Evidence map›Paper›PMID 40361080›Full record

ArticleBMC health services research2025

Evaluating for learning and sustainability (ELS) framework: a realist synthesis.

Marissa Bird, Maura MacPhee, James Shaw, Walter P Wodchis, Lianne Jeffs, Tujuanna Austin, Frances Bruno, Balpreet Panesar, Élizabeth Côté Boileau, Robert J Reid and 1 more

Abstract read
In one paragraph

Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Marissa BirdInstitute for Better Health, Trillium Health Partners, Mississauga, ON, Canada. marissa.bird@thp.ca.
Maura MacPheeUniversity of British Columbia School of Nursing, Vancouver, BC, Canada.
James ShawDepartment of Physical Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Walter P WodchisInstitute for Better Health, Trillium Health Partners, Mississauga, ON, Canada.
Lianne JeffsInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
Tujuanna AustinInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
Frances BrunoInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
Balpreet PanesarInstitute for Better Health, Trillium Health Partners, Mississauga, ON, Canada.
Élizabeth Côté BoileauDepartment of Health Management, Evaluation and Policy, School of Public Health, University of Montreal, Montreal, QC, Canada.
Robert J ReidInstitute for Better Health, Trillium Health Partners, Mississauga, ON, Canada.
Carolyn Steele GrayInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLearning Health Systems (LHS), in which continuous and equitable improvements support optimization of healthcare practices, outcomes, experience, and costs, offer enormous potential for health system transformation. Within the LHS model, evaluation of health innovations assists in question identification, data collection, and targeted action, which facilitates continuous improvement. Evaluation that catalyzes learning may contribute to health innovation implementation, refinement, and sustainability, however, there is little consensus as to why certain evaluations support learning, while others impede it.

methodsEmbedded in the implementation science literature, we conducted a realist synthesis to understand evaluative contextual factors and underlying mechanisms that best support health system learning and sustainable implementation of innovations. We sought to understand whether evaluations can 'work' to support learning and sustainability, in which contexts, for whom, and why. Working with an Expert Committee comprised of leaders in evaluation, innovation, sustainability, and realist methodology, we followed a five-stage process of: 1. Scoping the Review, 2. Building Theories, 3. Identifying the Evidence, 4. Evidence Selection and Appraisal, and 5. DATA EXTRACTION AND SYNTHESIS: Our Review Team and Expert Committee participated in iterative cycles of results interpretation and feedback.

resultsOur synthesis includes 60 articles capturing the mechanisms and contextual factors driving learning and sustainability through evaluation. We found that evaluations that support learning and sustainability incorporate favourable organizational preconditions and focus on implementing rapid cyclical feedback loops that contribute to a culture of innovation and evaluation sustainability. Our findings have been organized into 6 Context-Mechanism-Outcome Configurations (CMOCs): 1. Embracing Risk & Failure; 2. Increasing Capacity for Evaluation; 3. Co-Producing Evaluation; 4. Implementing Learning Feedback Loops; 5. Creating Sustainability Culture; and 6. Becoming a Learning Organization. We have also translated findings into a series of Action Strategies for evaluation implementation to support health systems learning and sustainability.

conclusionsWe identified key contextual factors and underlying mechanisms that make evaluations 'work' (or 'not work') to support learning and sustainability. Findings support the operationalization of LHS by translating CMOCs into Action Strategies for those tasked with completing evaluations with a view toward health system learning and innovation sustainability.

Indexed as

LearningLearning Health SystemProgram EvaluationHumansImplementation ScienceOrganizational InnovationQuality ImprovementEvaluationInnovationLearningLearning health systemsSustainability

Identifiers

PMID40361080
PMCPMC12070515

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LicenceCC BY
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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.