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Learning Health Systems
Article . 2022 . Peer-reviewed
License: CC BY NC ND
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Learning Health Systems
Article . 2023
Data sources: DOAJ
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Learning health system, positive deviance analysis, and electronic health records: Synergy for a learning health system

Authors: Azar, Kristen; Greene, Sarah; Pletcher, Mark; Pressman, Alice;

Learning health system, positive deviance analysis, and electronic health records: Synergy for a learning health system

Abstract

AbstractIntroductionOver the past decade, numerous efforts have encouraged the realization of the learning health system (LHS) in the United States. Despite these efforts, and promising aims of the LHS, the full potential and value of research conducted within LHSs have yet to be realized. New technology coupled with a catalyzing global pandemic have spurred momentum. In addition, the LHS has lacked a consistent framework within which “best evidence” can be identified. Positive deviance analysis, itself reinvigorated by recent advances in health information technology (IT) and ubiquitous adoption of electronic health records (EHRs), may finally provide a framework through which LHSs can be operationalized and optimized.MethodsWe describe the synergy between positive deviance and the LHS and how they may be integrated to achieve a continuous cycle of health system improvement.ResultsAs we describe below, the positive deviance approach focuses on learning from high‐performing teams and organizations.ConclusionSuch learning can be enabled by EHRs and health IT, providing a lens into how digital clinical interventions are successfully developed and deployed.

Country
United States
Keywords

Medicine (General), 330, comparative effectiveness, 610, quality improvement, positive deviance, R5-920, learning health system, Commentaries, Public aspects of medicine, RA1-1270

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    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
gold