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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Physicians’ Perspectives Regarding Prescription Drug Monitoring Program Use Within the Department of Veterans Affairs: a Multi-State Qualitative Study
|
|---|---|
| Published in |
Journal of General Internal Medicine, March 2018
|
| DOI | 10.1007/s11606-018-4374-1 |
| Pubmed ID | |
| Authors |
Thomas R. Radomski, Felicia R. Bixler, Susan L. Zickmund, KatieLynn M. Roman, Carolyn T. Thorpe, Jennifer A. Hale, Florentina E. Sileanu, Leslie R. M. Hausmann, Joshua M. Thorpe, Katie J. Suda, Kevin T. Stroupe, Adam J. Gordon, Chester B. Good, Michael J. Fine, Walid F. Gellad |
| Abstract |
The Department of Veterans Affairs (VA) has implemented robust strategies to monitor prescription opioid dispensing, but these strategies have not accounted for opioids prescribed by non-VA providers. State-based prescription drug monitoring programs (PDMPs) are a potential tool to identify VA patients' receipt of opioids from non-VA prescribers, and recent legislation requires their use within VA. To evaluate VA physicians' perspectives and experiences regarding use of PDMPs to monitor Veterans' receipt of opioids from non-VA prescribers. Qualitative study using semi-structured interviews. Forty-two VA primary care physicians who prescribed opioids to 15 or more Veterans in 2015. We sampled physicians from two states with PDMPs (Massachusetts and Illinois) and one without prescriber access to a PDMP at the time of the interviews (Pennsylvania). From February to August 2016, we conducted semi-structured telephone interviews that addressed the following topics regarding PDMPs: overall experiences, barriers to optimal use, and facilitators to improve use. VA physicians broadly supported use of PDMPs or desired access to one, while exhibiting varying patterns of PDMP use dictated by state laws and their clinical judgment. Physicians noted administrative burdens and incomplete or unavailable prescribing data as key barriers to PDMP use. To facilitate use, physicians endorsed (1) linking PDMPs with the VA electronic health record, (2) using templated notes to document PDMP use, and (3) delegating routine PDMP queries to ancillary staff. Despite the time and administrative burdens associated with their use, VA physicians in our study broadly supported PDMPs. The application of our findings to ongoing PDMP implementation efforts may strengthen PDMP use both within and outside VA and improve the safe prescribing of opioids. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 55 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 20% |
| Researcher | 8 | 15% |
| Other | 6 | 11% |
| Student > Ph. D. Student | 6 | 11% |
| Student > Doctoral Student | 3 | 5% |
| Other | 5 | 9% |
| Unknown | 16 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 25% |
| Nursing and Health Professions | 6 | 11% |
| Social Sciences | 6 | 11% |
| Psychology | 3 | 5% |
| Biochemistry, Genetics and Molecular Biology | 2 | 4% |
| Other | 5 | 9% |
| Unknown | 19 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 26 April 2018.
All research outputs
#19,440,618
of 23,911,072 outputs
Outputs from Journal of General Internal Medicine
#6,622
of 7,806 outputs
Outputs of similar age
#263,012
of 335,842 outputs
Outputs of similar age from Journal of General Internal Medicine
#110
of 146 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
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 is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 335,842 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.