Association for Public Policy Analysis & Management

Abuse of legal prescription drugs, particularly opioids, is a growing problem in the United States. This problem is driven by increases in the rate of prescribing of opioids as well as increasing abuse of those drugs. The abuse leads to addiction, negative health outcomes, increased disability costs, and death caused by overdose or poisoning. To combat this abuse, states have experimented with a variety of laws aimed at reducing the abuse of prescription drugs.  These laws include: tamper-resistant prescription pads, pain management clinic regulation, physical exams before prescribing, patient identification laws, prescription drug monitoring programs (PMPs), and others. Outside of PMPs, while some anecdotal evidence is promising, there are no systematic analyses of the impact of these laws on opioid use and abuse. This paper estimates the causal impact of these laws separately and in combination on various measures of opioid use and abuse in the Medicare population.

I begin by detailing the baseline level of opioid use and abuse in the Medicare population relying on measures of use that can be standardized across prescriptions (milligrams of morphine equivalence) and measures of abuse that are medically diagnosed or have agreed-upon cutoffs for appropriate use. I also analyze the baseline prescribing patterns of physicians who prescribe opioids. Relying on the variation in effective dates across states of each of these laws, I am able to identify a difference-in-differences model. I focus on a few state laws that, based on anecdotal reports or existing studies, are most likely to have an impact on a variety of opioid outcomes. Non-focus laws serve as important controls. The laws of focus are: prescription drug monitoring programs, tamper-resistant prescription pads, and stricter regulation of pain management clinics. Finally, I perform the difference-in-differences analysis using multivariate regressions. The outcomes of interest cover opioid use, medical and non-medical estimates of opioid abuse, and physician prescribing patterns. I also perform various sensitivity and falsification tests to lend credence to my findings.     

By quantifying the plausibly causal impact of various state laws on a wide variety of opioid-related outcomes, this paper identifies the collection of state laws that can help reduce opioid abuse. These findings can be used to craft legislative best-practices in opioid abuse reduction.