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Years of sustained, coordinated, and vigilant effort will be required to contain the present opioid epidemic and ameliorate its harmful effects on society. At least 2 million people have an opioid use disorder (OUD) involving prescription opioids, and almost 600,000 have an OUD associated with heroin (HHS, 2016). These numbers are likely to increase in the coming years, regardless of what policies are put in place. Follow-up studies of individuals receiving treatment for OUD involving heroin (e.g., Hser et al., 2001) find very high rates of premature mortality (in the neighborhood of one-third) due to overdose or other complications of the disorder. Thus, even if the nation ramps up treatment availability substantially and immediately, death rates will climb and quality of life will be dramatically reduced for many people for years to come. Likewise, the continued progression of still more people from prescription opioid use to OUD will demand sustained and coordinated effort to establish and implement the scientifically grounded policies and clinical practices necessary to reshape prescribing practices and reduce the occurrence of new cases of prescription opioid-induced OUD. 1 What should be done to contain the opioid epidemic and to prevent new cases of iatrogenic addiction and associated overdose, death, and other harms? The purpose of this chapter is to review available evidence on strategies that have been used to address the problems of opioid misuse, OUD, 1 Vigilance will also be needed to reduce the risk of similar problems in the future with other classes of medications for which there exists demand for clinical uses other than the indicated conditions and/or active black markets for their resale. 269RCTs, however, are rare for policies that require implementation at the level of an entire jurisdiction, nor are they ethically permissible in many policy contexts. In the absence of RCTs, other sources of evidence are needed to estimate the counterfactual outcome distribution under different strategies. One such source of evidence is the collection of data on individuals who happen to receive the strategies of interest as part of their routine care, often from electronic health records. The so-called observational analyses based on such data are attempts to emulate the RCT that cannot be conducted (the target trial). In these observational analyses, however, the comparability of the groups receiving each strategy is not guaranteed. In the real world, for example, the restricted opioid prescription policy might more likely be applied to individuals visiting providers in urban health care settings who also received other interventions to reduce the risk of addiction. As a result, a direct comparison of the outcome distribution between those who received each strategy would be confounded by the concomitant interventions.Observational analyses attempt to eliminate bias due to confounding by adjusting for all measured prognostic factors that are distributed differentially between the groups. For example, the ...

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Background and aims Buprenorphine is an effective medication for opioid use disorder that reduces mortality; however, many patients are not retained in buprenorphine treatment, and an optimal length of treatment after which patients can safely discontinue treatment has not been identified. This study measured the association between buprenorphine treatment duration and all‐cause mortality among patients who discontinued treatment. Secondary objectives were to measure the association between treatment duration and drug overdose and opioid‐related overdoses. Design Multi‐site cohort study. Setting Eight US health systems. Participants Patients who initiated and discontinued buprenorphine treatment between 1 January 2012 and 31 December 2018 (n = 6550). Outcomes occurring after patients discontinued buprenorphine treatment were compared between patients who initiated and discontinued treatment after 8–30, 31–90, 91–180, 181–365 and > 365 days. Measurements Covariate data were obtained from electronic health records (EHRs). Mortality outcomes were derived from EHRs and state vital statistics. Non‐fatal opioid and drug overdoses were obtained from diagnostic codes. Four sites provided cause‐of‐death data to identify fatal drug and opioid‐related overdoses. Adjusted frailty regression was conducted on a propensity‐weighted cohort to assess associations between duration of the final treatment episode and outcomes. Findings The mortality rate after buprenorphine treatment was 1.82 per 100 person‐years (n = 191 deaths). In regression analyses with > 365 days as the reference group, treatment duration was not associated with all‐cause mortality and drug overdose (P > 0.05 for both). However, compared with > 365 days of treatment, 91–180 days of treatment was associated with increased opioid overdose risk (hazard ratio = 2.94, 95% confidence interval = 1.11–7.79). Conclusions Among patients who discontinue buprenorphine treatment, there appears to be no treatment duration period associated with a reduced risk for all‐cause mortality. Patients who discontinue buprenorphine treatment after 91–180 days appear to be at heightened risk for opioid overdose compared with patients who discontinue after > 365 days of treatment.