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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record data
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, February 2013
|
| DOI | 10.1186/1472-6947-13-28 |
| Pubmed ID | |
| Authors |
Carlos A Alvarez, Christopher A Clark, Song Zhang, Ethan A Halm, John J Shannon, Carlos E Girod, Lauren Cooper, Ruben Amarasingham |
| Abstract |
Accurate, timely and automated identification of patients at high risk for severe clinical deterioration using readily available clinical information in the electronic medical record (EMR) could inform health systems to target scarce resources and save lives. |
X Demographics
The data shown below were collected from the profiles of 4 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 States | 2 | 50% |
| Spain | 1 | 25% |
| India | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Practitioners (doctors, other healthcare professionals) | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 179 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 2% |
| Canada | 2 | 1% |
| Denmark | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 172 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 36 | 20% |
| Researcher | 27 | 15% |
| Student > Bachelor | 21 | 12% |
| Other | 16 | 9% |
| Student > Master | 15 | 8% |
| Other | 36 | 20% |
| Unknown | 28 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 72 | 40% |
| Nursing and Health Professions | 14 | 8% |
| Computer Science | 14 | 8% |
| Engineering | 9 | 5% |
| Business, Management and Accounting | 6 | 3% |
| Other | 30 | 17% |
| Unknown | 34 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 June 2018.
All research outputs
#1,726,849
of 22,699,621 outputs
Outputs from BMC Medical Informatics and Decision Making
#88
of 1,980 outputs
Outputs of similar age
#14,528
of 192,966 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#4
of 40 outputs
Altmetric has tracked 22,699,621 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,980 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 95% 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 192,966 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.