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The N3C governance ecosystem: A model socio-technical partnership for the future of collaborative analytics at scale.

Authors :
Suver C
Harper J
Loomba J
Saltz M
Solway J
Anzalone AJ
Walters K
Pfaff E
Walden A
McMurry J
Chute CG
Haendel M
Source :
Journal of clinical and translational science [J Clin Transl Sci] 2023 Nov 14; Vol. 7 (1), pp. e252. Date of Electronic Publication: 2023 Nov 14 (Print Publication: 2023).
Publication Year :
2023

Abstract

The National COVID Cohort Collaborative (N3C) is a public-private-government partnership established during the Coronavirus pandemic to create a centralized data resource called the "N3C data enclave." This resource contains individual-level health data from participating healthcare sites nationwide to support rapid collaborative analytics. N3C has enabled analytics within a cloud-based enclave of data from electronic health records from over 17 million people (with and without COVID-19) in the USA. To achieve this goal of a shared data resource, N3C implemented a shared governance strategy involving stakeholders in decision-making. The approach leveraged best practices in data stewardship and team science to rapidly enable COVID-19-related research at scale while respecting the privacy of data subjects and participating institutions. N3C balanced equitable access to data, team-based scientific productivity, and individual professional recognition - a key incentive for academic researchers. This governance approach makes N3C research sustainable and effective beyond the initial days of the pandemic. N3C demonstrated that shared governance can overcome traditional barriers to data sharing without compromising data security and trust. The governance innovations described herein are a helpful framework for other privacy-preserving data infrastructure programs and provide a working model for effective team science beyond COVID-19.<br />Competing Interests: None of the authors has conflicts of interest related to this work.<br /> (© The Author(s) 2023.)

Details

Language :
English
ISSN :
2059-8661
Volume :
7
Issue :
1
Database :
MEDLINE
Journal :
Journal of clinical and translational science
Publication Type :
Academic Journal
Accession number :
38229902
Full Text :
https://doi.org/10.1017/cts.2023.681