State-level factors associated with implementation of prescription drug monitoring program integration and mandatory use policies, United States, 2009-2020

Christian E Johnson; Elizabeth A Chrischilles; Stephan Arndt; Ryan M Carnahan

doi:10.1093/jamia/ocae160

Prescription drug monitoring programs (PDMPs) have been widely adopted as a tool to address the prescription opioid epidemic in the United States. PDMP integration and mandatory use policies are 2 approaches states have implemented to increase use of PDMPs by prescribers. While the effectiveness of these approaches is mixed, it is unclear what factors motivated states to implement them. This study examines whether opioid dispensing, adverse health outcomes, or other non-health-related factors motivated implementation of these PDMP approaches.BACKGROUNDPrescription drug monitoring programs (PDMPs) have been widely adopted as a tool to address the prescription opioid epidemic in the United States. PDMP integration and mandatory use policies are 2 approaches states have implemented to increase use of PDMPs by prescribers. While the effectiveness of these approaches is mixed, it is unclear what factors motivated states to implement them. This study examines whether opioid dispensing, adverse health outcomes, or other non-health-related factors motivated implementation of these PDMP approaches.Time-to-event analysis was performed using lagged state-year covariates to reflect values from the year prior. Extended Cox regression estimated the association of states' rates of opioid dispensing, prescription opioid overdose deaths, and neonatal opioid withdrawal syndrome with implementation of PDMP integration and mandatory use policies from 2009 to 2020, controlling for demographic and economic factors, state government and political factors, and prior opioid policies.METHODSTime-to-event analysis was performed using lagged state-year covariates to reflect values from the year prior. Extended Cox regression estimated the association of states' rates of opioid dispensing, prescription opioid overdose deaths, and neonatal opioid withdrawal syndrome with implementation of PDMP integration and mandatory use policies from 2009 to 2020, controlling for demographic and economic factors, state government and political factors, and prior opioid policies.In our main model, prior opioid dispensing (HR 2.31, 95% CI 1.17, 4.57), neonatal opioid withdrawal syndrome hospitalizations (HR 1.55, 95% CI 1.09, 2.19), and number of prior opioid policies (HR 2.13, 95% CI 1.13, 4.00) were associated with mandatory use policies. Prior prescription opioid overdose deaths (HR 1.21, 95% CI 1.08, 1.35) were also associated with mandatory use policies in a model that did not include opioid dispensing or neonatal opioid withdrawal syndrome. No study variables were associated with implementation of PDMP integration.RESULTSIn our main model, prior opioid dispensing (HR 2.31, 95% CI 1.17, 4.57), neonatal opioid withdrawal syndrome hospitalizations (HR 1.55, 95% CI 1.09, 2.19), and number of prior opioid policies (HR 2.13, 95% CI 1.13, 4.00) were associated with mandatory use policies. Prior prescription opioid overdose deaths (HR 1.21, 95% CI 1.08, 1.35) were also associated with mandatory use policies in a model that did not include opioid dispensing or neonatal opioid withdrawal syndrome. No study variables were associated with implementation of PDMP integration.Understanding state-level factors associated with implementing PDMP approaches can provide insights into factors that motivate the adoption of future public health interventions.CONCLUSIONUnderstanding state-level factors associated with implementing PDMP approaches can provide insights into factors that motivate the adoption of future public health interventions.

State-level factors associated with implementation of prescription drug monitoring program integration and mandatory use policies, United States, 2009-2020

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