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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, June 2014
|
| DOI | 10.1186/1472-6947-14-55 |
| Pubmed ID | |
| Authors |
Nathan J Smischney, Venu M Velagapudi, James A Onigkeit, Brian W Pickering, Vitaly Herasevich, Rahul Kashyap |
| Abstract |
The development and validation of automated electronic medical record (EMR) search strategies are important for establishing the timing of mechanical ventilation initiation in the intensive care unit (ICU).Thus, we sought to develop and validate an automated EMR search algorithm (strategy) for time zero, the moment of mechanical ventilation initiation in the critically ill patient. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 8% |
| Spain | 1 | 3% |
| United Kingdom | 1 | 3% |
| Unknown | 33 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 24% |
| Student > Postgraduate | 4 | 11% |
| Student > Ph. D. Student | 3 | 8% |
| Student > Doctoral Student | 3 | 8% |
| Librarian | 2 | 5% |
| Other | 10 | 26% |
| Unknown | 7 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 42% |
| Agricultural and Biological Sciences | 3 | 8% |
| Engineering | 2 | 5% |
| Social Sciences | 2 | 5% |
| Psychology | 2 | 5% |
| Other | 4 | 11% |
| Unknown | 9 | 24% |
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 27 June 2014.
All research outputs
#17,722,431
of 22,757,541 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,498
of 1,985 outputs
Outputs of similar age
#155,477
of 227,908 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#27
of 31 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 21st percentile – i.e., 21% 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 227,908 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.