Neal Oden

Patients with opioid use disorder (OUD) frequently present to the emergency department (ED) after overdose, or seeking treatment for general medical conditions, their addiction, withdrawal symptoms, or complications of injection drug use, such as soft tissue infections. ED-initiated buprenorphine has been shown to be effective in increasing patient engagement in treatment compared with brief intervention with a facilitated referral or referral alone. However, adoption into practice has lagged behind need. To address this implementation challenge, we are evaluating the impact of implementation facilitation (IF) on the adoption of ED-initiated buprenorphine for OUD into practice. This protocol describes a study that is being conducted through the National Institute on Drug Abuse’s Center for the Clinical Trials Network. A hybrid type III effectiveness-implementation study design is used to evaluate the effectiveness of a standard educational dissemination strategy versus IF on implementation (primary) and effectiveness (secondary) outcomes in four urban, academic EDs. Sites start with a standard 60-min “Grand Rounds” educational intervention describing the prevalence of ED patients with OUD, the evidence for opioid agonist treatment and for innovative interventions with ED-initiated buprenorphine; followed by a 1-year baseline evaluation period. Using a modified stepped wedge design, sites are randomly assigned to the IF intervention which is guided by the Promoting Action on Research Implementation in Health Services (PARiHS) framework to assess evidence, context, and facilitation-related factors impacting the adoption of ED-initiated buprenorphine. During the 6 months of IF through the 1-year IF evaluation period, external facilitators work with local stakeholders to tailor and refine a bundle of activities to meet the site’s needs. The primary analyses compare the baseline evaluation period to the IF evaluation period (n = 120 patients with untreated OUD enrolled during each period) on (1) rates of provision of ED-initiated buprenorphine by ED providers with referral for ongoing medication (implementation outcome) and (2) rates of patient engagement in addiction treatment on the 30th day after the ED visit (effectiveness outcome). Finally, we will perform a cost-effectiveness analysis (CEA) to determine if the effectiveness benefits are worth the additional costs. Results will generate novel information regarding the impact of IF as a strategy to promote ED-initiated buprenorphine. ClinicalTrials.gov NCT03023930 first posted 1/10/2017, https://clinicaltrials.gov/ct2/show/NCT03023930?term=0069&rank=1

Screening, brief intervention, and referral to treatment (SBIRT) approaches to reducing hazardous alcohol and illicit drug use have been assessed in a variety of health care settings, including primary care, trauma centers, and emergency departments. A major methodological concern in these trials, however, is “assessment reactivity,” the hypothesized impact of intensive research assessments to reduce alcohol and drug use and thus mask the purported efficacy of the interventions under scrutiny. Thus, it has been recommended that prospective research designs take assessment reactivity into account. The present article describes the design of the National Institute on Drug Abuse Clinical Trials Network protocol, Screening, Motivational Assessment, Referral, and Treatment in Emergency Departments (SMART-ED), which addresses the potential bias of assessment reactivity.

There is a need for novel approaches to the treatment of stimulant abuse and dependence. Clinical data examining the use of exercise as a treatment for the abuse of nicotine, alcohol, and other substances suggest that exercise may be a beneficial treatment for stimulant abuse, with direct effects on decreased use and craving. In addition, exercise has the potential to improve other health domains that may be adversely affected by stimulant use or its treatment, such as sleep disturbance, cognitive function, mood, weight gain, quality of life, and anhedonia, since it has been shown to improve many of these domains in a number of other clinical disorders. Furthermore, neurobiological evidence provides plausible mechanisms by which exercise could positively affect treatment outcomes. The current manuscript presents the rationale, design considerations, and study design of the National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) CTN-0037 Stimulant Reduction Intervention using Dosed Exercise (STRIDE) study. STRIDE is a multisite randomized clinical trial that compares exercise to health education as potential treatments for stimulant abuse or dependence. This study will evaluate individuals diagnosed with stimulant abuse or dependence who are receiving treatment in a residential setting. Three hundred and thirty eligible and interested participants who provide informed consent will be randomized to one of two treatment arms: Vigorous Intensity High Dose Exercise Augmentation (DEI) or Health Education Intervention Augmentation (HEI). Both groups will receive TAU (i.e., usual care). The treatment arms are structured such that the quantity of visits is similar to allow for equivalent contact between groups. In both arms, participants will begin with supervised sessions 3 times per week during the 12-week acute phase of the study. Supervised sessions will be conducted as one-on-one (i.e., individual) sessions, although other participants may be exercising at the same time. Following the 12-week acute phase, participants will begin a 6-month continuation phase during which time they will attend one weekly supervised DEI or HEI session. ClinicalTrials.gov, NCT01141608 http://clinicaltrials.gov/ct2/show/NCT01141608?term=Stimulant+Reduction+Intervention+using+Dosed+Exercise&rank=1

Background: In clinical trials of treatment for stimulant abuse, researchers commonly record both Time-Line Follow-Back (TLFB) self-reports and urine drug screen (UDS) results. Objectives: To compare the power of self-report, qualitative (use vs. no use) UDS assessment, and various algorithms to generate self-report-UDS composite measures to detect treatment differences via t-test in simulated clinical trial data. Methods: We performed Monte Carlo simulations patterned in part on real data to model self-report reliability, UDS errors, dropout, informatively missing UDS reports, incomplete adherence to a urine donation schedule, temporal correlation of drug use, number of days in the study period, number of patients per arm, and distribution of drug-use probabilities. Investigated algorithms include maximum likelihood and Bayesian estimates, self-report alone, UDS alone, and several simple modifications of self-report (referred to here as ELCON algorithms) which eliminate perceived contradictions between it and UDS. Results: Among the algorithms investigated, simple ELCON algorithms gave rise to the most powerful t-tests to detect mean group differences in stimulant drug use. Conclusions: Further investigation is needed to determine if simple, naïve procedures such as the ELCON algorithms are optimal for comparing clinical study treatment arms. But researchers who currently require an automated algorithm in scenarios similar to those simulated for combining TLFB and UDS to test group differences in stimulant use should consider one of the ELCON algorithms. Scientific Significance: This analysis continues a line of inquiry which could determine how best to measure outpatient stimulant use in clinical trials (NIDA. NIDA Monograph-57: Self-Report Methods of Estimating Drug Abuse: Meeting Current Challenges to Validity. NTIS PB 88248083. Bethesda, MD: National Institutes of Health, 1985; NIDA. NIDA Research Monograph 73: Urine Testing for Drugs of Abuse. NTIS PB 89151971. Bethesda, MD: National Institutes of Health, 1987; NIDA. NIDA Research Monograph 167: The Validity of Self-Reported Drug Use: Improving the Accuracy of Survey Estimates. NTIS PB 97175889. GPO 017-024-01607–1. Bethesda, MD: National Institutes of Health, 1997).

We compare five closed tests for strong control of family-wide type 1 error while making all pairwise comparisons of means in clinical trials with multiple