Literature DB >> 36050271

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

Dipak Kotecha1, Folkert W Asselbergs2, Stephan Achenbach3, Stefan D Anker4, Dan Atar5, Colin Baigent6, Amitava Banerjee7, Birgit Beger8, Gunnar Brobert9, Barbara Casadei10, Cinzia Ceccarelli11, Martin R Cowie12, Filippo Crea13, Maureen Cronin14, Spiros Denaxas15, Andrea Derix16, Donna Fitzsimons17, Martin Fredriksson18, Chris P Gale19, Georgios V Gkoutos20, Wim Goettsch21, Harry Hemingway22, Martin Ingvar23, Adrian Jonas24, Robert Kazmierski25, Susanne Løgstrup8, R Thomas Lumbers26, Thomas F Lüscher27, Paul McGreavy28, Ileana L Piña29, Lothar Roessig16, Carl Steinbeisser30, Mats Sundgren31, Benoît Tyl32, Ghislaine van Thiel33, Kees van Bochove34, Panos E Vardas35, Tiago Villanueva36, Marilena Vrana8, Wim Weber36, Franz Weidinger37, Stephan Windecker38, Angela Wood39, Diederick E Grobbee40.   

Abstract

Big data is important to new developments in global clinical science that aim to improve the lives of patients. Technological advances have led to the regular use of structured electronic health-care records with the potential to address key deficits in clinical evidence that could improve patient care. The COVID-19 pandemic has shown this potential in big data and related analytics but has also revealed important limitations. Data verification, data validation, data privacy, and a mandate from the public to conduct research are important challenges to effective use of routine health-care data. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including representation from patients, clinicians, scientists, regulators, journal editors, and industry members. In this Review, we propose the CODE-EHR minimum standards framework to be used by researchers and clinicians to improve the design of studies and enhance transparency of study methods. The CODE-EHR framework aims to develop robust and effective utilisation of health-care data for research purposes.
Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

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Year:  2022        PMID: 36050271     DOI: 10.1016/S2589-7500(22)00151-0

Source DB:  PubMed          Journal:  Lancet Digit Health        ISSN: 2589-7500


  1 in total

1.  Post-mortem examination of high mortality in patients with heart failure and atrial fibrillation.

Authors:  Otilia Țica; Ovidiu Țica; Karina V Bunting; Joseph deBono; Georgios V Gkoutos; Mircea I Popescu; Dipak Kotecha
Journal:  BMC Med       Date:  2022-10-05       Impact factor: 11.150

  1 in total

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