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Applying a Health Network approach to translate evidence-informed policy into practice: A review and case study on musculoskeletal health

Overview of attention for article published in BMC Health Services Research, November 2012
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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 (81st percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
11 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
113 Mendeley
citeulike
1 CiteULike
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Title
Applying a Health Network approach to translate evidence-informed policy into practice: A review and case study on musculoskeletal health
Published in
BMC Health Services Research, November 2012
DOI 10.1186/1472-6963-12-394
Pubmed ID
Authors

Andrew M Briggs, Peter Bragge, Helen Slater, Madelynn Chan, Simon CB Towler

Abstract

While translation of evidence into health policy and practice is recognised as critical to optimising health system performance and health-related outcomes for consumers, mechanisms to effectively achieve these goals are neither well understood, nor widely communicated. Health Networks represent a framework which offers a possible solution to this dilemma, particularly in light of emerging evidence regarding the importance of establishing relationships between stakeholders and identifying clinical leaders to drive evidence integration and translation into policy. This is particularly important for service delivery related to chronic diseases. In Western Australia (WA), disease and population-specific Health Networks are comprised of cross-discipline stakeholders who work collaboratively to develop evidence-informed policies and drive their implementation. Since establishment of the Health Networks in WA, over 50 evidence-informed Models of Care (MoCs) have been produced across 18 condition or population-focused Networks. The aim of this paper is to provide an overview of the Health Network framework in facilitating the translation of evidence into policy and practice with a particular focus on musculoskeletal health.

Twitter Demographics

The data shown below were collected from the profiles of 11 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 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
United States 1 <1%
Canada 1 <1%
Unknown 109 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 21%
Student > Ph. D. Student 17 15%
Student > Master 14 12%
Librarian 8 7%
Student > Doctoral Student 7 6%
Other 26 23%
Unknown 17 15%
Readers by discipline Count As %
Medicine and Dentistry 33 29%
Nursing and Health Professions 18 16%
Social Sciences 15 13%
Economics, Econometrics and Finance 6 5%
Business, Management and Accounting 4 4%
Other 16 14%
Unknown 21 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 29 November 2012.
All research outputs
#4,237,369
of 21,796,013 outputs
Outputs from BMC Health Services Research
#1,986
of 7,256 outputs
Outputs of similar age
#32,318
of 175,590 outputs
Outputs of similar age from BMC Health Services Research
#66
of 381 outputs
Altmetric has tracked 21,796,013 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,256 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has gotten more attention than average, scoring higher than 72% 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 175,590 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 81% of its contemporaries.
We're also able to compare this research output to 381 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.