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Understanding effective care management implementation in primary care: a macrocognition perspective analysis

Overview of attention for article published in Implementation Science, August 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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12 X users
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1 Facebook page

Citations

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18 Dimensions

Readers on

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70 Mendeley
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1 CiteULike
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Title
Understanding effective care management implementation in primary care: a macrocognition perspective analysis
Published in
Implementation Science, August 2015
DOI 10.1186/s13012-015-0316-z
Pubmed ID
Authors

Jodi Summers Holtrop, Georges Potworowski, Laurie Fitzpatrick, Amy Kowalk, Lee A. Green

Abstract

Care management in primary care can be effective in helping patients with chronic disease improve their health status. Primary care practices, however, are often challenged with its implementation. Incorporating care management involves more than a simple physical process redesign to existing clinical care routines. It involves changes to who is working with patients, and consequently such things as who is making decisions, who is sharing patient information, and how. Studying the range of such changes in "knowledge work" during implementation requires a perspective and tools designed to do so. We used the macrocognition perspective, which is designed to understand how individuals think in dynamic, messy real-world environments such as care management implementation. To do so, we used cognitive task analysis to understand implementation in terms of such thinking as decision making, knowledge, and communication. Data collection involved semi-structured interviews and observations at baseline and at approximately 9 months into implementation at five practices in one physician-owned administratively connected group of practices in the state of Michigan, USA. Practices were intervention participants in a larger trial of chronic care model implementation. Data were transcribed, qualitatively coded and analyzed, initially using an editing approach and then a template approach with macrocognition as a guiding framework. Seventy-four interviews and five observations were completed. There were differences in implementation success across the practices, and these differences in implementation success were well explained by macrocognition. Practices that used more macrocognition functions and used them more often were also more successful in care management implementation. Although care management can introduce many new changes into the delivery of primary care clinical practice, implementing it successfully as a new complex intervention is possible. Macrocognition is a useful perspective for illuminating the elements that facilitate new complex interventions with a view to addressing them during implementation planning.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 1%
Unknown 69 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 17%
Student > Master 11 16%
Student > Ph. D. Student 8 11%
Student > Doctoral Student 7 10%
Other 6 9%
Other 10 14%
Unknown 16 23%
Readers by discipline Count As %
Medicine and Dentistry 17 24%
Nursing and Health Professions 10 14%
Engineering 6 9%
Social Sciences 4 6%
Computer Science 4 6%
Other 12 17%
Unknown 17 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 14 March 2016.
All research outputs
#3,683,270
of 22,824,164 outputs
Outputs from Implementation Science
#755
of 1,721 outputs
Outputs of similar age
#48,119
of 266,186 outputs
Outputs of similar age from Implementation Science
#19
of 52 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,721 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has gotten more attention than average, scoring higher than 56% 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 266,186 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 52 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.