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CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research

Kotecha, D; Asselbergs, FW; Achenbach, S; Anker, SD; Atar, D; Baigent, C; Banerjee, A; ... Grobbee, DE; + view all (2022) CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research. The BMJ , 378 , Article e069048. 10.1136/bmj-2021-069048. Green open access

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Abstract

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes.

Type: Article
Title: CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research
Open access status: An open access version is available from UCL Discovery
DOI: 10.1136/bmj-2021-069048
Publisher version: https://doi.org/10.1136/bmj-2021-069048
Language: English
Additional information: © 2022 BMJ Publishing Group Ltd. This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license (http://creativecommons.org/licenses/by/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
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
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Infectious Disease Informatics
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10156358
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