Community-Based Cluster-Randomized Trial to Reduce Opioid Overdose Deaths.

BACKGROUND: Evidence-based practices for reducing opioid-related overdose deaths include overdose education and naloxone distribution, the use of medications for the treatment of opioid use disorder, and prescription opioid safety. Data are needed on the effectiveness of a community-engaged intervention to reduce opioid-related overdose deaths through enhanced uptake of these practices. METHODS: In this community-level, cluster-randomized trial, we randomly assigned 67 communities in Kentucky, Massachusetts, New York, and Ohio to receive the intervention (34 communities) or a wait-list control (33 communities), stratified according to state. The trial was conducted within the context of both the coronavirus disease 2019 (Covid-19) pandemic and a national surge in the number of fentanyl-related overdose deaths. The trial groups were balanced within states according to urban or rural classification, previous overdose rate, and community population. The primary outcome was the number of opioid-related overdose deaths among community adults. RESULTS: During the comparison period from July 2021 through June 2022, the population-averaged rates of opioid-related overdose deaths were similar in the intervention group and the control group (47.2 deaths per 100,000 population vs. 51.7 per 100,000 population), for an adjusted rate ratio of 0.91 (95% confidence interval, 0.76 to 1.09; P = 0.30). The effect of the intervention on the rate of opioid-related overdose deaths did not differ appreciably according to state, urban or rural category, age, sex, or race or ethnic group. Intervention communities implemented 615 evidence-based practice strategies from the 806 strategies selected by communities (254 involving overdose education and naloxone distribution, 256 involving the use of medications for opioid use disorder, and 105 involving prescription opioid safety). Of these evidence-based practice strategies, only 235 (38%) had been initiated by the start of the comparison year. CONCLUSIONS: In this 12-month multimodal intervention trial involving community coalitions in the deployment of evidence-based practices to reduce opioid overdose deaths, death rates were similar in the intervention group and the control group in the context of the Covid-19 pandemic and the fentanyl-related overdose epidemic. (Funded by the National Institutes of Health; HCS ClinicalTrials.gov number, NCT04111939.).

Reductions in World Health Organization risk drinking level are associated with improvements in sleep problems among individuals with alcohol use disorder.

AIMS: Among individuals with alcohol use disorder (AUD), sleep disturbances are pervasive and contribute to the etiology and maintenance of AUD. However, despite increased attention toward the relationship between alcohol use and sleep, limited empirical research has systematically examined whether reductions in drinking during treatment for AUD are associated with improvements in sleep problems. METHODS: We used data from a multisite, randomized, controlled trial that compared 6 months of treatment with gabapentin enacarbil extended-release with placebo for adults with moderate-to-severe AUD (N = 346). The Timeline Follow-back was used to assess WHO risk drinking level reductions and the Pittsburgh Sleep Quality Index was used to assess sleep quality over the prior month at baseline and the end of treatment. RESULTS: Sleep problem scores in the active medication and placebo groups improved equally. Fewer sleep problems were noted among individuals who achieved at least a 1-level reduction (B = -0.99, 95% confidence interval (CI) [-1.77, -0.20], P = .014) or at least a 2-level reduction (B = -0.80, 95% CI [-1.47, -0.14], P = .018) in WHO risk drinking levels at the end of treatment. Reductions in drinking, with abstainers excluded from the analysis, also predicted fewer sleep problems at the end of treatment (1-level: B = -1.01, 95% CI [-1.83, -0.20], P = .015; 2-level: B = -0.90, 95% CI [-1.59, -0.22], P = .010). CONCLUSIONS: Drinking reductions, including those short of abstinence, are associated with improvements in sleep problems during treatment for AUD. Additional assessment of the causal relationships between harm-reduction approaches to AUD and improvements in sleep is warranted.

Cost of start-up activities to implement a community-level opioid overdose reduction intervention in the HEALing Communities Study.

