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The CODE-EHR global framework: lifting the veil on health record data

Asselbergs, Folkert W; Kotecha, Dipak; (2023) The CODE-EHR global framework: lifting the veil on health record data. European Heart Journal , 44 (36) pp. 3398-3400. 10.1093/eurheartj/ehad424. Green open access

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Abstract

With the emergence of electronic health record (EHR) systems, the application of big data research, including support from artificial intelligence, has the potential to massively enhance the value of routine data in healthcare. Big data research can also play a crucial role in generating evidence for clinical practice guidelines. One major advantage is the dynamic provision of contemporary evidence, which can update policies often based on historical studies that do not reflect current disease burdens or modern management strategies. Additionally, big data analysis can address patients with multimorbidity who are not well represented in clinical trials that underpin practice guidelines. However, there are several major obstacles and limitations to using routine care data, such as data access and quality, privacy, and security. Data are often not standardized, with limited interoperability between data sources. The COVID-19 pandemic has illustrated the need for open-access contemporary healthcare data and the urgency to develop new approaches to improve data anonymization and pseudonymization whilst preserving transparency and traceability of data. The retractions of COVID-19 studies1,2 are a clear signpost that guidance is needed to build trust using EHR data for evidence generation.

Type: Article
Title: The CODE-EHR global framework: lifting the veil on health record data
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/eurheartj/ehad424
Publisher version: https://doi.org/10.1093/eurheartj/ehad424
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery.ucl.ac.uk/id/eprint/10178522
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