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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
“Reducing unnecessary testing in a CPOE system through implementation of a targeted CDS intervention”
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, April 2013
|
| DOI | 10.1186/1472-6947-13-43 |
| Pubmed ID | |
| Authors |
Donald L Levick, Glenn Stern, Chad D Meyerhoefer, Aaron Levick, David Pucklavage |
| Abstract |
We describe and evaluate the development and use of a Clinical Decision Support (CDS) intervention; an alert, in response to an identified medical error of overuse of a diagnostic laboratory test in a Computerized Physician Order Entry (CPOE) system. CPOE with embedded CDS has been shown to improve quality of care and reduce medical errors. CPOE can also improve resource utilization through more appropriate use of laboratory tests and diagnostic studies. Observational studies are necessary in order to understand how these technologies can be successfully employed by healthcare providers. |
Twitter Demographics
The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 3% |
| Mexico | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 100 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 23 | 22% |
| Other | 15 | 14% |
| Researcher | 15 | 14% |
| Student > Ph. D. Student | 11 | 10% |
| Student > Bachelor | 8 | 8% |
| Other | 20 | 19% |
| Unknown | 13 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 40 | 38% |
| Nursing and Health Professions | 11 | 10% |
| Computer Science | 9 | 9% |
| Social Sciences | 8 | 8% |
| Business, Management and Accounting | 4 | 4% |
| Other | 17 | 16% |
| Unknown | 16 | 15% |
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 28 November 2013.
All research outputs
#15,268,549
of 22,705,019 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,306
of 1,981 outputs
Outputs of similar age
#124,548
of 199,277 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#30
of 37 outputs
Altmetric has tracked 22,705,019 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,981 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 199,277 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.