Jean-Francois Ethier1, Vasa Curcin2, Mark M McGilchrist3, Sarah N Lim Choi Keung4, Lei Zhao5, Anna Andreasson6, Piotr Bródka7, Radoslaw Michalski8, Theodoros N Arvanitis9, Nikolaos Mastellos10, Anita Burgun11, Brendan C Delaney12. 1. INSERM 1138, eq 22 Université Paris-Descartes, Paris, France. Electronic address: ethierj@gmail.com. 2. Department of Informatics, King's College London, London, United Kingdom. Electronic address: vasa.curcin@kcl.ac.uk. 3. Public Health Sciences, University of Dundee, Dundee, United Kingdom. Electronic address: m.m.mcgilchrist@dundee.ac.uk. 4. Institute of Digital Healthcare, WMG, University of Warwick, Coventry, United Kingdom. Electronic address: S.N.Lim-Choi-Keung@warwick.ac.uk. 5. Institute of Digital Healthcare, WMG, University of Warwick, Coventry, United Kingdom. Electronic address: Lei.Zhao@warwick.ac.uk. 6. Division of Family Medicine and Primary Care, Karolinska Institute Stockholm, Sweden. Electronic address: Anna.Andreasson@ki.se. 7. Department of Computational Intelligence, Wroclaw Institute of Science and Technology, Wroclaw, Poland. Electronic address: piotr.brodka@pwr.edu.pl. 8. Department of Computational Intelligence, Wroclaw Institute of Science and Technology, Wroclaw, Poland. Electronic address: radoslaw.michalski@pwr.edu.pl. 9. Institute of Digital Healthcare, WMG, University of Warwick, Coventry, United Kingdom. Electronic address: T.Arvanitis@warwick.ac.uk. 10. Department of Primary Care and Public Health, Imperial College London, London, United Kingdom. Electronic address: n.mastellos@imperial.ac.uk. 11. INSERM 1138, eq 22 Université Paris-Descartes, Paris, France. Electronic address: anita.burgun@aphp.fr. 12. Institute of Global Health Innovation, Department of Surgery and Cancer Imperial College London, London, United Kingdom. Electronic address: brendan.delaney@imperial.ac.uk.
Abstract
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.
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.
Authors: Maryam Y Garza; Michael Rutherford; Sahiti Myneni; Susan Fenton; Anita Walden; Umit Topaloglu; Eric Eisenstein; Karan R Kumar; Kanecia O Zimmerman; Mitra Rocca; Gideon Scott Gordon; Sam Hume; Zhan Wang; Meredith Zozus Journal: AMIA Annu Symp Proc Date: 2021-01-25
Authors: Carmen Rosa; Lisa A Marsch; Erin L Winstanley; Meg Brunner; Aimee N C Campbell Journal: Contemp Clin Trials Date: 2020-11-17 Impact factor: 2.226