Abstract：
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: Understanding state-level factors associated with implementing PDMP approaches can provide insights into factors that motivate the adoption of future public health interventions.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: Understanding state-level factors associated with implementing PDMP approaches can provide insights into factors that motivate the adoption of future public health interventions.
摘要：
背景：处方药监测计划（PDMPs）已被广泛采用作为解决美国处方阿片类药物流行的工具。PDMP整合和强制性使用政策是各州为增加处方者对PDMP的使用而实施的2种方法。虽然这些方法的有效性参差不齐，目前还不清楚是什么因素促使国家实施这些措施。这项研究检查了阿片类药物配药，不良健康结果，或其他非健康相关因素促使这些PDMP方法的实施。
方法：使用滞后状态年协变量进行事件时间分析，以反映前一年的值。扩展的Cox回归估计了阿片类药物分配率的关联，处方阿片类药物过量死亡,和新生儿阿片类药物戒断综合征，2009年至2020年实施PDMP整合和强制使用政策，控制人口和经济因素，政府和政治因素，和先前的阿片类药物政策。
结果：在我们的主要模型中，先前的阿片类药物配药（HR2.31，95%CI1.17，4.57），新生儿阿片类药物戒断综合征住院（HR1.55，95%CI1.09，2.19），和之前的阿片类药物政策数量(HR2.13,95%CI1.13,4.00)与强制使用政策相关.先前处方阿片类药物过量死亡（HR1.21，95％CI1.08，1.35）也与不包括阿片类药物配药或新生儿阿片类药物戒断综合征的模型中的强制性使用政策有关。没有研究变量与PDMP整合的实施相关。
结论：了解与实施PDMP方法相关的州一级因素可以提供对推动采用未来公共卫生干预措施的因素的见解。
方法：使用滞后状态年协变量进行事件时间分析，以反映前一年的值。扩展的Cox回归估计了阿片类药物分配率的关联，处方阿片类药物过量死亡,和新生儿阿片类药物戒断综合征，2009年至2020年实施PDMP整合和强制使用政策，控制人口和经济因素，政府和政治因素，和先前的阿片类药物政策。
结果：在我们的主要模型中，先前的阿片类药物配药（HR2.31，95%CI1.17，4.57），新生儿阿片类药物戒断综合征住院（HR1.55，95%CI1.09，2.19），和之前的阿片类药物政策数量(HR2.13,95%CI1.13,4.00)与强制使用政策相关.先前处方阿片类药物过量死亡（HR1.21，95％CI1.08，1.35）也与不包括阿片类药物配药或新生儿阿片类药物戒断综合征的模型中的强制性使用政策有关。没有研究变量与PDMP整合的实施相关。
结论：了解与实施PDMP方法相关的州一级因素可以提供对推动采用未来公共卫生干预措施的因素的见解。
