| Title |
Hospital Readmission in General Medicine Patients: A Prediction Model
|
|---|---|
| Published in |
Journal of General Internal Medicine, December 2009
|
| DOI | 10.1007/s11606-009-1196-1 |
| Pubmed ID | |
| Authors |
Omar Hasan, David O. Meltzer, Shimon A. Shaykevich, Chaim M. Bell, Peter J. Kaboli, Andrew D. Auerbach, Tosha B. Wetterneck, Vineet M. Arora, James Zhang, Jeffrey L. Schnipper |
Mendeley readers
The data shown below were compiled from readership statistics for 346 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 13 | 4% |
| Spain | 4 | 1% |
| United Kingdom | 3 | <1% |
| India | 2 | <1% |
| Japan | 2 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Switzerland | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 319 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 51 | 15% |
| Student > Ph. D. Student | 50 | 14% |
| Student > Master | 48 | 14% |
| Other | 25 | 7% |
| Student > Postgraduate | 24 | 7% |
| Other | 83 | 24% |
| Unknown | 65 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 114 | 33% |
| Nursing and Health Professions | 36 | 10% |
| Computer Science | 30 | 9% |
| Engineering | 20 | 6% |
| Business, Management and Accounting | 15 | 4% |
| Other | 46 | 13% |
| Unknown | 85 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 10 February 2021.
All research outputs
#1,478,732
of 23,911,072 outputs
Outputs from Journal of General Internal Medicine
#1,190
of 7,806 outputs
Outputs of similar age
#6,351
of 169,844 outputs
Outputs of similar age from Journal of General Internal Medicine
#3
of 39 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,806 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.8. This one has done well, scoring higher than 84% 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 169,844 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 96% of its contemporaries.
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 has done particularly well, scoring higher than 92% of its contemporaries.