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International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium

Gabriel A. Brat 1 Griffin M. Weber 1 Nils Gehlenborg 1 Paul Avillach 1 Nathan P. Palmer 1 Luca Chiovato 2 James Cimino 3 Brett K. Beaulieu-Jones 1 Sehi L'Yi 1 Mark S. Keller 1 Douglas S. Bell 4 Robert W. Follett 4 Lav P. Patel 5 Anne Sophie Jannot 6 Lemuel R. Waitman 5 Gilbert Omenn 7 Alberto Malovini 8 Jason H. Moore 9 Valentina Tibollo 8 Shawn N Murphy 10 Riccardo Bellazzi 11 David A Hanauer 12 Arnaud Serret-Larmande 13 Alba Gutierrez-Sacristan 1 John J Holmes 9 Douglas Bell 4 Kenneth D. Mandl 14 Jeffrey G Klann 10 Douglas A Murad 4 Luigia Scudeller 15 Mauro Bucalo 16 Katie Kirchoff 17 Jean Craig 17 Jihad Obeid 17 Vianney Jouhet 18, 19 Romain Griffier 20 Sébastien Cossin 21, 19 Bertrand Moal 22 Antonio Bellasi 23 Hans U Prokosch 24 Detlef Kraska 25 Piotr Sliz 14 Amelia L.M. Tan 1 Kee Yuan Ngiam 26 Alberto Zambelli 23 Danielle L Mowery 9 Emily Schiver 9 Batsal Devkota 27 Robert Bradford 28 Mohamad Daniar 14 Christel Daniel 29 Vincent Benoit 29 Romain Bey 29 Nicolas Paris 29 Patricia Serre 29 Nina Orlova 29 Julien Dubiel 29 Martin Hilka 29 Stephane Breant 29 Judith Leblanc 30 Nicolas Griffon 31 Anita Burgun 32 Melodie Bernaux 29 Arnaud Sandrin 29 Elisa Salamanca 29 Sylvie Cormont 29 Thomas Ganslandt 33 Tobias Gradinger 33 Julien Champ 34 Martin Boeker 35 Patricia Martel 29 Loïc Estève 36 Alexandre Gramfort 36 Olivier Grisel 36 Damien Leprovost 37 Thomas Moreau 36 Gael Varoquaux 36, 38, 39 Jill-Jênn Vie 40, 41 Demian Wassermann 36 Arthur Mensch 36 Charlotte Caucheteux 42 Christian Haverkamp 35 Guillaume Lemaître 36 Silvano Bosari 43 Andrew South 44 Tianxi Cai 45 Isaac Kohane 1 
34 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
36 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
NEUROSPIN - Service NEUROSPIN, Inria Saclay - Ile de France
40 Scool - Scool
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : We leveraged the largely untapped resource of electronic health record data to address critical clinical and epidemiological questions about Coronavirus Disease 2019 (COVID-19). To do this, we formed an international consortium (4CE) of 96 hospitals across 5 countries (www.covidclinical.net). Contributors utilized the Informatics for Integrating Biology and the Bedside (i2b2) or Observational Medical Outcomes Partnership (OMOP) platforms to map to a common data model. The group focused on comorbidities and temporal changes in key laboratory test values. Harmonized data were analyzed locally and converted to a shared aggregate form for rapid analysis and visualization of regional differences and global commonalities. Data covered 27,584 COVID-19 cases with 187,802 laboratory tests. Case counts and laboratory trajectories were concordant with existing literature. Laboratory tests at the time of diagnosis showed hospital-level differences equivalent to country-level variation across the consortium partners. Despite the limitations of decentralized data generation, we established a framework to capture the trajectory of COVID-19 disease in patients and their response to interventions.
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Submitted on : Friday, August 21, 2020 - 10:32:49 PM
Last modification on : Friday, August 5, 2022 - 3:03:28 PM
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Gabriel A. Brat, Griffin M. Weber, Nils Gehlenborg, Paul Avillach, Nathan P. Palmer, et al.. International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium. npj Digital Medicine, Nature Research 2020, 3 (1), pp.#109. ⟨10.1038/s41746-020-00308-0⟩. ⟨hal-02918344⟩

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