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Mendeley readers
Attention Score in Context
| Title |
Prescription reporting with immediate medication utilization mapping (PRIMUM): development of an alert to improve narcotic prescribing
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, August 2016
|
| DOI | 10.1186/s12911-016-0352-x |
| Pubmed ID | |
| Authors |
Rachel B. Seymour, Daniel Leas, Meghan K. Wally, Joseph R. Hsu, the PRIMUM Group |
| Abstract |
Prescription narcotic overdoses and abuse have reached alarming numbers. To address this epidemic, integrated clinical decision support within the electronic medical record (EMR) to impact prescribing behavior was developed and tested. A multidisciplinary Expert Panel identified risk factors for misuse, abuse, or diversion of opioids or benzodiazepines through literature reviews and consensus building for inclusion in a rule within the EMR. We ran the rule "silently" to test the rule and collect baseline data. Five criteria were programmed to trigger the alert; based on data collected during a "silent" phase, thresholds for triggers were modified. The alert would have fired in 21.75 % of prescribing encounters (1.30 % of all encounters; n = 9998), suggesting the alert will have a low prescriber burden yet capture a significant number of at-risk patients. While the use of the EMR to provide clinical decision support is not new, utilizing it to develop and test an intervention is novel. We successfully built an alert system to address narcotic prescribing by providing critical, objective information at the point of care. The silent phase data were useful to appropriately tune the alert and obtain support for widespread implementation. Future healthcare initiatives can utilize similar methodology to collect data prospectively via the electronic medical record to inform the development, delivery, and evaluation of interventions. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Unknown | 56 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 14% |
| Student > Master | 7 | 12% |
| Student > Ph. D. Student | 7 | 12% |
| Other | 6 | 11% |
| Student > Doctoral Student | 5 | 9% |
| Other | 12 | 21% |
| Unknown | 12 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 22 | 39% |
| Psychology | 4 | 7% |
| Nursing and Health Professions | 3 | 5% |
| Social Sciences | 3 | 5% |
| Biochemistry, Genetics and Molecular Biology | 2 | 4% |
| Other | 11 | 19% |
| Unknown | 12 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 16 November 2018.
All research outputs
#13,241,926
of 22,883,326 outputs
Outputs from BMC Medical Informatics and Decision Making
#945
of 1,994 outputs
Outputs of similar age
#179,088
of 343,744 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#24
of 43 outputs
Altmetric has tracked 22,883,326 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,994 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 51% 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 343,744 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.