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-19Start & end year
20212023Known Financial Commitments (USD)
$96,811Funder
National Institutes of Health (NIH)Principal Investigator
CHRISTOPHER CHUTEResearch Location
United States of AmericaLead Research Institution
UNIVERSITY OF COLORADO DENVERResearch 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.