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Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks

Overview of attention for article published in BMC Health Services Research, May 2014
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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35 X users

Citations

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42 Mendeley
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Title
Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks
Published in
BMC Health Services Research, May 2014
DOI 10.1186/1472-6963-14-226
Pubmed ID
Authors

Enrico Coiera, Ying Wang, Farah Magrabi, Oscar Perez Concha, Blanca Gallego, William Runciman

Abstract

Current prognostic models factor in patient and disease specific variables but do not consider cumulative risks of hospitalization over time. We developed risk models of the likelihood of death associated with cumulative exposure to hospitalization, based on time-varying risks of hospitalization over any given day, as well as day of the week. Model performance was evaluated alone, and in combination with simple disease-specific models.

X Demographics

X Demographics

The data shown below were collected from the profiles of 35 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 21%
Other 6 14%
Student > Ph. D. Student 4 10%
Student > Master 4 10%
Student > Doctoral Student 3 7%
Other 8 19%
Unknown 8 19%
Readers by discipline Count As %
Medicine and Dentistry 14 33%
Computer Science 6 14%
Business, Management and Accounting 4 10%
Engineering 4 10%
Psychology 1 2%
Other 4 10%
Unknown 9 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 22 July 2014.
All research outputs
#1,679,489
of 25,247,212 outputs
Outputs from BMC Health Services Research
#563
of 8,572 outputs
Outputs of similar age
#16,362
of 232,889 outputs
Outputs of similar age from BMC Health Services Research
#8
of 115 outputs
Altmetric has tracked 25,247,212 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,572 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 93% 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 232,889 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.