CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research
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.
Author
Kotecha, Dipak
Asselbergs, Folkert W
Achenbach, Stephan
Anker, Stefan D
Atar, Dan
Baigent, Colin
Banerjee, Amitava
Beger, Birgit
Brobert, Gunnar
Casadei, Barbara
Ceccarelli, Cinzia
Cowie, Martin R
Crea, Filippo
Cronin, Maureen
Denaxas, Spiros
Derix, Andrea
Fitzsimons, Donna
Fredriksson, Martin
Gale, Chris P
Gkoutos, Georgios V
Goettsch, Wim
Hemingway, Harry
Ingvar, Martin
Jonas, Adrian
Kazmierski, Robert
Løgstrup, Susanne
Lumbers, R Thomas
Lüscher, Thomas F
McGreavy, Paul
Piña, Ileana L
Roessig, Lothar
Steinbeisser, Carl
Sundgren, Mats
Tyl, Benoît
Thiel, Ghislaine van
Bochove, Kees van
Vardas, Panos E
Villanueva, Tiago
Vrana, Marilena
Weber, Wim
Weidinger, Franz
Windecker, Stephan
Wood, Angela
Grobbee, Diederick E
Asselbergs, Folkert W
Achenbach, Stephan
Anker, Stefan D
Atar, Dan
Baigent, Colin
Banerjee, Amitava
Beger, Birgit
Brobert, Gunnar
Casadei, Barbara
Ceccarelli, Cinzia
Cowie, Martin R
Crea, Filippo
Cronin, Maureen
Denaxas, Spiros
Derix, Andrea
Fitzsimons, Donna
Fredriksson, Martin
Gale, Chris P
Gkoutos, Georgios V
Goettsch, Wim
Hemingway, Harry
Ingvar, Martin
Jonas, Adrian
Kazmierski, Robert
Løgstrup, Susanne
Lumbers, R Thomas
Lüscher, Thomas F
McGreavy, Paul
Piña, Ileana L
Roessig, Lothar
Steinbeisser, Carl
Sundgren, Mats
Tyl, Benoît
Thiel, Ghislaine van
Bochove, Kees van
Vardas, Panos E
Villanueva, Tiago
Vrana, Marilena
Weber, Wim
Weidinger, Franz
Windecker, Stephan
Wood, Angela
Grobbee, Diederick E
Citations
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Date
2022-08-29
Type
Article
Subject
Public health. Health statistics. Occupational health. Health education, Cardiology
Collections
Citation
Kotecha D, Asselbergs FW, Achenbach S, Anker SD, Atar D, Baigent C, Banerjee A, Beger B, Brobert G, Casadei B, Ceccarelli C, Cowie MR, Crea F, Cronin M, Denaxas S, Derix A, Fitzsimons D, Fredriksson M, Gale CP, Gkoutos GV, Goettsch W, Hemingway H, Ingvar M, Jonas A, Kazmierski R, Løgstrup S, Lumbers RT, Lüscher TF, McGreavy P, Piña IL, Roessig L, Steinbeisser C, Sundgren M, Tyl B, Thiel GV, Bochove KV, Vardas PE, Villanueva T, Vrana M, Weber W, Weidinger F, Windecker S, Wood A, Grobbee DE; Innovative Medicines Initiative BigData@Heart Consortium, European Society of Cardiology, and CODE-EHR International Consensus Group. CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research. Lancet Digit Health. 2022 Oct;4(10):e757-e764. doi: 10.1016/S2589-7500(22)00151-0. Epub 2022 Aug 29.
Journal / Source Title
The Lancet Digital Health
DOI
10.1016/S2589-7500(22)00151-0
PMID
36050271
Publisher
Elsevier
Publisher’s URL
https://www.sciencedirect.com/journal/the-lancet-digital-health