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Ascertainment of chronic diseases using population health data: a comparison of health administrative data and patient self-report

Overview of attention for article published in BMC Public Health, January 2013
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
141 Dimensions

Readers on

mendeley
136 Mendeley
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Title
Ascertainment of chronic diseases using population health data: a comparison of health administrative data and patient self-report
Published in
BMC Public Health, January 2013
DOI 10.1186/1471-2458-13-16
Pubmed ID
Authors

Elizabeth Muggah, Erin Graves, Carol Bennett, Douglas G Manuel

Abstract

Health administrative data is increasingly being used for chronic disease surveillance. This study explored agreement between administrative and survey data for ascertainment of seven key chronic diseases, using individually linked data from a large population of individuals in Ontario, Canada.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 3 2%
Netherlands 1 <1%
Portugal 1 <1%
France 1 <1%
United States 1 <1%
Unknown 129 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 29 21%
Researcher 20 15%
Student > Ph. D. Student 18 13%
Student > Doctoral Student 17 13%
Student > Bachelor 12 9%
Other 26 19%
Unknown 14 10%
Readers by discipline Count As %
Medicine and Dentistry 53 39%
Social Sciences 13 10%
Nursing and Health Professions 11 8%
Agricultural and Biological Sciences 8 6%
Neuroscience 5 4%
Other 22 16%
Unknown 24 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 January 2013.
All research outputs
#13,070,986
of 21,342,999 outputs
Outputs from BMC Public Health
#9,440
of 13,833 outputs
Outputs of similar age
#166,483
of 292,960 outputs
Outputs of similar age from BMC Public Health
#662
of 1,043 outputs
Altmetric has tracked 21,342,999 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,833 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.7. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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 292,960 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,043 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.