Announcement: Access to the COVID-19 Data Analytics Platform Is Open

Last Updated February 25, 2021

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N3C Data Enclave

  • With stewardship from NCATS, more than 70 institutions, including more than 40 Clinical and Translational Science Awards (CTSA) Program hubs, worked together to build this extensive database to help researchers study COVID-19 and identify potential treatments as the pandemic evolves.
  • Close to 715,124 COVID-19-positive patients and more than 3.6 billion rows of data are included in this enclave. Apply for NCATS National COVID Cohort Collaborative (N3C) access today.
  • More than 120 projects are underway using the enclave data to examine associations between COVID-19 patient outcomes and social determinants of health.
  • The new public-facing N3C Cohort Exploration Dashboard provides high-level information about the N3C cohort and N3C Data Enclave.

A Powerful Tool for Researchers

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 120 projects underway to explore a range of questions. Here are two examples. Access the complete listing of projects that have been submitted through the Data Use Request (DUR) process and were approved by the N3C Data Access Committee.

How Social Determinants of Health Shape COVID-19 Vulnerability and Outcomes 

Affiliation: The University of Tennessee Health Science Center

Lead Investigator: Charisse Madlock, Ph.D., M.L.S.

Question: What social determinants are related to vulnerability to high incidence and poor COVID-19 outcomes at the patient and county level?

Objective: Identify how much Social Determinants of Health (SDoH) explain the variation in COVID-19 incidence, assess the impact of COVID-19 policies on the relationship between SDoH and COVID-19, and understand how SDOH can affect county-level resilience to COVID-19.

Impact: A greater understanding of the relationship between SDoH and COVID-19 can help policymakers target the most vulnerable populations and improve intervention implementation.

How COVID-19 Affects People With Suppressed or Compromised Immune Systems

Affiliation: Virginia Commonwealth University

Lead Investigator: Amy Olex, M.S.

Co-Leads: Roslyn Mannon, M.D. (University of Nebraska Medical Center), Vithal Madhira, M.S. (Palilia Software, Inc.)

Question: Individuals with suppressed or compromised immune systems (ISC) due to diseases or treatments are considered high-risk for developing severe or life-threatening symptoms due to viral infections. What is the impact of COVID-19 on these patients?

Objective: To utilize the unique large cohort of harmonized data from across the U.S. in the N3C Enclave to assess the impact of COVID-19 on those with an ISC condition. These conditions include, but are not limited to, organ transplant recipients, autoimmune diseases, and HIV. The researchers are answering questions on COVID-19 severity and outcomes such as the length of hospitalization, ventilator status, organ failure, death, and the impact of their condition or treatment.

Impact: Through this research, researchers can gain a better understanding of how various types, levels and duration of immunosuppression or compromise contribute towards ISC patient outcomes upon COVID-19 infection, which can inform future care strategies of these patients.

Researchers interested in accessing the data will need to register with N3C and submit a DUR for review by the N3C Data Access Committee. Learn more about the process and requirements, including data security training, for data access.

Hongfang Liu, Ph.D., program director for informatics at Mayo Clinic, is experienced in using clinical data for translational science research and to improve health care delivery. Dr. Liu explains how collaborating with experts in other disciplines to build the N3C Data Enclave will advance the science behind COVID-19 to deliver health care interventions and treatments.

View all I Am Translational Science videos.

A Resource Unlike Any Other

  • Harmonized data
    • The N3C platform translates the different ways that contributing hospitals store patient data into a single, common format to enable combined “apples-to-apples” analyses.
  • Robust in scale and scope
    • Currently, 73 sites across the country have agreed to transfer diverse data from individuals tested for COVID-19, including demographics, symptoms, laboratory test results, procedures, medications, medical conditions, physical measurements and more.
    • By marshalling the national reach of the Clinical and Translational Science Awards (CTSA) Program network, N3C is ensuring that the data represent the diversity of the country so researchers can understand and address geographic and population disparities during the pandemic.
  • Powerful analytics capabilities
    • The platform is built to enable machine-learning approaches and rigorous statistical analyses to identify connections and patterns more quickly than is possible through traditional methodologies. These advanced analytics approaches can lead to the simultaneous exploration of multiple questions — and to the revelation of likely answers — on a powerful scale.
  • Centralized and secure
    • The data reside and remain in NCATS’ secure, cloud-based database, certified through the Federal Risk and Authorization Management Program, or FedRAMP, which provides standardized assessment, authorization and continuous monitoring of cloud products and services, thereby ensuring the validity of the data while protecting patient privacy.
    • Three levels of protected data are included for analysis:
      • Limited Data Set (LDS): Consists of patient data that retain the following protected health information —
        • dates of service
        • patient ZIP code
      • De-identified Data Set: Consists of patient data from the LDS with the following changes —
        • Dates of service are algorithmically shifted to protect patient privacy.
        • Patient ZIP codes are truncated to the first three digits or removed entirely if the ZIP code represents fewer than 20,000 individuals.
      • Synthetic Data Set: Consists of data that are computationally derived from the LDS that resemble patient information statistically but are not actual patient data.

Learn more about the requirements for accessing different levels of data in the N3C Data Enclave.

Learn more about N3C data including data stewardship and protections.

 

The N3C is a collaborative, community-driven partnership among the NCATS-supported CTSA Program hubs and the National Center for Data to Health (CD2H), with overall stewardship by NCATS.

More information:

If you have questions about the N3C, please email NCATS_N3C@nih.gov.