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

Hsien-Yen Chang

Tatyana Lyapustina

Lainie Rutkow

Matt Richey

DOI: http://dx.doi.org/10.1016/j.drugalcdep.2016.04.033

Article Info

Highlights

•Impact of PDMPs and pill mill laws on high-risk prescriber in Florida were evaluated.
•High-risk prescribers accounted for 67% of total opioid volume and 40% of total opioid prescriptions.
•High-risk prescribers are disproportionately responsive to state policies to reduce opioid abuse.
•After policy implementation prescribing remains highly concentrated among the same prescribers.

Abstract

Background

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.

Methods

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.

Results

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 (−0.88 mg/month, CI −1.13 to −0.62), and total opioid volume (−3.88 kg/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.

Conclusions

High-risk prescribers are disproportionately responsive to state policies. However, opioids-prescribing remains highly concentrated among high-risk providers.