N J Pauly1, S Slavova2, C Delcher3, P R Freeman4, J Talbert4. 1. Institute for Pharmaceutical Outcomes and Policy, University of Kentucky College of Pharmacy, 789 South Limestone, Lexington, KY 40536, United States. Electronic address: Nathan.Pauly@uky.edu. 2. Department of Biostatistics, University of Kentucky College of Public Health, 333 Waller Avenue, Suite 242, Lexington, KY 40504, United States. 3. Department of Health Outcomes and Policy, University of Florida, 2004 Mowry Road, Suite 2237, P.O. Box 100177, Gainesville, FL 32610, United States. 4. Institute for Pharmaceutical Outcomes and Policy, University of Kentucky College of Pharmacy, 789 South Limestone, Lexington, KY 40536, United States.
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.
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.
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