135 Learning experience from establishing a Research Seed Grant Program supporting an integrated community-based research and practice via the learning health system framework

Objectives/Goals: Community-based practices have limited research opportunities for providers. As a rural community-based health system, Mayo Clinic Health System (MCHS) sought to create intramural funding mechanisms to help early-stage researchers conduct pilot research so they are more competitive to compete for more robust extramural funding opportunities. Methods/Study Population: We created a Research Seed Grant Program infrastructure across our four MCHS regions (Southwest and Southeast Minnesota, Northwest and Southwest Wisconsin). This model program featured an initial research funding announcement call based on 6 prioritized programs (AI Validation & Stewardship, Cancer, Health Equity, Population Health, Rural Health, Learning Healthcare System [LHS]), with submissions uploaded to a central electronic repository. Proposal review and ranking was organized on a regional basis, with ranking of all proposals by at least 2 clinical scientist reviewers according to the NIH domain-specific framework (i.e., 1.0 best > 9.0 worst). Awards were competitively selected by conformity to prioritized research areas and through ranking of most competitive overall application scores. Results/Anticipated Results: For our inaugural RFA, we received 55 grant application submissions across the MCHS regions. Fifteen of the most highly ranked applications were selected for awards on a per region basis, providing direct funding as well as protected investigator research time of 10% for up to six months. The selected projects address several research priorities including improving access, reducing health disparities, improving behavioral health in our communities, increasing cancer screening and prevention, and community-based pragmatic trials and interventions. Outcomes from these now completed pilot projects remain pending at this time. Funding for this seed grant program was supported by philanthropy, Mayo Clinic Research Administration, Mayo Clinic Comprehensive Cancer Center, and the Mayo Clinic CCaTS Rural Core. Discussion/Significance of Impact: We present this framework for a LHS-focused Seed Grant program model for consideration of adoption by other national/international LHS. Future plans include tracking of outcome metrics (e.g., published peer review articles, extramural grant applications) of this initial cycle and future expansion of this program to support the goals of our LHS.

Authors

Institutions

Publication Details

Journal
Journal of Clinical and Translational Science
Published
2025-03-25
DOI
https://doi.org/10.1017/cts.2024.795
Primary Topic
Health Sciences Research and Education
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

135 Learning experience from establishing a Research Seed Grant Program supporting an integrated community-based research and practice via the learning health system framework

Young J. Juhn, Nanako A Hawley, Édouard Louis, Jennifer A. Weis et al.
Journal of Clinical and Translational Science
Health Sciences Research and Education
article

135 Learning experience from establishing a Research Seed Grant Program supporting an integrated community-based research and practice via the learning health system framework

Young J. Juhn, Nanako A Hawley, Édouard Louis, Jennifer A. Weis, Thanai Pongdee, Matthew Spiten
article en

Abstract

Objectives/Goals: Community-based practices have limited research opportunities for providers. As a rural community-based health system, Mayo Clinic Health System (MCHS) sought to create intramural funding mechanisms to help early-stage researchers conduct pilot research so they are more competitive to compete for more robust extramural funding opportunities. Methods/Study Population: We created a Research Seed Grant Program infrastructure across our four MCHS regions (Southwest and Southeast Minnesota, Northwest and Southwest Wisconsin). This model program featured an initial research funding announcement call based on 6 prioritized programs (AI Validation & Stewardship, Cancer, Health Equity, Population Health, Rural Health, Learning Healthcare System [LHS]), with submissions uploaded to a central electronic repository. Proposal review and ranking was organized on a regional basis, with ranking of all proposals by at least 2 clinical scientist reviewers according to the NIH domain-specific framework (i.e., 1.0 best > 9.0 worst). Awards were competitively selected by conformity to prioritized research areas and through ranking of most competitive overall application scores. Results/Anticipated Results: For our inaugural RFA, we received 55 grant application submissions across the MCHS regions. Fifteen of the most highly ranked applications were selected for awards on a per region basis, providing direct funding as well as protected investigator research time of 10% for up to six months. The selected projects address several research priorities including improving access, reducing health disparities, improving behavioral health in our communities, increasing cancer screening and prevention, and community-based pragmatic trials and interventions. Outcomes from these now completed pilot projects remain pending at this time. Funding for this seed grant program was supported by philanthropy, Mayo Clinic Research Administration, Mayo Clinic Comprehensive Cancer Center, and the Mayo Clinic CCaTS Rural Core. Discussion/Significance of Impact: We present this framework for a LHS-focused Seed Grant program model for consideration of adoption by other national/international LHS. Future plans include tracking of outcome metrics (e.g., published peer review articles, extramural grant applications) of this initial cycle and future expansion of this program to support the goals of our LHS.

Journal of Clinical and Translational ScienceVol. 9(s1)
WinnMed (US)
National Institutes of Health
Openalex Percentile: Top 91%
Health Sciences Research and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.