journal article·2022-02-02Open access

How Can a Clinical Data Modelling Tool Be Used to Represent Data Items of Relevance to Paediatric Clinical Trials? Learning from the Conect4children (c4c) Consortium

Chima Amadi, Rebecca Leary, Avril Palmeri, Victoria Hedley, Anando Sen, Rahil Qamar Siddiqui, Dipak Kalra, Volker Straub

Applied Sciences· Volume 12· Issue 3

Abstract

Data dictionaries for clinical trials are often created manually, with data structures and controlled vocabularies specific for a trial or family of trials within a sponsor’s portfolio. Microsoft Excel is commonly used to capture the representation of data dictionary items but has limited functionality for this purpose. The conect4children (c4c) network is piloting the Direcht clinical data modelling tool to model their Cross Cutting Paediatric Data Dictionary (CCPDD) in a more formalised way. The first pilot had the key objective of testing whether a clinical data modelling tool could be used to represent data items from the CCPDD. The key objective of the second pilot is to establish whether a small team with little or no experience of clinical data modelling can use Direcht to expand the CCPDD. Clinical modelling is the process of structuring clinical data so it can be understood by computer systems and humans. The model contains all of the elements that are needed to define the data item. Results from the pilots show that Direcht creates a structured environment to build data items into models that fit into the larger CCPDD. Models can be represented as an HTML document, mind map, or exported in various formats for import into a computer system. Challenges identified over the course of both pilots are being addressed with c4c partners and external stakeholders.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Electronic Health Records Systems · Biomedical Text Mining and Ontologies · Scientific Computing and Data Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

John Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 3BZ, UK

Sidqam Ltd., Altrincham WA14 3NB, UK

Department of Medical Informatics & Statistics, The European Institute for Innovation through Health Data, Ghent University Hospital, 9000 Gent, Belgium

Funding

Innovative Medicines Initiative

References (28)

Show source-provided references
1. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support10.1016/j.jbi.2008.08.010 ↗
2. The conect4children (c4c) Consortium: Potential for Improving European Clinical Research into Medicines for Children
3. (2022, January 20). Conect4children (c4c). Available online: https://conect4children.org/.
4. CDISC (2022, January 20). Therapeutic Area Data Standards for Type 1 Diabetes—Pediatrics and Device Modules. Available online: https://www.cdisc.org/system/files/members/standard/ta/TAUG-.
5. Health Level Seven International (2022, January 20). HL7 Standards. Available online: https://www.hl7.org/.
6. Sharing and reuse of individual participant data from clinical trials: Principles and recommendations10.1136/bmjopen-2017-018647 ↗
7. Project, T.Y. (2022, January 20). Yale University Open Data Access (YODA) Project Procedures to Guide External Investigator Access to Clinical Trial Data. Available online: https://yoda.yale.edu.
8. Using electronic health records for clinical research: The case of the EHR4CR project10.1016/j.jbi.2014.10.006 ↗
9. Federated electronic health records research technology to support clinical trial protocol optimization: Evidence from EHR4CR and the InSite platform10.1016/j.jbi.2018.12.004 ↗
10. Performances of a Solution to Semi-Automatically Fill eCRF with Data from the Electronic Health Record: Protocol for a Prospective Individual Participant Data Meta-Analysis
11. Virtanen, M., Ustun, B., Rodrigues, J., Stroetmann, V., Surjan, G., Rector, A., Stroetmann, K., Lewalle, P., Zanstra, P.E., and Kalra, D. (2013). Semantic Interoperability for Better Health and Safer Healthcare: Deployment and Research Roadmap for Europe, European Commission.
12. Beale, T. (2022, January 20). Archetypes: Constraint-based Domain Models for Future-proof Information Systems. Available online: https://www.researchgate.net/publication/237033734_Archetypes_Constraint-based_Domain_Models_for_Future-proof_Information_Systems.
13. Archetype-Based Knowledge Management for Semantic Interoperability of Electronic Health Records
14. Clinical information modeling processes for semantic interoperability of electronic health records: Systematic review and inductive analysis10.1093/jamia/ocv008 ↗
15. Quality requirements for EHR Archetypes
16. Quality metrics for detailed clinical models10.1016/j.ijmedinf.2012.09.006 ↗
17. ISO (2022, January 20). ISO 13606-2:2019. Health Informatics—Electronic Health Record Communication—Part 2: Archetype interchange specification., Available online: https://www.iso.org/standard/62305.html.
18. ISO (2022, January 20). ISO 13606-1:2019. Health Informatics—Electronic Health Record Communication—Part 1: Reference Model., Available online: https://www.iso.org/standard/67868.html.
19. Evaluation of clinical information modeling tools10.1093/jamia/ocw018 ↗
20. Comparison and transformation between CDISC ODM and EN13606 EHR standards in connecting EHR data with clinical trial research data
21. (2022, January 20). Direcht. Available online: https://www.direcht.com/.
22. Towards ISO 13606 and openEHR archetype-based semantic interoperability
23. Evaluation of ISO EN 13606 as a result of its implementation in XML10.1177/1460458212473993 ↗
24. CDISC (2022, January 20). Therapeutic Area User Guides. Available online: https://www.cdisc.org/standards/therapeutic-areas.
25. A pragmatic method for transforming clinical research data from the research electronic data capture “REDCap” to Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model (SDTM): Development and evaluation of REDCap2SDTM10.1016/j.jbi.2017.05.003 ↗
26. Clinical trial data visualisation10.1186/1745-6215-16-S2-P187 ↗
27. Hassanzadeh, O., Lim, L., Kementsietsidis, A., Miller, R.J., and Wang, M. (2009). LinkedCT: A Linked Data Space for Clinical Trials. arXiv.
28. A comprehensive clinical research database based on CDISC ODM and i2b2