Assessing The Impact Of State Policies For Prescription Drug Monitoring Programs On High-Risk Opioid Prescriptions

Abstract

Policies and practices have proliferated to optimize prescribers' use of their states' prescription drug monitoring programs, which are statewide databases of controlled substances dispensed at retail pharmacies. Our study assessed the effectiveness of three such policies: comprehensive legislative mandates to use the program, laws that allow prescribers to delegate its use to office staff, and state participation in interstate data sharing. Our analysis of information from a large commercial insurance database indicated that comprehensive use mandates implemented during 2011-15 were associated with a 6-9 percent reduction in opioid prescriptions with high risk for misuse and overdose. We also found delegate laws to be associated with reductions of a similar magnitude for selected outcomes. In general, the effects of all three policies strengthened over time, especially beginning in the second year after implementation. Our findings support comprehensive use mandates and delegate laws to optimize prescribers' use of drug monitoring programs, but the results will need updates in the context of evolving state opioid policies-including the increasing integration of drug monitoring data with electronic health records.

Keywords: Mental Health/Substance Abuse; Prescription Drug Monitoring Programs; Prescription Opioid Misuse.

Exhibit 1

Changes in the probability of high-risk opioid prescriptions after the implementation of a comprehensive mandate to use a prescription drug monitoring program, 2011–15 Source/Notes: SOURCE Authors’ analysis of data for 2011–15 from the Health Care Cost Institute’s insurance claims database. NOTES The exhibit shows the predicted changes in the probabilities of outcomes associated with the implementation of a mandate among privately insured adults who were ages 18–64, had at least one opioid prescription in the study period, and lived in the twenty-eight states that had an operating program by the end of 2010. The whiskers indicate 95% confidence intervals. The percentages (relative effects) indicate the difference between probabilities with and without a mandate. High-risk opioid prescriptions are explained in the text. MME is morphine milligram equivalent. ****p < 0.001

Exhibit 2

Changes in the probability of high-risk opioid prescriptions after the implementation of legislation allowing delegate access to prescription drug monitoring program databases, 2011–15 Source/Notes: SOURCE Authors’ analysis of data for 2011–15 from the Health Care Cost Institute’s insurance claims database. NOTES The exhibit shows the predicted changes in the probabilities of outcomes associated with the implementation of the legislation among the population described in the notes to Exhibit 1. The whiskers indicate 95% confidence intervals. The percentages (relative effects) indicate the difference between probabilities with and without the legislation. High-risk opioid prescriptions are explained in the text. MME is morphine milligram equivalent. ***p < 0.01 ****p < 0.001

Exhibit 3

Changes in the probability of high-risk opioid prescriptions after states’ participation in interstate data sharing in prescription drug monitoring programs, 2011–15 Source/Notes: SOURCE Authors’ analysis of data for 2011–15 from the Health Care Cost Institute’s insurance claims database. NOTES The exhibit shows the predicted changes in the probabilities of outcomes associated with data sharing among the population described in the notes to Exhibit 1. The whiskers indicate 95% confidence intervals. The percentages (relative effects) indicate the difference between probabilities with and without data sharing. High-risk opioid prescriptions are explained in the text. MME is morphine milligram equivalent. ***p < 0.01 ****p < 0.001

Exhibit 4

Changes in the probability of high-risk opioid prescriptions after the implementation of a comprehensive mandate to use a prescription drug monitoring program, by time since mandate implementation, 2011–15 Source/Notes: SOURCE Authors’ analysis of data for 2011–15 from the Health Care Cost Institute’s insurance claims database. NOTES The exhibit shows the predicted changes in the probabilities of outcomes associated with the implementation of a mandate among the population described in the notes to Exhibit 1, relative to the period 0–6 months before implementation. The whiskers indicate 95% confidence intervals. MME is morphine milligram equivalent.