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Principal Investigator: Sally Lynn Hodder
Organization: WEST VIRGINIA UNIVERSITY
Fiscal Year: 2022
Award: $645,360
Funding agency: National Institute of General Medical Sciences
Electronic Health Record (EHR) data collected during routine clinical care offer real world evidence to support
decision making and observational research. The National COVID Cohort Collaborative (N3C) is a centralized
national EHR data resource for the study of COVID-19 patient outcomes. Centers supported by the Institutional
Development Award for Clinical and Translational Research (IDeA-CTRs) have effectively contributed
data and expertise to N3C, and the IDeA-CTR N3C initiative has served as an important stimulus to
forming a cohesive, collaborative CTR network, poised for meaningful future scientific contributions
relevant to the minority and underserved populations in IDeA states. Since the inception of the IDeA-
CTR N3C initiative in 2020, the West Virginia Clinical and Translational Science Institute (WVCTSI)
has provided infrastructure that has driven productivity and collaboration among participating IDeA-
CTRs. For Year 3 of the IDeA-CTR N3C initiative, WVCTSI will continue to provide network wide
infrastructure, while expanding novel data analytic techniques, thereby generating data relevant to
optimizing COVID-19 patient outcomes while driving collaboration and investigator engagement across
the IDeA-CTR network. We will accomplish these broad objectives through the following specific aims:
Aim 1- Provide IDeA-CTR infrastructure to drive relevant science and productivity. To accomplish
this aim, WVCTSI personnel will provide administrative support to the entire IDeA-CTR N3C team;
Aim 2 - Increase frequency of WVCTSI data exports to improve timely data availability and
ensure SARS-CoV-2 variant data are released appropriately in N3C. Given the speed with which
SARS-CoV-2 is evolving as well as the increasing number of available therapeutic agents, frequent
data exports are needed to minimize lag time with which new data may be used; Aim 3 - Expand
novel data analytic techniques, including machine learning (ML) and artificial intelligence (AI)
strategies as well as geospatial methods and disseminate across the IDeA-CTR N3C
Consortium. Machine learning approaches leverage the power of a large-scale database to identify
efficacious therapies while spatial analyses will investigate geographic disparities in COVID 19 related
outcomes; Aim 4 - Actively engage investigators in high quality COVID-19 data projects relevant
to populations in their respective states while facilitating investigator development.
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