# Quality Assurance and Reporting

> **NIH NIH UL1** · VIRGINIA COMMONWEALTH UNIVERSITY · 2020 · $117,816

## Abstract

Project Summary/Abstract
 A primary goal of the CTSA Program is to support research institutions to
improve the efficiency, effectiveness, and reach of clinical translational research.
However, the reality is there are administrative reporting and approval requirements
related to conducting translational research. Such requirements include NCATS Prior
Approval for activities such as changes in key personnel, requesting carryover funds,
standard annual reporting, and human subjects Prior Approval for KL2 Scholars and for
Pilot Projects. If administrative reporting requirements contain errors or incomplete
material this process delays the conduct of clinical translational research. As such, it is
necessary to ensure quality of our reporting and that we, as a hub, meet reporting
expectations by NCATS.
 This administrative supplement will support a staff position with the
intention of managing and ensuring quality assurance for reporting activities to
NCATS. This position will work with the Director of Evaluation, PI/Director and
Administrative Director in ensuring that reporting requirements are consistent,
efficient and error free. The individual who fills the staff position will contribute to
the development of procedures at our local CTSA hub and will share and
disseminate processes and procedures work well to the CTSA network.

## Key facts

- **NIH application ID:** 10158702
- **Project number:** 3UL1TR002649-03S1
- **Recipient organization:** VIRGINIA COMMONWEALTH UNIVERSITY
- **Principal Investigator:** FREDERICK Gerard MOELLER
- **Activity code:** UL1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $117,816
- **Award type:** 3
- **Project period:** 2020-07-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10158702

## Citation

> US National Institutes of Health, RePORTER application 10158702, Quality Assurance and Reporting (3UL1TR002649-03S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10158702. Licensed CC0.

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