Analytics Platform Harnesses COVID-19 Patient Data

National COVID Cohort Collaborative platform helps scientists analyze disease and develop treatments
matrix of data

The National Institutes of Health (NIH) has launched a centralized, secure enclave to store and study vast amounts of medical record data from people diagnosed with coronavirus disease across the country. 

It is part of an effort, called the National COVID Cohort Collaborative (N3C), to help scientists analyze these data to understand the disease and develop treatments. 

This effort announced on June 17, 2020, aims to transform clinical information into knowledge urgently needed to study COVID-19 disease, including health risk factors that indicate better or worse outcomes of the disease, and identify potentially effective treatments.

The N3C initiative will create an analytics platform to systematically collect clinical, laboratory, and diagnostic data from health care provider organizations nationwide. 

It will then harmonize the aggregated information into a standard format and make it available rapidly for researchers and health care providers to accelerate COVID-19 research and provide information that may improve clinical care.

Having access to a centralized enclave of this magnitude will help researchers and healthcare providers answer clinically important questions they previously could not, such as, 

“Can we predict who might need dialysis because of kidney failure?” or, 

“Who might need to be on a ventilator because of lung failure?” and, 

“Are there different patient responses to coronavirus infection that require distinct therapies?”

There currently are 35 collaborating sites across the country and the platform contains diverse data from individuals tested for COVID-19.

Contributing sites add demographics, symptoms, medications, lab test results, and outcomes data regularly over a five-year period, enabling both the immediate and long-term study of the impact of COVID-19 on health outcomes.

The platform is built to enable machine learning approaches and rigorous statistical analyses, identifying connections and patterns more quickly than can be done through traditional methodologies. 

These advanced analytics approaches require large, robust datasets to generate statistically valid results and can lead to the simultaneous exploration of multiple questions – and the revealing of likely answers – on a powerful scale.

“The exciting transformation this platform represents is in providing an environment where data and the power of the analytics can be used by researchers and clinicians to quickly examine and answer new COVID-19 hypotheses,” said Warren A. Kibbe, Ph.D., chief of Translational Biomedical Informatics in the Department of Biostatistics and Bioinformatics and chief data officer for the Duke Cancer Institute.

To learn more about the National COVID Cohort Collaborative, including data transfer and access, visit N3C.

N3C is funded by the National Center for Advancing Translational Sciences (NCATS), and support for the N3C comes from the National Cancer Institute, the National Institute of Diabetes and Digestive and Kidney Diseases and the National Institute of General Medical Sciences.

For more information about NIH and its programs, visit National Institutes of Health.

Coronavirus Today publishes pandemic news.