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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Optimising the use of electronic health records to estimate the incidence of rheumatoid arthritis in primary care: what information is hidden in free text?
|
|---|---|
| Published in |
BMC Medical Research Methodology, August 2013
|
| DOI | 10.1186/1471-2288-13-105 |
| Pubmed ID | |
| Authors |
Elizabeth Ford, Amanda Nicholson, Rob Koeling, A Rosemary Tate, John Carroll, Lesley Axelrod, Helen E Smith, Greta Rait, Kevin A Davies, Irene Petersen, Tim Williams, Jackie A Cassell |
| Abstract |
Primary care databases are a major source of data for epidemiological and health services research. However, most studies are based on coded information, ignoring information stored in free text. Using the early presentation of rheumatoid arthritis (RA) as an exemplar, our objective was to estimate the extent of data hidden within free text, using a keyword search. |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 31% |
| Chile | 2 | 15% |
| United States | 2 | 15% |
| Colombia | 1 | 8% |
| Argentina | 1 | 8% |
| Unknown | 3 | 23% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 62% |
| Practitioners (doctors, other healthcare professionals) | 4 | 31% |
| Scientists | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| Indonesia | 1 | 1% |
| Belgium | 1 | 1% |
| Unknown | 81 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 22% |
| Student > Ph. D. Student | 13 | 15% |
| Student > Master | 10 | 12% |
| Other | 6 | 7% |
| Professor > Associate Professor | 5 | 6% |
| Other | 13 | 15% |
| Unknown | 19 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 25 | 29% |
| Computer Science | 8 | 9% |
| Psychology | 4 | 5% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Mathematics | 3 | 4% |
| Other | 15 | 18% |
| Unknown | 27 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 April 2016.
All research outputs
#4,419,506
of 22,765,347 outputs
Outputs from BMC Medical Research Methodology
#705
of 2,010 outputs
Outputs of similar age
#38,797
of 198,902 outputs
Outputs of similar age from BMC Medical Research Methodology
#6
of 22 outputs
Altmetric has tracked 22,765,347 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,010 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 64% 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 198,902 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.