ArticleLearning health systems2022
From "Invented here" to "Use it everywhere!": A Learning health system from bottom and/or top?
Article in Learning health systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Exploring innovation landscapes: a national cross-sectional study of Swedish primary care from the viewpoint of primary care managers.BMC health services research · 2026Article
- Evaluating health organization readiness for implementing a learning health system: a scoping review.Health research policy and systems · 2025Article
- Tools and frameworks for evaluating the implementation of learning health systems: a scoping review.Health research policy and systems · 2024Article
- International perspectives on measuring national digital public health system maturity through a multidisciplinary Delphi study.NPJ digital medicine · 2024Article
- From "Invented here" to "Use it everywhere!": A Learning health system from bottom and/or top?Learning health systems · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Departing from a practical problem of how to use digitalization to improve care quality and efficiency, this paper investigates how the concept of Learning Health Systems (LHSs) can be applied to an existing organization. LHSs offer a vision for how healthcare can accelerate both scale-up of innovations and quality improvements at all levels. However, aligning stakeholders at different levels to convergent development is challenging and translation and adaptation of the LHS concept to fit with the existing organization is essential. Methods: A one-year longitudinal action research (AR) study was conducted within five psychiatric departments at the Sahlgrenska University Hospital in Gothenburg, Sweden. Translation of the LHS concept to the local circumstances within the organization was set as the aim, to both improve practice and further scientific understanding. An AR group led the practical and scholarly work and holistic data were collected, including field notes, documents, recordings, and workshops. Data were analyzed by an insider-outsider approach. Results: The one-year study is described to provide insights into the process of designing a locally adapted LHS using an AR approach. Practical needs were identified and iteratively matched with theory to form a local LHS model. A conflict between top-down and bottom-up views on development emerged, where higher-level management tended to prioritize uniform solutions and developers local learning. An adapted solution to balance these approaches was negotiated, consisting of a technical and an organizational part. Conclusions: The conflict between top-down and bottom-up approaches for how to implement LHSs needs to be considered both in practical work to transform care organizations and in scientific studies of LHSs. The approach to translate, rather than instrumentally implement, LHSs to real-world settings is suggested as advantageous. Furthermore, designing such endeavors as AR projects can provide excellent conditions to create LHSs that work in practice.
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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.