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The use of administrative health care databases to identify patients with rheumatoid arthritis

Overview of attention for article published in Open Access Rheumatology : Research and Reviews , November 2015
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19 Mendeley
Title
The use of administrative health care databases to identify patients with rheumatoid arthritis
Published in
Open Access Rheumatology : Research and Reviews , November 2015
DOI 10.2147/oarrr.s92630
Pubmed ID
Authors

John G Hanly, Kara Thompson, Chris Skedgel

Abstract

To validate and compare the decision rules to identify rheumatoid arthritis (RA) in administrative databases. A study was performed using administrative health care data from a population of 1 million people who had access to universal health care. Information was available on hospital discharge abstracts and physician billings. RA cases in health administrative databases were matched 1:4 by age and sex to randomly selected controls without inflammatory arthritis. Seven case definitions were applied to identify RA cases in the health administrative data, and their performance was compared with the diagnosis by a rheumatologist. The validation study was conducted on a sample of individuals with administrative data who received a rheumatologist consultation at the Arthritis Center of Nova Scotia. We identified 535 RA cases and 2,140 non-RA, noninflammatory arthritis controls. Using the rheumatologist's diagnosis as the gold standard, the overall accuracy of the case definitions for RA cases varied between 68.9% and 82.9% with a kappa statistic between 0.26 and 0.53. The sensitivity and specificity varied from 20.7% to 94.8% and 62.5% to 98.5%, respectively. In a reference population of 1 million, the estimated annual number of incident cases of RA was between 176 and 1,610 and the annual number of prevalent cases was between 1,384 and 5,722. The accuracy of case definitions for the identification of RA cases from rheumatology clinics using administrative health care databases is variable when compared to a rheumatologist's assessment. This should be considered when comparing results across studies. This variability may also be used as an advantage in different study designs, depending on the relative importance of sensitivity and specificity for identifying the population of interest to the research question.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 37%
Student > Master 4 21%
Librarian 2 11%
Student > Ph. D. Student 2 11%
Student > Doctoral Student 1 5%
Other 2 11%
Unknown 1 5%
Readers by discipline Count As %
Medicine and Dentistry 6 32%
Nursing and Health Professions 4 21%
Mathematics 2 11%
Biochemistry, Genetics and Molecular Biology 1 5%
Business, Management and Accounting 1 5%
Other 2 11%
Unknown 3 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 November 2015.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from Open Access Rheumatology : Research and Reviews
#126
of 192 outputs
Outputs of similar age
#176,405
of 294,811 outputs
Outputs of similar age from Open Access Rheumatology : Research and Reviews
#1
of 1 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 192 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 26th percentile – i.e., 26% 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 294,811 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them