TY - JOUR
T1 - eSource for clinical trials
T2 - Implementation and evaluation of a standards-based approach in a real world trial
AU - Ethier, Jean Francois
AU - Curcin, Vasa
AU - McGilchrist, Mark M.
AU - Choi Keung, Sarah N.Lim
AU - Zhao, Lei
AU - Andreasson, Anna
AU - Bródka, Piotr
AU - Michalski, Radoslaw
AU - Arvanitis, Theodoros N.
AU - Mastellos, Nikolaos
AU - Burgun, Anita
AU - Delaney, Brendan C.
N1 - This work was supported in part by the European Commission—DG INFSO (FP7 247787) and partially supported by the European Commission under the 7th Framework Programme, Coordination and Support Action, Grant Agreement Number 316097, ENGINE - European research centre of Network intelliGence for INnovation Enhancement (http://engine.pwr.edu.pl/). The RENOIR project - Reverse EngiNeering of sOcial Information pRocessing - leading to this publication has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 691152.
PY - 2017/10/1
Y1 - 2017/10/1
N2 - 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.
AB - 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.
KW - Clinical trial
KW - Electronic health records
KW - Interoperability
KW - Learning health system
KW - Operational data model
U2 - 10.1016/j.ijmedinf.2017.06.006
DO - 10.1016/j.ijmedinf.2017.06.006
M3 - Article
C2 - 28870379
AN - SCOPUS:85024473685
SN - 1386-5056
VL - 106
SP - 17
EP - 24
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
ER -