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Comparison of the International Crowding Measure in Emergency Departments (ICMED) and the National Emergency Department Overcrowding Score (NEDOCS) to measure emergency department crowding: pilot…

Overview of attention for article published in Emergency Medicine Journal, January 2016
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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 (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

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20 tweeters
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1 Facebook page

Citations

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14 Dimensions

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47 Mendeley
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Title
Comparison of the International Crowding Measure in Emergency Departments (ICMED) and the National Emergency Department Overcrowding Score (NEDOCS) to measure emergency department crowding: pilot study
Published in
Emergency Medicine Journal, January 2016
DOI 10.1136/emermed-2014-203616
Pubmed ID
Authors

Adrian Boyle, Gary Abel, Pramin Raut, Richard Austin, Vijayasankar Dhakshinamoorthy, Ravi Ayyamuthu, Iona Murdoch, Joel Burton

Abstract

There is uncertainty about the best way to measure emergency department crowding. We have previously developed a consensus-based measure of crowding, the International Crowding Measure in Emergency Departments (ICMED). We aimed to obtain pilot data to evaluate the ability of a shortened form of the ICMED, the sICMED, to predict senior emergency department clinicians' concerns about crowding and danger compared with a very well-studied measure of emergency department crowding, the National Emergency Department Overcrowding Score (NEDOCS). We collected real-time observations of the sICMED and NEDOCS and compared these with clinicians' perceptions of crowding and danger on a visual analogue scale. Data were collected in four emergency departments in the East of England. Associations were explored using simple regression, random intercept models and models accounting for correlation between adjacent time points. We conducted 82 h of observation in 10 observation sets. Naive modelling suggested strong associations between sICMED and NEDOCS and clinician perceptions of crowding and danger. Further modelling showed that, due to clustering, the association between sICMED and danger persisted, but the association between these two measures and perception of crowding was no longer statistically significant. Both sICMED and NEDOCS can be collected easily in a variety of English hospitals. Further studies are required but initial results suggest both scores may have potential use for assessing crowding variation at long timescales, but are less sensitive to hour-by-hour variation. Correlation in time is an important methodological consideration which, if ignored, may lead to erroneous conclusions. Future studies should account for such correlation in both design and analysis.

Twitter Demographics

The data shown below were collected from the profiles of 20 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Brazil 1 2%
Unknown 45 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 32%
Researcher 14 30%
Student > Postgraduate 5 11%
Unspecified 3 6%
Other 3 6%
Other 7 15%
Readers by discipline Count As %
Medicine and Dentistry 27 57%
Nursing and Health Professions 9 19%
Unspecified 5 11%
Psychology 1 2%
Economics, Econometrics and Finance 1 2%
Other 4 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 19 October 2018.
All research outputs
#1,410,439
of 13,901,766 outputs
Outputs from Emergency Medicine Journal
#736
of 3,358 outputs
Outputs of similar age
#42,584
of 363,798 outputs
Outputs of similar age from Emergency Medicine Journal
#24
of 95 outputs
Altmetric has tracked 13,901,766 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,358 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has done well, scoring higher than 78% 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 363,798 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 88% of its contemporaries.
We're also able to compare this research output to 95 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 74% of its contemporaries.