Disclosure: This study is unfunded; none of the authors received direct compensation for their role in this study. At the time this article was written, LMR, DD, JEB, RCD, and BBB were employees or advisory board members for the DHHA/RMPDC RADARS System.
Do Prescription Monitoring Programs Impact State Trends in Opioid Abuse/Misuse?
Article first published online: 2 FEB 2012
Wiley Periodicals, Inc.
Volume 13, Issue 3, pages 434–442, March 2012
How to Cite
Reifler, L. M., Droz, D., Bailey, J. E., Schnoll, S. H., Fant, R., Dart, R. C. and Bucher Bartelson, B. (2012), Do Prescription Monitoring Programs Impact State Trends in Opioid Abuse/Misuse?. Pain Medicine, 13: 434–442. doi: 10.1111/j.1526-4637.2012.01327.x
- Issue published online: 16 MAR 2012
- Article first published online: 2 FEB 2012
- Prescription Monitoring Programs;
- Opioid Abuse;
- Opioid Misuse
Objective. Prescription monitoring programs (PMPs) are statewide databases containing prescriber and patient-level prescription data on select drugs of abuse. These databases are used by medical professionals or law enforcement officials to identify patients with prescription drug use patterns indicative of abuse or providers engaging in illegal activities. Most states have implemented PMPs in an attempt to curb prescription drug abuse and diversion. However, assessment of their impact on drug abuse is only beginning. This study aimed to evaluate the relationship between PMPs and opioid misuse over time in two drug abuse surveillance data sources.
Methods. Data from the RADARS® System Poison Center and Opioid Treatment surveillance databases were used to obtain measures of abuse and misuse of opioids. Repeated measures negative binomial regression was applied to quarterly surveillance data (from 2003 to mid-2009) to estimate and compare opioid abuse and misuse trends. PMP presence was modeled as a time varying covariate for each state.
Results. Results support an association between PMPs and mitigated opioid abuse and misuse trends. Without a PMP in place, Poison Center intentional exposures increased, on average, 1.9% per quarter, whereas opioid intentional exposures increase 0.2% (P = 0.036) per quarter with a PMP in place. Opioid treatment admissions increase, on average, 4.9% per quarter in states without a PMP vs 2.6% (P = 0.058) in states with a PMP. In addition to the time trend, population and a measure of drug availability were also significant predictors. A secondary analysis that classified PMP based upon ideal characteristic showed consistent though not significant results.
Conclusions. Two observational data sources offer preliminary support that PMPs are effective. Future efforts should evaluate what PMP characteristics are most effective and which opioids are most impacted.