# West Virginia Clinical and Translational Science Institute: A Statewide Organization Building Research Excellence and Engaging Communities to Improve Health

> **NIH NIH U54** · WEST VIRGINIA UNIVERSITY · 2022 · $645,360

## Abstract

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.

## Key facts

- **NIH application ID:** 10685808
- **Project number:** 3U54GM104942-07S2
- **Recipient organization:** WEST VIRGINIA UNIVERSITY
- **Principal Investigator:** Sally Lynn Hodder
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $645,360
- **Award type:** 3
- **Project period:** 2012-08-15 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10685808

## Citation

> US National Institutes of Health, RePORTER application 10685808, West Virginia Clinical and Translational Science Institute: A Statewide Organization Building Research Excellence and Engaging Communities to Improve Health (3U54GM104942-07S2). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10685808. Licensed CC0.

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