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

Innovative Medicines Initiative BigData@Heart Consortium; European Society of Cardiology (ESC); CODE-EHR International Consensus Group; Dipak Kotecha; Folkert W Asselbergs; Stephan Achenbach; Stefan D Anker; Dan Atar; Colin Baigent; Amitava Banerjee; Birgit Beger; Gunnar Brobert; Barbara Casadei; Cinzia Ceccarelli; Martin R Cowie; Filippo Crea; Maureen Cronin; Spiros Denaxas; Andrea Derix; Donna Fitzsimons; Martin Fredriksson; Chris P Gale; Georgios V Gkoutos; Wim Goettsch; Harry Hemingway; Martin Ingvar; Adrian Jonas; Robert Kazmierski; Susanne Løgstrup; R Thomas Lumbers; Thomas F Lüscher; Paul McGreavy; Ileana L Piña; Lothar Roessig; Carl Steinbeisser; Mats Sundgren; Benoît Tyl; Ghislaine van Thiel; Kees van Bochove; Panos E Vardas; Tiago Villanueva; Marilena Vrana; Wim Weber; Franz Weidinger; Stephan Windecker; Angela Wood; Diederick E Grobbee

doi:10.1016/S2589-7500(22)00151-0

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

Innovative Medicines Initiative BigData@Heart Consortium, European Society of Cardiology (ESC), CODE-EHR International Consensus Group, Dipak Kotecha^*, Folkert W Asselbergs, Stephan Achenbach, Stefan D Anker, Dan Atar, Colin Baigent, Amitava Banerjee, Birgit Beger, Gunnar Brobert, Barbara Casadei, Cinzia Ceccarelli, Martin R Cowie, Filippo Crea, Maureen Cronin, Spiros Denaxas, Andrea Derix, Donna FitzsimonsMartin Fredriksson, Chris P Gale, Georgios V Gkoutos, Wim Goettsch, Harry Hemingway, Martin Ingvar, Adrian Jonas, Robert Kazmierski, Susanne Løgstrup, R Thomas Lumbers, Thomas F Lüscher, Paul McGreavy, Ileana L Piña, Lothar Roessig, Carl Steinbeisser, Mats Sundgren, Benoît Tyl, Ghislaine van Thiel, Kees van Bochove, Panos E Vardas, Tiago Villanueva, Marilena Vrana, Wim Weber, Franz Weidinger, Stephan Windecker, Angela Wood, Diederick E Grobbee

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

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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.

Original language	English
Pages (from-to)	e757-e764
Number of pages	8
Journal	The Lancet Digital Health
Volume	4
Issue number	10
Early online date	29 Aug 2022
DOIs	https://doi.org/10.1016/S2589-7500(22)00151-0
Publication status	Published - Oct 2022

Bibliographical note

Copyright:
© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

ASJC Scopus subject areas

Medicine (miscellaneous)
Health Informatics
Decision Sciences (miscellaneous)
Health Information Management

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KotechaD2022CODEEHRFinal published version, 1.29 MBLicence: Creative Commons: Attribution (CC BY)

Cite this

Innovative Medicines Initiative BigData@Heart Consortium, European Society of Cardiology (ESC), CODE-EHR International Consensus Group, Kotecha, D., Asselbergs, F. W., Achenbach, S., Anker, S. D., Atar, D., Baigent, C., Banerjee, A., Beger, B., Brobert, G., Casadei, B., Ceccarelli, C., Cowie, M. R., Crea, F., Cronin, M., Denaxas, S., Derix, A., ... Grobbee, D. E. (2022). CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research. The Lancet Digital Health, 4(10), e757-e764. https://doi.org/10.1016/S2589-7500(22)00151-0

