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Can learning health systems help organisations deliver personalised care?

Overview of attention for article published in BMC Medicine, October 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

twitter
21 tweeters

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
74 Mendeley
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Title
Can learning health systems help organisations deliver personalised care?
Published in
BMC Medicine, October 2017
DOI 10.1186/s12916-017-0935-0
Pubmed ID
Authors

Bright I. Nwaru, Charles Friedman, John Halamka, Aziz Sheikh

Abstract

There is increasing international policy and clinical interest in developing learning health systems and delivering precision medicine, which it is hoped will help reduce variation in the quality and safety of care, improve efficiency, and lead to increasing the personalisation of healthcare. Although reliant on similar policies, informatics tools, and data science and implementation research capabilities, these two major initiatives have thus far largely progressed in parallel. In this opinion piece, we argue that they should be considered as complementary, synergistic initiatives whereby the creation of learning health systems infrastructure can support and catalyse the delivery of precision medicine that maximises the benefits and minimises the risks associated with treatments for individual patients. We illustrate this synergy by considering the example of treatments for asthma, which is now recognised as an umbrella term for a heterogeneous group of related conditions.

Twitter Demographics

The data shown below were collected from the profiles of 21 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 74 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 16%
Student > Master 12 16%
Researcher 10 14%
Professor 4 5%
Student > Postgraduate 3 4%
Other 14 19%
Unknown 19 26%
Readers by discipline Count As %
Medicine and Dentistry 18 24%
Nursing and Health Professions 6 8%
Computer Science 5 7%
Social Sciences 4 5%
Economics, Econometrics and Finance 3 4%
Other 13 18%
Unknown 25 34%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 January 2019.
All research outputs
#1,424,614
of 15,923,287 outputs
Outputs from BMC Medicine
#1,056
of 2,485 outputs
Outputs of similar age
#37,927
of 280,722 outputs
Outputs of similar age from BMC Medicine
#1
of 2 outputs
Altmetric has tracked 15,923,287 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,485 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.2. This one has gotten more attention than average, scoring higher than 57% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,722 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them