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

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 GkoutosWim Goettsch, Harry Hemingway, Martin Ingvar, Adrian Jonas, Robert Kazmierski, Susanne Logstrup, R. Thomas Lumbers, Thomas F. Luescher, Paul McGreavy, Ileana L. Pina, Lothar Roessig, Carl Steinbeisser, Mats Sundgren, Benoit 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

Research output: Contribution to journalReview articlepeer-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 languageEnglish
Pages (from-to)E757-E764
JournalThe Lancet Digital Health
Volume4
Issue number10
DOIs
Publication statusPublished - Oct 2022

Keywords

  • Big Data
  • COVID-19
  • Electronic Health Records
  • Electronics
  • Humans
  • Pandemics

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