A National Center for Digital Health Informatics Innovation

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 3U24TR002306-05S1

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2021
    2023
  • Known Financial Commitments (USD)

    $96,811
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    CHRISTOPHER CHUTE
  • Research Location

    United States of America
  • Lead Research Institution

    UNIVERSITY OF COLORADO DENVER
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease susceptibility

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Type

    Clinical

  • Clinical Trial Details

    Not applicable

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Project Summary Local solutions rarely scale to multi-institutional settings, and don't realize the vision of CTSAs catalyzing data- driven translational research. Data, Software, and People are Largely Decentralized and Unconnected in CTSA. CTSAs hold a wealth of data that is neither accessible nor interoperable; this hinders opportunities to innovate algorithms and tools. Tools in turn, suffer from myopic focus or blind duplication. It is extremely difficult to identify expert partners whether for functionally validating a candidate variant for a rare disease, finding clinical cohorts, or navigating the IP odyssey of starting a company. There are the challenges in building a truly learning health system where high quality clinical and research data can effectively and efficiently be reused in clinical care. The CD2H has developed the National COVID Cohort Collaborative (N3C) with COVID data from clinical institutions across the country. This publicly available data resource includes data on adults and pediatrics and can address the questions related to vaccine effectiveness, treatments and predictions of severity of illness. The Pediatric COVID-19 DREAM Challenge will ask community participants to predict severity status in children, using the National COVID Cohort Collaborative (N3C) Electronic Health Record (EHR) data. The desired outcome for this challenge is to produce trained and validated pediatric COVID-19 severity prediction models that can be implemented into a clinical workflow in an EHR to help facilitate appropriate treatment.