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Mendeley readers
Attention Score in Context
| Title |
Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
|
|---|---|
| Published in |
BMC Primary Care, October 2014
|
| DOI | 10.1186/s12875-014-0176-7 |
| Pubmed ID | |
| Authors |
C van den Dungen, N Hoeymans, M van den Akker, MCJ Biermans, K van Boven, JHK Joosten, RA Verheij, MWM de Waal, FG Schellevis, JAM van Oers |
| Abstract |
General practice based registration networks (GPRNs) provide information on population health derived from electronic health records (EHR). Morbidity estimates from different GPRNs reveal considerable, unexplained differences. Previous research showed that population characteristics could not explain this variation. In this study we investigate the influence of practice characteristics on the variation in incidence and prevalence figures between general practices and between GPRNs. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 22% |
| Researcher | 6 | 22% |
| Student > Postgraduate | 4 | 15% |
| Student > Ph. D. Student | 3 | 11% |
| Professor | 3 | 11% |
| Other | 1 | 4% |
| Unknown | 4 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 33% |
| Nursing and Health Professions | 6 | 22% |
| Social Sciences | 4 | 15% |
| Computer Science | 2 | 7% |
| Engineering | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 5 | 19% |
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 01 November 2014.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from BMC Primary Care
#2,212
of 2,359 outputs
Outputs of similar age
#233,965
of 274,413 outputs
Outputs of similar age from BMC Primary Care
#36
of 39 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,359 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 1st percentile – i.e., 1% 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 274,413 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.