ORIGINAL RESEARCH article
Front. Public Health
Sec. Public Health Policy
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1581205
This article is part of the Research TopicImpact Evaluation using the Translational Science Benefits Model Framework in the National Center for Advancing Translational Science Clinical and Translational Science Award ProgramView all 5 articles
Building on the Translational Science Benefits Model to Include Team Science: A Practical and Theory-Based Approach to Continuous Quality Improvement and Impact Evaluation for Clinical and Translational Science Award Programs
Provisionally accepted
- Boston University, Boston, United States
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Introduction: Clinical and Translational Science Award (CTSA) programs seek to improve the quality and impact of clinical and translational science. CTSA evaluation teams implement structured, evidence-based continuous quality improvement (CQI) processes to enhance activities and outcomes, ultimately benefiting public health. The Translational Science Benefits Model (TSBM) provides a framework for assessing translational science's health and societal impact, yet additional tools are needed to integrate CQI with impact evaluation. Addressing this gap requires combining CQI methodologies with team science approaches. Building on TSBM, CQI theories (e.g., Plan-Do-Study-Act cycles), and team science principles (e.g., inclusive leadership), we propose a theory-driven, evidence-based logic model to enhance CTSA programs. Using our TL1 Regenerative Medicine Training Program (RMTP) as a case study, we demonstrate its practical application for CTSA evaluation teams.We conducted a literature review on impact evaluation, CQI, and team science to develop a theory-based approach for CTSA evaluation teams. Using case study methodology, we analyzed RMTP data (2015-2023) through: a) Interviews with RMTP leaders, mentors, and trainees to explore program implementation and outcomes; b) Document analysis of program materials, meeting notes, and reports; c) Bibliometric and policy analysis of publications, citations, and policy documents to assess impact; and d) Surveys to capture trainees' perspectives on program quality and leadership. This mixedmethods approach provided a comprehensive assessment of RMTP's impact and demonstrated the utility of our team science-based approach to CQI and evaluation.Results: Our sample included RMTP directors (N=2), mentors (N=24), and trainees (N=38).Among trainees, 68% identified as female, and 21% were from underrepresented groups in medicine. Of 34 graduates, 31 continued in regenerative medicine research. Qualitative data highlighted CQI strategies, such as embedding evaluation into advisory meetings to enhance program functioning. Inclusive leadership fostered a climate where diverse perspectives informed improvements. Quantitative and document analysis further demonstrated how RMTP activities led to positive health and societal impacts within the TSBM framework.Discussion: CTSA evaluation teams must integrate CQI and impact evaluation, yet few theory-based approaches exist. Our evaluation and CQI framework merges TSBM, CQI, and team science principles, providing a practical tool for guiding evaluation teams in continuous improvement while maximizing translational science impact.
Keywords: Clinical and Translational Sciences Award1, Continuous Quality Improvement2, evaluation3, Translational Science Benefits Model4, Logic Models5
Received: 21 Feb 2025; Accepted: 21 Apr 2025.
Copyright: © 2025 Brimhall, Kuhfeldt, Kotton and Jones. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Kim Brimhall, Boston University, Boston, United States
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.