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Using an electronic medical record (EMR) to conduct clinical trials: Salford Lung Study feasibility

Overview of attention for article published in BMC Medical Informatics and Decision Making, February 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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Citations

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33 Dimensions

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131 Mendeley
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Title
Using an electronic medical record (EMR) to conduct clinical trials: Salford Lung Study feasibility
Published in
BMC Medical Informatics and Decision Making, February 2015
DOI 10.1186/s12911-015-0132-z
Pubmed ID
Authors

Hanaa F Elkhenini, Kourtney J Davis, Norman D Stein, John P New, Mark R Delderfield, Martin Gibson, Jorgen Vestbo, Ashley Woodcock, Nawar Diar Bakerly

Abstract

Real-world data on the benefit/risk profile of medicines is needed, particularly in patients who are ineligible for randomised controlled trials conducted for registration purposes. This paper describes the methodology and source data verification which enables the conduct of pre-licensing clinical trials of COPD and asthma in the community using the electronic medical record (EMR), NorthWest EHealth linked database (NWEH-LDB) and alert systems.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 2%
Australia 1 <1%
Unknown 127 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 14%
Student > Ph. D. Student 16 12%
Student > Master 12 9%
Student > Bachelor 12 9%
Student > Doctoral Student 11 8%
Other 30 23%
Unknown 32 24%
Readers by discipline Count As %
Medicine and Dentistry 47 36%
Nursing and Health Professions 13 10%
Computer Science 8 6%
Agricultural and Biological Sciences 4 3%
Biochemistry, Genetics and Molecular Biology 3 2%
Other 18 14%
Unknown 38 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 10 April 2016.
All research outputs
#6,740,312
of 25,382,035 outputs
Outputs from BMC Medical Informatics and Decision Making
#588
of 2,139 outputs
Outputs of similar age
#82,660
of 358,231 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#8
of 24 outputs
Altmetric has tracked 25,382,035 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 2,139 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. 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 358,231 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 76% of its contemporaries.
We're also able to compare this research output to 24 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 70% of its contemporaries.