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Impact of prescription drug monitoring programs and pill mill laws on high-risk opioid prescribers: A comparative interrupted time series analysis

Overview of attention for article published in Drug & Alcohol Dependence, August 2016
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216

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
26 news outlets
blogs
3 blogs
policy
2 policy sources
twitter
14 tweeters
facebook
3 Facebook pages

Citations

dimensions_citation
80 Dimensions

Readers on

mendeley
132 Mendeley
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Title
Impact of prescription drug monitoring programs and pill mill laws on high-risk opioid prescribers: A comparative interrupted time series analysis
Published in
Drug & Alcohol Dependence, August 2016
DOI 10.1016/j.drugalcdep.2016.04.033
Pubmed ID
Authors

Hsien-Yen Chang, Tatyana Lyapustina, Lainie Rutkow, Matthew Daubresse, Matt Richey, Mark Faul, Elizabeth A. Stuart, G. Caleb Alexander

Abstract

Prescription drug monitoring programs (PDMPs) and pill mill laws were implemented to reduce opioid-related injuries/deaths. We evaluated their effects on high-risk prescribers in Florida. We used IMS Health's LRx Lifelink database between July 2010 and September 2012 to identify opioid-prescribing prescribers in Florida (intervention state, N: 38,465) and Georgia (control state, N: 18,566). The pre-intervention, intervention, and post-intervention periods were: July 2010-June 2011, July 2011-September 2011, and October 2011-September 2012. High-risk prescribers were those in the top 5th percentile of opioid volume during four consecutive calendar quarters. We applied comparative interrupted time series models to evaluate policy effects on clinical practices and monthly prescribing measures for low-risk/high-risk prescribers. We identified 1526 (4.0%) high-risk prescribers in Florida, accounting for 67% of total opioid volume and 40% of total opioid prescriptions. Relative to their lower-risk counterparts, they wrote sixteen times more monthly opioid prescriptions (79 vs. 5, p<0.01), and had more prescription-filling patients receiving opioids (47% vs. 19%, p<0.01). Following policy implementation, Florida's high-risk providers experienced large relative reductions in opioid patients and opioid prescriptions (-536 patients/month, 95% confidence intervals [CI] -829 to -243; -847 prescriptions/month, CI -1498 to -197), morphine equivalent dose (-0.88mg/month, CI -1.13 to -0.62), and total opioid volume (-3.88kg/month, CI -5.14 to -2.62). Low-risk providers did not experience statistically significantly relative reductions, nor did policy implementation affect the status of being high- vs. low- risk prescribers. High-risk prescribers are disproportionately responsive to state policies. However, opioids-prescribing remains highly concentrated among high-risk providers.

Twitter Demographics

The data shown below were collected from the profiles of 14 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 132 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 16%
Student > Master 21 16%
Student > Ph. D. Student 20 15%
Student > Doctoral Student 13 10%
Other 12 9%
Other 22 17%
Unknown 23 17%
Readers by discipline Count As %
Medicine and Dentistry 31 23%
Nursing and Health Professions 17 13%
Social Sciences 15 11%
Pharmacology, Toxicology and Pharmaceutical Science 9 7%
Business, Management and Accounting 4 3%
Other 19 14%
Unknown 37 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 216. 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 01 April 2020.
All research outputs
#94,288
of 17,361,274 outputs
Outputs from Drug & Alcohol Dependence
#54
of 4,905 outputs
Outputs of similar age
#2,682
of 273,101 outputs
Outputs of similar age from Drug & Alcohol Dependence
#1
of 97 outputs
Altmetric has tracked 17,361,274 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,905 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has done particularly well, scoring higher than 98% 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 273,101 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 99% of its contemporaries.
We're also able to compare this research output to 97 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 99% of its contemporaries.