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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 = "{Innovative Medicines Initiative BigData@Heart Consortium} and {European Society of Cardiology (ESC)} and {CODE-EHR International Consensus Group} and Dipak Kotecha and Asselbergs, {Folkert W} and Stephan Achenbach and Anker, {Stefan D} and Dan Atar and Colin Baigent and Amitava Banerjee and Birgit Beger and Gunnar Brobert and Barbara Casadei and Cinzia Ceccarelli and Cowie, {Martin R} and Filippo Crea and Maureen Cronin and Spiros Denaxas and Andrea Derix and Donna Fitzsimons and Martin Fredriksson and Gale, {Chris P} and Gkoutos, {Georgios V} and Wim Goettsch and Harry Hemingway and Martin Ingvar and Adrian Jonas and Robert Kazmierski and Susanne L{\o}gstrup and Lumbers, {R Thomas} and L{\"u}scher, {Thomas F} and Paul McGreavy and Pi{\~n}a, {Ileana L} and Lothar Roessig and Carl Steinbeisser and Mats Sundgren and Beno{\^i}t Tyl and Thiel, {Ghislaine van} and Bochove, {Kees van} and Vardas, {Panos E} and Tiago Villanueva and Marilena Vrana and Wim Weber and Franz Weidinger and Stephan Windecker and Angela Wood and Grobbee, {Diederick E}",

note = "Copyright: {\textcopyright} 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license",

year = "2022",

month = oct,

doi = "10.1016/S2589-7500(22)00151-0",

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Innovative Medicines Initiative BigData@Heart Consortium, European Society of Cardiology (ESC), CODE-EHR International Consensus Group, 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 2022, 'CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research', The Lancet Digital Health, vol. 4, no. 10, pp. e757-e764. https://doi.org/10.1016/S2589-7500(22)00151-0

CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research. / Innovative Medicines Initiative BigData@Heart Consortium; European Society of Cardiology (ESC); CODE-EHR International Consensus Group et al.
In: The Lancet Digital Health, Vol. 4, No. 10, 10.2022, p. e757-e764.

Research output: Contribution to journal › Review article › peer-review

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AU - Innovative Medicines Initiative BigData@Heart Consortium

AU - European Society of Cardiology (ESC)

AU - CODE-EHR International Consensus Group

AU - Kotecha, Dipak

AU - Asselbergs, Folkert W

AU - Achenbach, Stephan

AU - Anker, Stefan D

AU - Atar, Dan

AU - Baigent, Colin

AU - Banerjee, Amitava

AU - Beger, Birgit

AU - Brobert, Gunnar

AU - Casadei, Barbara

AU - Ceccarelli, Cinzia

AU - Cowie, Martin R

AU - Crea, Filippo

AU - Cronin, Maureen

AU - Denaxas, Spiros

AU - Derix, Andrea

AU - Fitzsimons, Donna

AU - Fredriksson, Martin

AU - Gale, Chris P

AU - Gkoutos, Georgios V

AU - Goettsch, Wim

AU - Hemingway, Harry

AU - Ingvar, Martin

AU - Jonas, Adrian

AU - Kazmierski, Robert

AU - Løgstrup, Susanne

AU - Lumbers, R Thomas

AU - Lüscher, Thomas F

AU - McGreavy, Paul

AU - Piña, Ileana L

AU - Roessig, Lothar

AU - Steinbeisser, Carl

AU - Sundgren, Mats

AU - Tyl, Benoît

AU - Thiel, Ghislaine van

AU - Bochove, Kees van

AU - Vardas, Panos E

AU - Villanueva, Tiago

AU - Vrana, Marilena

AU - Weber, Wim

AU - Weidinger, Franz

AU - Windecker, Stephan

AU - Wood, Angela

AU - Grobbee, Diederick E

PY - 2022/10

Y1 - 2022/10

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AB - 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.

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DO - 10.1016/S2589-7500(22)00151-0

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Innovative Medicines Initiative BigData@Heart Consortium, European Society of Cardiology (ESC), CODE-EHR International Consensus Group, Kotecha D, Asselbergs FW, Achenbach S et al. CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research. The Lancet Digital Health. 2022 Oct;4(10):e757-e764. Epub 2022 Aug 29. doi: 10.1016/S2589-7500(22)00151-0

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

Abstract

Bibliographical note

ASJC Scopus subject areas

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