eSource for clinical trials: Implementation and evaluation of a standards-based approach in a real world trial

Jean Francois Ethier, Vasa Curcin, Mark M. McGilchrist, Sarah N.Lim Choi Keung, Lei Zhao, Anna Andreasson, Piotr Bródka, Radoslaw Michalski, Theodoros N. Arvanitis, Nikolaos Mastellos, Anita Burgun, Brendan C. Delaney (Lead / Corresponding author)

    Research output: Contribution to journalArticlepeer-review

    15 Citations (Scopus)
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    Objective: 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.

    Materials and Methods: 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.

    Results: 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.

    Discussion: 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.

    Conclusion: 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.

    Original languageEnglish
    Pages (from-to)17-24
    Number of pages8
    JournalInternational Journal of Medical Informatics
    Early online date29 Jun 2017
    Publication statusPublished - 1 Oct 2017


    • Clinical trial
    • Electronic health records
    • Interoperability
    • Learning health system
    • Operational data model


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