The NCATS National COVID Cohort Collaborative (N3C) maintains one of the largest collections of clinical data related to COVID-19 symptoms and patient outcomes in the United States. Having access to a centralized enclave of this magnitude allows research teams to study, probe and answer clinically important questions about COVID-19 that they could not have answered previously.
There are more than 90 projects underway to explore a range of questions. Here are two examples. Access the complete listing of projects(link is external) that have been submitted through the Data Use Request (DUR) process and were approved by the N3C Data Access Committee.
The CICB and CTSC are participating in the National COVID Cohort Collaborative (N3C)
July 2020 -- The National COVID Cohort Collaborative (N3C) is a collaboration between the Center for Data to Health (CD2H) and National Center for Advancing Translational Sciences (NCATS) for the purpose of creating the NIH COVID-19 Data Warehouse.
The NIH COVID-19 Data Warehouse will be an NIH data sharing resource containing clinical and imaging data from individuals who have received a Coronavirus Disease 2019 (“COVID-19”) test or whose symptoms are consistent with COVID-19. Data will also be collected from individuals infected with pathogens such as SARS 1, MERS, and H1N1 to support comparative studies. The data warehouse will accelerate discovery using near real-time data and observational research, clinical studies and clinical trials, and will bring these data to bear on COVID-19. This solution requires a single computational environment to support public health actions, clinical care, policy, and science underpinning vaccines, prophylaxis, and treatment. The data warehouse will be highly interoperable, secure, clinical data research environment that will harmonize clinical and patient data. The NIH COVID-19 Data Warehouse will serve as a national resource to address the COVID-19 pandemic, as well as demonstrate coordination of clinical and patient data, setting an example for how to approach urgent research needs during future healthcare challenges.
NIH intends to provide access to and use by researchers for public health purposes and decision making, including conducting and supporting research to define the clinical natural history of COVID-19 infection and assess therapeutic responses and outcomes, and conducting and supporting a broad range of studies, including the identification of COVID-19 risk factors and development of effective countermeasures and diagnostics. Importantly, the underlying data model to which data from OMOP, PCORNet, i2b2/ACT, and TriNetX will be ETL’d (extract-transformed-loaded), harmonized and aggregated is the OMOP common data model.
The Cleveland Institute for Computational Biology (CICB) has engaged with the N3C via participation in the Data Ingestion & Harmonization work stream and the Phenotype & Data Acquisition work stream.