Features of prescription drug monitoring programs associated with reduced rates of prescription opioid-related poisonings

Abstract

Background: The United States is in the midst of an opioid epidemic. In addition to other system-level interventions, all states have responded during the crisis by implementing prescription drug monitoring programs (PDMPs). This study examines associations between specific administrative features of PDMPs and changes in the risk of prescription opioid-related poisoning (RxORP) over time.

Methods: This longitudinal, observational study utilized a 'natural experiment' design to assess associations between PDMP features and risk of RxORP in a nationally-representative population of privately-insured adults from 2004 to 2014. Administrative health claims data were used to identify inpatient hospital admissions and emergency department visits related to RxORP. Generalized estimating equation Poisson regression models were used to examine associations between specific PDMP features and changes in relative risk (RR) of RxORP over time.

Results: In adjusted analyses, states without PDMPs experienced an average annual increase in the rate of RxORP of 9.51% over the study period, while states with operational PDMPs experienced an average annual increase of 3.17%. The increase in RR of RxORP over time in states with operational PDMPs was significantly less than increases in states without PDMPs. States with specific features, including those that monitored more schedules or required more frequent data reporting, experienced stronger protective effects on the RR of RxORP over time.

Conclusion: This study examined associations between specific PDMP features and RxORP rates in a nationally-representative population of privately-insured adults. Results of this study may be used as empirical evidence to guide PDMP best practices.

Keywords: Evaluation; Opioid; Poisoning; Policy; Prescription drug monitoring program.

Figure 1 (A, B, C). Predicted unadjusted rates of RxORP over time by PDMP features of interest

Effect plots are generated from unadjusted generalized estimating equation Poisson regression models where each model includes a single PDMP feature, a time indicator variable, and an interaction between the PDMP feature and time. The y axis displays the predicted rate of RxORP per 100,000 beneficiaries and the×axis displays the number of months since the study period began (IE month 0= January 2004 and month 131= December 2014). The shaded regions surrounding lines represent 95% confidence intervals.

Figure 1 (A, B, C). Predicted unadjusted rates of RxORP over time by PDMP features of interest

Effect plots are generated from unadjusted generalized estimating equation Poisson regression models where each model includes a single PDMP feature, a time indicator variable, and an interaction between the PDMP feature and time. The y axis displays the predicted rate of RxORP per 100,000 beneficiaries and the×axis displays the number of months since the study period began (IE month 0= January 2004 and month 131= December 2014). The shaded regions surrounding lines represent 95% confidence intervals.

Figure 2. Forest plot of adjusted relative risk of RxORP in December 2014 in states with PDMPs with certain features relative to states without PDMPs

Generalized estimating equation Poisson regression models were used to estimate the RR of RxORP in December 2014 associated with each level of each PDMP feature while adjusting for clinical and demographic covariates. Separate models were built for each feature of interest. Each model included one PDMP feature, as well as measures for the percentage of the population that was male, percentage aged 25–35, rate of diagnosed substance use disorder, geographic region, a time indicator, and an interaction between the PDMP feature and time. For each model, person-months observed in each state-month, expressed as natural logarithms, were used as offset terms and robust standard errors were calculated to account for repeated measures from each state. Acronyms: PDMP: Prescription Drug Monitoring Program, RxORP: Prescription Opioid-Related Poisoning, aRR: adjusted relative risk, LCL: lower confidence level, UCL: upper confidence level, CI: confidence interval