# The integrated Translational Health Research Institute of Virginia (iTHRIV): Using Data to Improve Health

> **NIH NIH UL1** · UNIVERSITY OF VIRGINIA · 2021 · $50,000

## Abstract

The unknown and changing characteristics of the SARS-CoV-2 pandemic have severely challenged the
United States (U.S.) health care systems. The key to addressing many of these challenges is data and
information sharing. To do this requires bringing together individual level health data from disparate systems into
a common structure that can be analyzed for answers to the important questions about COVID-19.
 Within the health informatics community there are two approaches to integrating data for analysis: (1)
Federated data sharing which keeps the data at individual locations and allows for aggregated queries and (2)
Harmonized repository that joins the data from the different sites into one database with a common data model
that allows for individual or row level queries. While the federated approach is easier to implement and much
more widely used, the harmonization approach is what is needed to address the challenges of the COVID-19
pandemic since it will enable more impactful data analysis on the scientific questions surrounding this disease.
 The University of Virginia (UVA), the lead site for the cross-state integrated Translational Health Research
Institute of Virginia (iTHRIV), is well positioned to serve as an initial, pilot provider of data for the harmonized,
analytic database being assembled by the National Center for Advancing Translational Sciences (NCATS)
known as the National COVID Cohort Collaborative (N3C). There four reasons iTHRIV can do this at UVA: 1)
iTHRIV has implemented the Observational Medical Outcomes Partnership (OMOP) Common Data Model
(CDM) and this is not only the accepted CDM for data transfer to N3C but it also the target data transfer model
for N3C, which will make the iTHRIV CDM a good choice to validate data transforms; 2) The iTHRIV informatics
team have been active participants in the development of the COVID-19 Phenotype implementation in OMOP
and we can thus quickly implement the data queries; 3) The iTHRIV data Commons utilizes an architecture which
includes multiple CDM and this gives us the capability to expand data acquisition to all partner institutions in
iTHRIV and to rapidly respond to changes required in data acquisition and transfer; and 4) The University of
Virginia has an IRB Reliance Agreement in place with SMART IRB and can rely on any non-UVA IRB that also
has an IRB Reliance Agreement with SMART IRB, which will streamline our start-up process for participation.
iTHRIV at UVA therefore provides an ideal pilot site for the N3C project, and brings the iTHRIV Commons and
the iTHRIV partners institutions to rapidly support rapid expansion to other CDM as a model for the larger
consortium. The Commons also provides a leading team-science platform during the follow-on phases of N3C
where researchers within Virginia can collaborate with others from around the U.S. and the world to analyze the
data collected in centralized repository by the N3C project and address impactful health problems for the
co...

## Key facts

- **NIH application ID:** 10335371
- **Project number:** 3UL1TR003015-03S1
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Donald E Brown
- **Activity code:** UL1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $50,000
- **Award type:** 3
- **Project period:** 2020-08-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10335371

## Citation

> US National Institutes of Health, RePORTER application 10335371, The integrated Translational Health Research Institute of Virginia (iTHRIV): Using Data to Improve Health (3UL1TR003015-03S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10335371. Licensed CC0.

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