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Attention Score in Context
Title |
Predictive performance of comorbidity measures in administrative databases for diabetes cohorts
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Published in |
BMC Health Services Research, September 2013
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DOI | 10.1186/1472-6963-13-340 |
Pubmed ID | |
Authors |
Lisa M Lix, Jacqueline Quail, Opeyemi Fadahunsi, Gary F Teare |
Abstract |
The performance of comorbidity measures for predicting mortality in chronic disease populations and using ICD-9 diagnosis codes in administrative health data has been investigated in several studies, but less is known about predictive performance with ICD-10 data and for other health outcomes. This study investigated predictive performance of five comorbidity measures for population-based diabetes cohorts in administrative data. The objectives were to evaluate performance for: (a) disease-specific and general health outcomes, (b) data based on the ICD-9 and ICD-10 diagnoses, and (c) different age groups. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 2 | 2% |
Australia | 1 | 1% |
Spain | 1 | 1% |
Unknown | 83 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 13 | 15% |
Student > Ph. D. Student | 12 | 14% |
Student > Bachelor | 10 | 11% |
Student > Doctoral Student | 7 | 8% |
Student > Master | 7 | 8% |
Other | 17 | 20% |
Unknown | 21 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 36 | 41% |
Mathematics | 7 | 8% |
Social Sciences | 6 | 7% |
Nursing and Health Professions | 5 | 6% |
Psychology | 3 | 3% |
Other | 7 | 8% |
Unknown | 23 | 26% |
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 03 September 2013.
All research outputs
#18,345,822
of 22,719,618 outputs
Outputs from BMC Health Services Research
#6,444
of 7,600 outputs
Outputs of similar age
#147,816
of 198,166 outputs
Outputs of similar age from BMC Health Services Research
#90
of 107 outputs
Altmetric has tracked 22,719,618 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,600 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 7th percentile – i.e., 7% 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 198,166 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.