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

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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.