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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

Lookup NU author(s): Chima Amadi, Becca LearyORCiD, Avril PalmeriORCiD, Victoria HedleyORCiD, Dr Anando SenORCiD, Professor Volker StraubORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


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.


Publication metadata

Author(s): Amadi C, Leary R, Palmeri A, Hedley V, Sen A, Siddiqui RQ, Kalra D, Straub V

Publication type: Article

Publication status: Published

Journal: Applied Sciences

Year: 2022

Volume: 12

Issue: 3

Online publication date: 02/02/2022

Acceptance date: 28/01/2022

Date deposited: 19/07/2022

ISSN (electronic): 2076-3417

Publisher: MDPI

URL: https://doi.org/10.3390/app12031604

DOI: 10.3390/app12031604

PubMed id: 33539007


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Funding

Funder referenceFunder name
777389IMI Joint Undertaking

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