# Learning Health System Embedded Scientist Training and Research Center - RDAC

> **NIH AHRQ P30** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $166,087

## Abstract

Abstract - UCSF E-STaR Research Data and Analysis Core
The UCSF E-STaR Research Data and Analysis Core (RDAC) aims to create, identify, catalogue, and facilitate
the dissemination, implementation, and use of scientific information produced by E-STaR Scholars, with a
specific focus on AHRQ/PCORI priorities. RDAC will synergize activities with the other E-STaR Cores to
achieve the goals of Learning Health Systems (LHS) to continuously generate and implement new evidence in
the context of clinical care. RDAC will act as a portal to help LHS scientists identify issues of shared
importance across key stakeholders in the health system – leadership, frontline providers, patients and
families, researchers, and the larger community. It will provide required access to real-world data derived in the
context of clinical care to both monitor improvement processes and support robust evaluation. Equity is the
embedded through-line of all Aims, by prioritizing projects targeting healthcare disparities, measurement of
outcomes by priority populations, and dissemination strategies that link findings back to representative groups
of patients and families served within our healthcare settings. RDAC will rely on the principle of co-production
of intervention, evaluation, and dissemination strategies to ensure creation of useful knowledge to achieve the
following Aims: Aim 1. To guide E-STaR Scholars' co-production project study design, leveraging EHR-
enabled tools and infrastructure. Co-production for Aim 1 requires Scholars to work with E-STaR
stakeholders to identify opportunities for knowledge generation in the context of health system initiatives.
RDAC targets problems and priority areas identified by the Administrative Core (AC), and supports Scholars to
utilize skills and mentorship (particularly for implementation science and Lean methodology) supported by the
Research Education Core (REC). Aim 2. To provide analytic support and oversight for E-STaR Scholar
projects, RDAC uses co-production to analyze and interpret results so that useful and generalizable
knowledge is generated. RDAC's LHS Oversight Committee will rely on priorities (and membership) drawn
from the AC, and leverage research, implementation science, and leadership training from REC. Aim 3. To
collect, categorize, and disseminate E-STaR Scholars' project's and overall program's findings. Co-
production will frame a repository that categorizes opportunities, solutions, and results from Scholars' work to
optimally facilitate dissemination and spread of knowledge within UCSF E-STaR sites and nationally.
Expected Outcomes of RDAC: RDAC will be the learning laboratory for E-STaR Scholars, and a hub of
generalizable knowledge for E-STaR stakeholders and beyond. RDAC will support at least 1 project per
Scholar (and ad hoc consultations for UCSF community LHS scientists), will monitor outcomes and record
project details (e.g., informatics tool chosen, target population, impact on clinical outcomes), and...

## Key facts

- **NIH application ID:** 10814493
- **Project number:** 1P30HS029738-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** ANDREW D AUERBACH
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2024
- **Award amount:** $166,087
- **Award type:** 1
- **Project period:** 2024-01-01 → 2028-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10814493

## Citation

> US National Institutes of Health, RePORTER application 10814493, Learning Health System Embedded Scientist Training and Research Center - RDAC (1P30HS029738-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10814493. Licensed CC0.

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