BACKGROUND: Communities That HEAL (CTH) is a novel, data-driven community-engaged intervention designed to reduce opioid overdose deaths by increasing community engagement, adoption of an integrated set of evidence-based practices, and delivering a communications campaign across healthcare, behavioral-health, criminal-legal, and other community-based settings. The implementation of such a complex initiative requires up-front investments of time and other expenditures (i.e., start-up costs). Despite the importance of these start-up costs in investment decisions to stakeholders, they are typically excluded from cost-effectiveness analyses. The objective of this study is to report a detailed analysis of CTH start-up costs pre-intervention implementation and to describe the relevance of these data for stakeholders to determine implementation feasibility. METHODS: This study is guided by the community perspective, reflecting the investments that a real-world community would need to incur to implement the CTH intervention. We adopted an activity-based costing approach, in which resources related to hiring, training, purchasing, and community dashboard creation were identified through macro- and micro-costing techniques from 34 communities with high rates of fatal opioid overdoses, across four states-Kentucky, Massachusetts, New York, and Ohio. Resources were identified and assigned a unit cost using administrative and semi-structured-interview data. All cost estimates were reported in 2019 dollars. RESULTS: State-level average and median start-up cost (representing 8-10 communities per state) were $268,657 and $175,683, respectively. Hiring and training represented 40%, equipment and infrastructure costs represented 24%, and dashboard creation represented 36% of the total average start-up cost. Comparatively, hiring and training represented 49%, purchasing costs represented 18%, and dashboard creation represented 34% of the total median start-up cost. CONCLUSION: We identified three distinct CTH hiring models that affected start-up costs: hospital-academic (Massachusetts), university-academic (Kentucky and Ohio), and community-leveraged (New York). Hiring, training, and purchasing start-up costs were lowest in New York due to existing local infrastructure. Community-based implementation similar to the New York model may have lower start-up costs due to leveraging of existing infrastructure, relationships, and support from local health departments.

Effect of the Communities that HEAL intervention on receipt of behavioral therapies for opioid use disorder: A cluster randomized wait-list controlled trial.

BACKGROUND: The U.S. opioid overdose crisis persists. Outpatient behavioral health services (BHS) are essential components of a comprehensive response to opioid use disorder and overdose fatalities. The Helping to End Addiction Long-Term® (HEALing) Communities Study developed the Communities That HEAL (CTH) intervention to reduce opioid overdose deaths in 67 communities in Kentucky, Ohio, New York, and Massachusetts through the implementation of evidence-based practices (EBPs), including BHS. This paper compares the rate of individuals receiving outpatient BHS in Wave 1 intervention communities (n = 34) to waitlisted Wave 2 communities (n = 33). METHODS: Medicaid data included individuals ≥18 years of age receiving any of five BHS categories: intensive outpatient, outpatient, case management, peer support, and case management or peer support. Negative binomial regression models estimated the rate of receiving each BHS for Wave 1 and Wave 2. Effect modification analyses evaluated changes in the effect of the CTH intervention between Wave 1 and Wave 2 by research site, rurality, age, sex, and race/ethnicity. RESULTS: No significant differences were detected between intervention and waitlisted communities in the rate of individuals receiving any of the five BHS categories. None of the interaction effects used to test the effect modification were significant. CONCLUSIONS: Several factors should be considered when interpreting results-no significant intervention effects were observed through Medicaid claims data, the best available data source but limited in terms of capturing individuals reached by the intervention. Also, the 12-month evaluation window may have been too brief to see improved outcomes considering the time required to stand-up BHS. TRIAL REGISTRATION: Clinical Trials.gov http://www. CLINICALTRIALS: gov: Identifier: NCT04111939.

Reductions in World Health Organization Risk Drinking Level Are Associated With Reductions in Alcohol Use Disorder Diagnosis and Criteria: Evidence From an Alcohol Pharmacotherapy Trial.

OBJECTIVES: This study aimed to evaluate the validity of World Health Organization (WHO) risk drinking level reductions as meaningful endpoints for clinical practice and research. This study examined whether such reductions were associated with a lower likelihood of a current alcohol use disorder (AUD) diagnosis and fewer AUD criteria. METHODS: We conducted a secondary data analysis to address these objectives using data from a multisite randomized controlled trial of gabapentin enacarbil extended release in treating moderate to severe AUD among adults (N = 346). Participants received gabapentin enacarbil extended release or placebo for 6 months. The timeline follow-back was used to assess WHO risk drinking level reductions, and the Mini-International Neuropsychiatric Interview was used to assess Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) AUD diagnosis and criteria at baseline (past year) and end of treatment (past month). RESULTS: Most participants (80.1%) achieved at least a 1-level reduction in the WHO risk drinking levels from baseline to end of treatment, and nearly half of participants (49.8%) achieved at least a 2-level reduction. At least a 1-level reduction or at least a 2-level reduction in WHO risk drinking level predicted lower odds of an active AUD diagnosis (1-level: odds ratio, 0.74 [95% confidence interval (CI), 0.66-0.84]; 2-level: odds ratio, 0.71 [95% CI, 0.64-0.79]) and fewer AUD criteria (1-level: B, -1.66 [95% CI, -2.35 to -0.98]; 2-level: B, -1.76 [95% CI, -2.31 to -1.21]) at end of treatment. CONCLUSIONS: World Health Organization risk drinking level reductions correlate with Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) AUD diagnosis and criteria, providing further evidence for their use as endpoints in alcohol intervention trials, which has potential implications for broadening the base of AUD treatment.

