| Title |
Electronic health record design and implementation for pharmacogenomics: a local perspective
|
|---|---|
| Published in |
Genetics in Medicine, September 2013
|
| DOI | 10.1038/gim.2013.109 |
| Pubmed ID | |
| Authors |
Josh F. Peterson, Erica Bowton, Julie R. Field, Marc Beller, Jennifer Mitchell, Jonathan Schildcrout, William Gregg, Kevin Johnson, Jim N. Jirjis, Dan M. Roden, Jill M. Pulley, Josh C. Denny |
| Abstract |
The design of electronic health records to translate genomic medicine into clinical care is crucial to successful introduction of new genomic services, yet there are few published guides to implementation. |
X Demographics
The data shown below were collected from the profiles of 12 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 | 8 | 67% |
| Korea, Republic of | 1 | 8% |
| Argentina | 1 | 8% |
| Unknown | 2 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 50% |
| Scientists | 4 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
| Practitioners (doctors, other healthcare professionals) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 4% |
| United Kingdom | 3 | 2% |
| Korea, Republic of | 1 | <1% |
| Unknown | 115 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 24 | 19% |
| Student > Ph. D. Student | 23 | 19% |
| Other | 12 | 10% |
| Student > Master | 11 | 9% |
| Student > Doctoral Student | 9 | 7% |
| Other | 26 | 21% |
| Unknown | 19 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 31 | 25% |
| Computer Science | 17 | 14% |
| Agricultural and Biological Sciences | 11 | 9% |
| Biochemistry, Genetics and Molecular Biology | 10 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 9 | 7% |
| Other | 21 | 17% |
| Unknown | 25 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 42. 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 30 March 2015.
All research outputs
#981,700
of 25,371,288 outputs
Outputs from Genetics in Medicine
#288
of 2,943 outputs
Outputs of similar age
#8,347
of 209,062 outputs
Outputs of similar age from Genetics in Medicine
#8
of 42 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,943 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.0. This one has done particularly well, scoring higher than 90% 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 209,062 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 42 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.