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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Approaches to ascertaining comorbidity information: validation of routine hospital episode data with clinician-based case note review
|
|---|---|
| Published in |
BMC Research Notes, April 2014
|
| DOI | 10.1186/1756-0500-7-253 |
| Pubmed ID | |
| Authors |
Martin Soo, Lynn M Robertson, Tariq Ali, Laura E Clark, Nicholas Fluck, Marjorie Johnston, Angharad Marks, Gordon J Prescott, William Cairns S Smith, Corri Black |
| Abstract |
In clinical practice, research, and increasingly health surveillance, planning and costing, there is a need for high quality information to determine comorbidity information about patients. Electronic, routinely collected healthcare data is capturing increasing amounts of clinical information as part of routine care. The aim of this study was to assess the validity of routine hospital administrative data to determine comorbidity, as compared with clinician-based case note review, in a large cohort of patients with chronic kidney disease. |
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 % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| United States | 1 | 2% |
| Unknown | 56 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 20% |
| Student > Ph. D. Student | 10 | 17% |
| Researcher | 7 | 12% |
| Other | 5 | 8% |
| Student > Bachelor | 4 | 7% |
| Other | 10 | 17% |
| Unknown | 11 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 24 | 41% |
| Social Sciences | 5 | 8% |
| Mathematics | 2 | 3% |
| Psychology | 2 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 5 | 8% |
| Unknown | 20 | 34% |
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 25 April 2014.
All research outputs
#18,371,293
of 22,754,104 outputs
Outputs from BMC Research Notes
#3,015
of 4,262 outputs
Outputs of similar age
#163,980
of 226,772 outputs
Outputs of similar age from BMC Research Notes
#57
of 82 outputs
Altmetric has tracked 22,754,104 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 4,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 16th percentile – i.e., 16% 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 226,772 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.