ArticleLearning health systems2025
Funding model for embedded research: Impacts, challenges, and lessons learned for investigators.
Article in Learning health systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Funding model for embedded research: Impacts, challenges, and lessons learned for investigators.Learning health systems · 2025Article
- Next Frontiers in Embedded Research Career Pathways; A Response to Recent Commentaries.International journal of health policy and management · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Embedding research mechanisms within Learning Health Systems can improve healthcare performance by informing program development and expansion, supporting strategic planning, and demonstrating value. The role of the investigator is crucial in partnered funding mechanisms, and there is a growing need to better understand how investigators operate in this space. This evaluation assessed the impacts, challenges, and lessons learned by investigators funded through an embedded research program. Methods: This was an outcome evaluation within the Department of Veterans Affairs healthcare system and followed an adapted version of the Centers for Disease Control and Prevention evaluation framework. Three data sources were used to generate information: a descriptive analysis of close-out reports, a comprehensive search of research databanks, and an online survey focused on high-priority areas. Participants were investigators whose projects took place during the FY2017-2021 funding period. During the funding period, 25 unique investigators completed projects. Results: Investigators indicated that the embedded research program had significant, meaningful impacts on their professional development, including generating tangible products that advanced their professional goals and more subtle impacts, such as increasing knowledge and experience, increasing multidisciplinary collaboration, and creating opportunities for professional development. Investigators also reflected on challenges, including issues with the data, logistical concerns, and disruptions due to COVID-19. Investigators identified lessons learned for future collaboration efforts, including the need for feasible and appropriate goals, as well as dedicated and trained support staff. Conclusions: The insights from this evaluation provide understanding on the impacts, challenges, and lessons learned from the experiences of investigators participating in embedded research mechanisms. The impacts illuminated explicit ways in which investigators professionally benefited from this program, as well as challenges and lessons learned that offer insights into how future programs can be tailored. These findings offer ways to improve practices in implementing LHS in other large healthcare organizations.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.