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Learning Health Systems
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Learning Health Systems
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Article . 2020
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Learning Health Systems
Article . 2020
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From Learning Healthcare Systems to Learning Health Systems

Authors: Aziz Sheikh;

From Learning Healthcare Systems to Learning Health Systems

Abstract

There is growing national and international interest in creating learning healthcare systems; this drive is stimulated by the (then) Institute of Medicine's (now National Academy of Medicine) 2007 seminal report on the Learning Healthcare System.1 In this report, the Institute of Medicine urged for the creation of a model of care “…that is designed to generate and apply the best evidence for the collaborative healthcare choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care; and to ensure innovation, quality, safety, and value in healthcare.” Over the ensuing 12 years, this bold idea has catalyzed considerable scientific, clinical, and policy interest in finding ways to converge the processes of knowledge generation and practice improvement and through doing so, simultaneously improving healthcare delivery and personalization of care2 whilst also containing healthcare expenditure.3 Whilst this expanding interest is welcome in many respects, I believe the emphasis on Learning Healthcare Systems is misplaced. My contention is that we need to focus on the creation of Learning Health Systems. There are two key reasons why I believe we need to shift our focus, which I summarize below.

Country
United Kingdom
Related Organizations
Keywords

Medicine (General), R5-920, Commentary, health policy, data science, Public aspects of medicine, RA1-1270, population health

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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!
7
Top 10%
Average
Top 10%
Green
gold