic case report forms (e-CRF). Both control and eSource sites recruited better than expected with no significant difference. Completeness of clinical forms was significantly improved by eSource, but Patient Related Outcome Measures (PROMs) were less well completed on smartphones than paper in this population. The TRANSFoRm approach provides an ontologically-based approach to eSource in a low-resource, heterogeneous, highly distributed environment, that allows precise prospective mapping of data elements in the EHR. Further studies using this approach to CDISC should optimise the delivery of PROMS, whilst building a sustainable infrastructure for eSource with research networks, trials units and EHR vendors.
Publisher: Hindawi Limited
Date: 2015
DOI: 10.1155/2015/961526
Abstract: The Learning Health System (LHS) describes linking routine healthcare systems directly with both research translation and knowledge translation as an extension of the evidence-based medicine paradigm, taking advantage of the ubiquitous use of electronic health record (EHR) systems. TRANSFoRm is an EU FP7 project that seeks to develop an infrastructure for the LHS in European primary care. Methods . The project is based on three clinical use cases, a genotype-phenotype study in diabetes, a randomised controlled trial with gastroesophageal reflux disease, and a diagnostic decision support system for chest pain, abdominal pain, and shortness of breath. Results . Four models were developed (clinical research, clinical data, provenance, and diagnosis) that form the basis of the projects approach to interoperability. These models are maintained as ontologies with binding of terms to define precise data elements. CDISC ODM and SDM standards are extended using an archetype approach to enable a two-level model of in idual data elements, representing both research content and clinical content. Separate configurations of the TRANSFoRm tools serve each use case. Conclusions. The project has been successful in using ontologies and archetypes to develop a highly flexible solution to the problem of heterogeneity of data sources presented by the LHS.
Publisher: IEEE
Date: 2015
Publisher: Georg Thieme Verlag KG
Date: 2015
DOI: 10.3414/ME13-02-0024
Abstract: Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Managing Interoperability and Complexity in Health Systems”. Background: Primary care data is the single richest source of routine health care data. However its use, both in research and clinical work, often requires data from multiple clinical sites, clinical trials databases and registries. Data integration and interoperability are therefore of utmost importance. Objectives: TRANSFoRm’s general approach relies on a unified interoperability framework, described in a previous paper. We developed a core ontology for an interoperability framework based on data mediation. This article presents how such an ontology, the Clinical Data Integration Model (CDIM), can be designed to support, in conjunction with appropriate terminologies, biomedical data federation within TRANSFoRm, an EU FP7 project that aims to develop the digital infrastructure for a learning healthcare system in European Primary Care. Methods: TRANSFoRm utilizes a unified structural / terminological interoperability frame work, based on the local-as-view mediation paradigm. Such an approach mandates the global information model to describe the domain of interest independently of the data sources to be explored. Following a requirement analysis process, no ontology focusing on primary care research was identified and, thus we designed a realist ontology based on Basic Formal Ontology to support our framework in collaboration with various terminologies used in primary care. Results: The resulting ontology has 549 classes and 82 object properties and is used to support data integration for TRANSFoRm’s use cases. Concepts identified by researchers were successfully expressed in queries using CDIM and pertinent terminologies. As an ex le, we illustrate how, in TRANSFoRm, the Query Formulation Workbench can capture eligibility criteria in a computable representation, which is based on CDIM. Conclusion: A unified mediation approach to semantic interoperability provides a flexible and extensible framework for all types of interaction between health record systems and research systems. CDIM, as core ontology of such an approach, enables simplicity and consistency of design across the heterogeneous software landscape and can support the specific needs of EHR-driven phenotyping research using primary care data.
Location: Canada
No related grants have been discovered for Jean-François Ethier.