| Title |
Evaluating Electronic Referrals for Specialty Care at a Public Hospital
|
|---|---|
| Published in |
Journal of General Internal Medicine, May 2010
|
| DOI | 10.1007/s11606-010-1402-1 |
| Pubmed ID | |
| Authors |
Judy E. Kim-Hwang, Alice Hm Chen, Douglas S. Bell, David Guzman, Hal F. Yee, Margot B. Kushel |
| Abstract |
Poor communication between referring clinicians and specialists may lead to inefficient use of specialist services. San Francisco General Hospital implemented an electronic referral system (eReferral) that facilitates iterative pre-visit communication between referring and specialty clinicians to improve the referral process. |
Mendeley readers
The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| Canada | 2 | 2% |
| Australia | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Netherlands | 1 | <1% |
| Unknown | 123 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 26 | 20% |
| Researcher | 23 | 18% |
| Student > Ph. D. Student | 11 | 8% |
| Student > Doctoral Student | 10 | 8% |
| Student > Bachelor | 10 | 8% |
| Other | 27 | 21% |
| Unknown | 24 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 51 | 39% |
| Computer Science | 11 | 8% |
| Nursing and Health Professions | 11 | 8% |
| Engineering | 7 | 5% |
| Business, Management and Accounting | 6 | 5% |
| Other | 16 | 12% |
| Unknown | 29 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 25. 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 15 January 2021.
All research outputs
#1,376,817
of 23,911,072 outputs
Outputs from Journal of General Internal Medicine
#1,117
of 7,806 outputs
Outputs of similar age
#4,378
of 98,527 outputs
Outputs of similar age from Journal of General Internal Medicine
#9
of 40 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 94th 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 85% 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 98,527 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 95% 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 well, scoring higher than 75% of its contemporaries.