BACKGROUND: Long-term efficacy of opioids for noncancer pain is unproven, but risks argue for cautious prescribing. Few data suggest how long or how much opioid can be prescribed for opioid-naïve patients without inadvertently promoting long-term use. OBJECTIVE: To examine the association between initial opioid prescribing patterns and likelihood of long-term use among opioid-naïve patients. DESIGN: Retrospective cohort study; data from Oregon resident prescriptions linked to death certificates and hospital discharges. PARTICIPANTS: Patients filling opioid prescriptions between October 1, 2012, and September 30, 2013, with no opioid fills for the previous 365 days. Subgroup analyses examined patients under age 45 who did not die in the follow-up year, excluding most cancer or palliative care patients. MAIN MEASURES: Exposure: Numbers of prescription fills and cumulative morphine milligram equivalents (MMEs) dispensed during 30 days following opioid initiation (Binitiation month^). Outcome: Proportion of patients with six or more opioid fills during the subsequent year (Blong-term users^). KEY RESULTS: There were 536,767 opioid-naïve patients who filled an opioid prescription. Of these, 26,785 (5.0 %) became long-term users. Numbers of fills and cumulative MMEs during the initiation month were associated with long-term use. Among patients under age 45 using short-acting opioids who did not die in the follow-up year, the adjusted odds ratio (OR) for long-term use among those receiving two fills versus one was 2.25 (95 % CI: 2.17, 2.33). Compared to those who received < 120 total MMEs, those who received between 400 and 799 had an OR of 2.96 (95 % CI: 2.81, 3.11). Patients initiating with long-acting opioids had a higher risk of long-term use than those initiating with short-acting drugs.CONCLUSIONS: Early opioid prescribing patterns are associated with long-term use. While patient characteristics are important, clinicians have greater control over initial prescribing. Our findings may help minimize the risk of inadvertently initiating long-term opioid use.

Lumbar fusion surgery is usually prompted by chronic back pain, and many patients receive long-term preoperative opioid analgesics. Many expect surgery to eliminate the need for opioids. We sought to determine what fraction of long-term preoperative opioid users discontinue or reduce dosage postoperatively; what fraction of patients with little preoperative use initiate long-term use; and what predicts long-term postoperative use. This retrospective cohort study included 2491 adults undergoing lumbar fusion surgery for degenerative conditions, using Oregon's prescription drug monitoring program to quantify opioid use before and after hospitalization. We defined long-term postoperative use as ≥4 prescriptions filled in the 7 months after hospitalization, with at least 3 occurring >30 days after hospitalization. Overall, 1045 patients received long-term opioids preoperatively, and 1094 postoperatively. Among long-term preoperative users, 77.1% continued long-term postoperative use, and 13.8% had episodic use. Only 9.1% discontinued or had short-term postoperative use. Among preoperative users, 34.4% received a lower dose postoperatively, but 44.8% received a higher long-term dose. Among patients with no preoperative opioids, 12.8% became long-term users. In multivariable models, the strongest predictor of long-term postoperative use was cumulative preoperative opioid dose (odds ratio of 15.47 [95% confidence interval 8.53-28.06] in the highest quartile). Cumulative dose and number of opioid prescribers in the 30-day postoperative period were also associated with long-term use. Thus, lumbar fusion surgery infrequently eliminated long-term opioid use. Opioid-naive patients had a substantial risk of initiating long-term use. Patients should have realistic expectations regarding opioid use after lumbar fusion surgery.

Prescription drug monitoring programs (PDMP) are relatively new but potentially useful tools to enhance prudent prescribing of controlled substances. However, little is known about the types of clinicians who make most use of PDMPs, how they are incorporated into workflow, or how clinicians and patients respond to the information. We therefore surveyed a random sample of Oregon providers, with 1065 respondents. Clinicians in emergency medicine, primary care, and pain and addiction specialties were the largest number of registrants but many frequent prescribers of controlled substances were not registered to use the PDMP. Among users, 95% reported accessing the PDMP when they suspected a patient of abuse or diversion, but fewer than half would check it for every new patient or every time they prescribe a controlled drug. Nearly all PDMP users reported that they discuss worrisome PDMP data with patients; 54% reported making mental health or substance abuse referrals, and 36% reported sometimes discharging patients from the practice. Clinicians reported frequent patient denial or anger, and only occasional requests for help with drug dependence. More research is needed to optimize how clinicians use PDMPs across settings, and how clinicians and patients respond to the data.

Greater consistency is needed in use of PDMP in monitoring existing patients and in conformity to guidelines against discharging patients from practice. Research is needed to determine optimal approaches to interpreting PDMP profiles in relation to clinical judgment, patient screeners, and other information.

The net effects of prescribing initiatives that encourage dose reductions are uncertain. We examined whether rapid dose reduction after high-dose chronic opioid therapy (COT) associates with suicide, overdose, or other opioid-related adverse events. This retrospective cohort study included Oregon Medicaid recipients with high-dose COT. Claims were linked with prescription data from the prescription drug monitoring program and death data from vital statistics, 2014 to 2017. Participants were placed into 4 mutually exclusive dose trajectory groups after the high-dose COT period, and Cox proportional hazard models were used to examine the effect of dose changes on patient outcomes in the following year. Of the 14,596 high-dose COT patients, 4191 (28.7%) abruptly discontinued opioid prescriptions, 1648 (11.3%) reduced opioid dose before discontinuing, 6480 (44.4%) had a dose reduction but never discontinued, and 2277 (15.6%) had a stable or increasing dose. Discontinuation, whether abrupt (adjusted hazard ratio [aHR] 3.63; 95% confidence interval [CI] 1.42-9.25) or with dose reduction (aHR 4.47,) significantly increased risk of suicide compared with those with stable or increasing dose. By contrast, discontinuation or dose reduction reduced the risk of overdose compared with those with a stable or increasing dose (aHR 0.36-0.62, 95% CI 0.20-0.94). Patients with an abrupt discontinuation were more likely to overdose on heroin (vs. prescription opioids) than patients in other groups (P , 0.0001). Our study suggests that patients on COT require careful risk assessment and supportive interventions when considering opioid discontinuation or continuation at a high dose.