The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment

Melissa A Haendel; Christopher G Chute; Tellen D Bennett; David A Eichmann; Justin Guinney; Warren A Kibbe; Philip R O Payne; Emily R Pfaff; Peter N Robinson; Joel H Saltz; Heidi Spratt; Christine Suver; John Wilbanks; Adam B Wilcox; Andrew E Williams; Chunlei Wu; Clair Blacketer; Robert L Bradford; James J Cimino; Marshall Clark; Evan W Colmenares; Patricia A Francis; Davera Gabriel; Alexis Graves; Raju Hemadri; Stephanie S Hong; George Hripscak; Dazhi Jiao; Jeffrey G Klann; Kristin Kostka; Adam M Lee; Harold P Lehmann; Lora Lingrey; Robert T Miller; Michele Morris; Shawn N Murphy; Karthik Natarajan; Matvey B Palchuk; Usman Sheikh; Harold Solbrig; Shyam Visweswaran; Anita Walden; Kellie M Walters; Griffin M Weber; Xiaohan Tanner Zhang; Richard L Zhu; Benjamin Amor; Andrew T Girvin; Amin Manna; Nabeel Qureshi; Michael G Kurilla; Sam G Michael; Lili M Portilla; Joni L Rutter; Christopher P Austin; Ken R Gersing; National COVID Cohort Collaborative (N3C)

doi:10.1093/jamia/ocaa196

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The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment

Journal article

Open access

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment

Melissa A Haendel, Christopher G Chute, Tellen D Bennett, David A Eichmann, Justin Guinney, Warren A Kibbe, Philip R O Payne, Emily R Pfaff, Peter N Robinson, Joel H Saltz, …

Journal of the American Medical Informatics Association : JAMIA, Vol.28(3), pp.427-443

03/01/2021

DOI: 10.1093/jamia/ocaa196

PMID: 32805036

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Abstract

Abstract Objective Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. Materials and Methods The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. Results Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. Conclusions The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.

Details

Title: Subtitle: The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment
Creators: Melissa A Haendel - Oregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, Oregon, USA, Translational and Integrative Sciences Center, Department of Molecular Toxicology, Oregon State University, Corvallis, Oregon, USA
Christopher G Chute - Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, Maryland, USA
Tellen D Bennett - Section of Informatics and Data Science, Department of Pediatrics, University of Colorado School of Medicine, University of Colorado, Aurora, Colorado, USA
David A Eichmann - School of Library and Information Science, The University of Iowa, Iowa City, Iowa, USA
Justin Guinney - Sage Bionetworks, Seattle, Washington, USA
Warren A Kibbe - Duke University, Durham,North Carolina, USA
Philip R O Payne - Institute for Informatics, Washington University in St. Louis, Saint Louis,Missouri, USA
Emily R Pfaff - North Carolina Translational and Clinical Sciences Institute (NC TraCS), University of North Carolina at Chapel Hill, Chapel Hill,North Carolina, USA
Peter N Robinson - Jackson Laboratory, Bar Harbor, Maine, USA
Joel H Saltz - Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
Heidi Spratt - University of Texas Medical Branch, Galveston, Texas, USA
Christine Suver - Sage Bionetworks, Seattle, Washington, USA
John Wilbanks - Sage Bionetworks, Seattle, Washington, USA
Adam B Wilcox - University of Washington, Seattle, Washington, USA
Andrew E Williams - Virginia Commonwealth University
Chunlei Wu - Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA
Clair Blacketer - Janssen Research and Development, LLC, Raritan, New Jersey, USA
Robert L Bradford - North Carolina Translational and Clinical Sciences Institute (NC TraCS), University of North Carolina at Chapel Hill, Chapel Hill,North Carolina, USA
James J Cimino - University of Alabama-Birmingham, Birmingham, Alabama, USA
Marshall Clark - North Carolina Translational and Clinical Sciences Institute (NC TraCS), University of North Carolina at Chapel Hill, Chapel Hill,North Carolina, USA
Evan W Colmenares - Department of Pharmaceutical Outcomes and Policy, University of North Carolina at Chapel Hill, Chapel Hill,North Carolina, USA
Patricia A Francis - Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
Davera Gabriel - Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
Alexis Graves - University of Iowa Institute for Clinical and Translational Science, The University of Iowa, Iowa City, Iowa, USA
Raju Hemadri - National Center for Advancing Translational Science, Bethesda, Maryland, USA
Stephanie S Hong - Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
George Hripscak - Department of Biomedical Informatics, Columbia University, New York, New York, USA
Dazhi Jiao - Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
Jeffrey G Klann - Harvard Medical School, Boston,Massachusetts, USA
Kristin Kostka - IQVIA, Durham, North Carolina, USA
Adam M Lee - University of North Carolina at Chapel Hill, Chapel Hill,North Carolina, USA
Harold P Lehmann - Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
Lora Lingrey - TriNetX, Cambridge,Massachusetts, USA
Robert T Miller - Tufts Clinical and Translational Science Institute, Tufts University, Boston,Massachusetts, USA
Michele Morris - Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh,Pennsylvania, USA
Shawn N Murphy - Mass General Brigham, Boston,Massachusetts, USA
Karthik Natarajan - Irving Medical Center, Columbia University, New York, New York, USA
Matvey B Palchuk - TriNetX, Cambridge,Massachusetts, USA
Usman Sheikh - National Center for Advancing Translational Science, Bethesda, Maryland, USA
Harold Solbrig - Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
Shyam Visweswaran - Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh,Pennsylvania, USA
Anita Walden - Oregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, Oregon, USA, Sage Bionetworks, Seattle, Washington, USA
Kellie M Walters - North Carolina Translational and Clinical Sciences Institute (NC TraCS), University of North Carolina at Chapel Hill, Chapel Hill,North Carolina, USA
Griffin M Weber - Department of Biomedical Informatics, Harvard Medical School, Boston,Massachusetts, USA
Xiaohan Tanner Zhang - Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
Richard L Zhu - Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
Benjamin Amor - Palantir Technologies, Palo Alto, California, USA
Andrew T Girvin - Palantir Technologies, Palo Alto, California, USA
Amin Manna - Palantir Technologies, Palo Alto, California, USA
Nabeel Qureshi - Palantir Technologies, Palo Alto, California, USA
Michael G Kurilla - Division of Clinical Innovation, National Center for Advancing Translational Science, Bethesda, Maryland, USA
Sam G Michael - National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA
Lili M Portilla - Office of Strategic Alliances, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA
Joni L Rutter - Office of the Director, National Center for Advancing Translational Science, Bethesda, Maryland, USA
Christopher P Austin - National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA
Ken R Gersing - National Center for Advancing Translational Science, Bethesda, Maryland, USA
National COVID Cohort Collaborative (N3C)
Resource Type: Journal article
Publication Details: Journal of the American Medical Informatics Association : JAMIA, Vol.28(3), pp.427-443
DOI: 10.1093/jamia/ocaa196
PMID: 32805036
NLM abbreviation: J Am Med Inform Assoc
ISSN: 1527-974X
eISSN: 1527-974X
Grant note: DOI: 10.13039/100000002, name: National Institutes of Health; name: National Center for Advancing Translational Sciences Institute, award: U24TR002306
Language: English
Date published: 03/01/2021
Academic Unit: School of Library and Information Science
Record Identifier: 9984080111802771

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