Ian Ayres, J.D., Ph.D., is the William K. Townsend Professor at Yale Law School. He received his Ph.D (Economics) from M.I.T. and his J.D. from Yale. Amen Jalal is a Post-Graduate Research Fellow at Yale Law School.
J Law Med Ethics. 2018 Jun;46(2):387-403. doi: 10.1177/1073110518782948.
This paper seeks to understand the treatment effect of Prescription Drug Monitoring Programs (PDMPs) on opioid prescription rates. Using county-level panel data on all opioid prescriptions in the U.S. between 2006 and 2015, we investigate whether state interventions like PDMPs have heterogeneous treatment effects at the sub-state level, based on regional and temporal variations in policy design, extent of urbanization, race, and income. Our models comprehensively control for a set of county and time fixed effects, countyspecific and time-varying demographic controls, potentially endogenous time-series trends in prescription rates, and other state-level opioid interventions such as Naloxone Access and Good Samaritan laws, Medicaid expansion, and the provision of Methadone Assistance Treatment. We find that PDMPs are only effective in reducing prescription rates if they obligate doctors to check for patients' history prior to filling out a prescription, but the frequency at which a state requires its PDMP to be updated is irrelevant to its effectiveness. Moreover, the significant treatment effects of PDMPs are almost exclusively driven by urban and predominantly white counties, with the relatively more affluent regions showing greater responsiveness than their less affluent counterparts.
本文旨在探讨处方药物监测计划（PDMPs）对阿片类药物处方率的治疗效果。利用美国 2006 年至 2015 年间所有阿片类药物处方的县级面板数据，我们根据政策设计、城市化程度、种族和收入的区域和时间差异，研究了 PDMP 等州级干预措施在次州一级是否具有异质的治疗效果。我们的模型全面控制了一组县和时间固定效应、县特定和时变人口统计控制、处方率的潜在内源性时间序列趋势，以及其他州级阿片类药物干预措施，如纳洛酮准入和好人法、医疗补助扩大和提供美沙酮辅助治疗。我们发现，只有当医生在填写处方前强制检查患者的病史时，PDMP 才能有效降低处方率，但州要求 PDMP 更新的频率与其有效性无关。此外，PDMP 的显著治疗效果几乎完全由城市和以白种人为主的县驱动，相对富裕的地区比贫困地区的反应更为明显。
