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Healthcare Worker Contact Networks and the Prevention of Hospital-Acquired Infections

Overview of attention for article published in PLOS ONE, December 2013
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
2 X users
facebook
1 Facebook page
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1 research highlight platform

Readers on

mendeley
106 Mendeley
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Article details
Title
Healthcare Worker Contact Networks and the Prevention of Hospital-Acquired Infections
Published in
PLOS ONE, December 2013
DOI 10.1371/journal.pone.0079906
Pubmed ID
Authors
Abstract

We present a comprehensive approach to using electronic medical records (EMR) for constructing contact networks of healthcare workers in a hospital. This approach is applied at the University of Iowa Hospitals and Clinics (UIHC)--a 3.2 million square foot facility with 700 beds and about 8,000 healthcare workers--by obtaining 19.8 million EMR data points, spread over more than 21 months. We use these data to construct 9,000 different healthcare worker contact networks, which serve as proxies for patterns of actual healthcare worker contacts. Unlike earlier approaches, our methods are based on large-scale data and do not make any a priori assumptions about edges (contacts) between healthcare workers, degree distributions of healthcare workers, their assignment to wards, etc. Preliminary validation using data gathered from a 10-day long deployment of a wireless sensor network in the Medical Intensive Care Unit suggests that EMR logins can serve as realistic proxies for hospital-wide healthcare worker movement and contact patterns. Despite spatial and job-related constraints on healthcare worker movement and interactions, analysis reveals a strong structural similarity between the healthcare worker contact networks we generate and social networks that arise in other (e.g., online) settings. Furthermore, our analysis shows that disease can spread much more rapidly within the constructed contact networks as compared to random networks of similar size and density. Using the generated contact networks, we evaluate several alternate vaccination policies and conclude that a simple policy that vaccinates the most mobile healthcare workers first, is robust and quite effective relative to a random vaccination policy.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 3 3%
United Kingdom 1 <1%
Spain 1 <1%
Denmark 1 <1%
Unknown 100 94%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 19 18%
Researcher 17 16%
Student > Master 12 11%
Student > Bachelor 8 8%
Other 7 7%
Other 21 20%
Unknown 22 21%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 31 29%
Computer Science 9 8%
Nursing and Health Professions 7 7%
Engineering 7 7%
Mathematics 7 7%
Other 20 19%
Unknown 25 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 28 March 2023.
All research outputs
#3,605,299
of 34,358,242 outputs
Outputs from PLOS ONE
#37,908
of 224,513 outputs
Outputs of similar age
#35,046
of 373,346 outputs
Outputs of similar age from PLOS ONE
#996
of 5,917 outputs
Altmetric has tracked 34,358,242 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 224,513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one has done well, scoring higher than 82% 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 373,346 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 90% of its contemporaries.
We're also able to compare this research output to 5,917 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.