Establishing a Protocol for Determining the Costs of an Integrated Set of Evidence-based Practices Aimed at Reducing Opioid Overdose Deaths.

OBJECTIVES: In the midst of the opioid overdose crisis, local jurisdictions face a choice of public health interventions. A significant barrier when considering evidence-based practices (EBPs) is the lack of information regarding their implementation cost. This protocol paper provides the methodological foundation for the economic cost evaluations of community-wide strategies on the scale of a national study. It can serve as a resource for other communities, local policymakers, and stakeholders as they consider implementing possible public health strategies in their unique settings. METHODS: We present a protocol that details (1) the process of identifying, reviewing, and analyzing individual strategies for study-funded and non-study-funded costs; (2) prospective costing tool designation, and; (3) data collection. To do this, we set up working groups with community stakeholders, reviewed financial invoices, and surveyed individuals with detailed knowledge of their community implementation. DISCUSSION: There were 3 main challenges/limitations. The first was the lack of a standard structure for documenting nonfunded costs associated with each strategy. The second was the need for timely implementation of cost data. The third was generalizability because our study designed its strategies for selected communities due to their high opioid overdose mortality rates. Future steps include more tailored questions to ask during the categorization/filter process and establishing realistic expectations for organizations regarding documenting. CONCLUSIONS: Data collected will provide a critical methodological foundation for costing large community-based EBP strategies and provide clarity for stakeholders on the cost of implementing EBP strategies to reduce opioid overdose deaths.

Reductions in WHO risk drinking levels correlate with alcohol craving among individuals with alcohol use disorder.

BACKGROUND: Abstinence has historically been considered the preferred goal of alcohol use disorder (AUD) treatment. However, most individuals with AUD do not want to abstain and many are able to reduce their drinking successfully. Craving is often a target of pharmacological and behavioral interventions for AUD, and reductions in craving may signal recovery. Whether reductions in drinking during AUD treatment are associated with reductions in craving has not been well examined. METHODS: We conducted secondary analyses of data from three AUD clinical trials (N's= 1327, 346, and 200). Drinking reductions from baseline to the end of treatment were measured as changes in World Health Organization (WHO) risk drinking levels; alcohol craving was measured using validated self-report measures. Regression analyses tested whether drinking reductions were associated with end-of-treatment craving reductions; moderation analyses tested whether associations between drinking reduction and end-of-treatment craving differed across AUD severity. RESULTS: Reductions of at least 1 or at least 2 WHO risk drinking levels were associated with lower craving (all p's < 0.05). Results were substantively similar after removing abstainers at the end-of-treatment. Associations between drinking reductions and craving were generally not moderated by AUD severity. CONCLUSIONS: Individuals with WHO risk drinking level reductions reported significantly lower craving, as compared to those who did not achieve meaningful reductions in drinking. The results demonstrate the utility of WHO risk drinking levels as AUD clinical trial endpoints and provide evidence that drinking reductions mitigate craving.

Associations between opioid overdose deaths and drugs confiscated by law enforcement and submitted to crime laboratories for analysis, United States, 2014-2019: an observational study.

Background: The overdose epidemic in the United States (US) continues to generate unprecedented levels of mortality. There is urgent need for a national data system capable of yielding high-quality, timely, and actionable information on existing and emerging drugs. Public health researchers have started using law enforcement forensic laboratory data to obtain surveillance information on illicit drugs. This study is the first to use drug reports from the entire US to examine correlations between a changing drug supply and increasing opioid-involved overdose deaths (OOD) on a national scale. Methods: This study is observational and investigates associations between law enforcement drug reports and OOD for the US from 2014 to 2019. OOD data are from the Centers for Disease Control and Prevention's National Vital Statistics System restricted-use multiple cause of death files. The US Drug Enforcement Administration's National Forensic Laboratory Information System (NFLIS) contains forensic laboratory-tested drug exhibit information for the entire US (NFLIS-Drug). Counts of forensic laboratory reports and OOD were aggregated for each state by month, quarter, and year. A difference-in-differences framework was used to estimate contemporaneous and lagged associations. Findings: Between 2014 and 2019 in the US, 249,522 OOD were reported, with the annual number nearly doubling from 28,723 to 50,179. OOD involving illicitly manufactured fentanyls (IMF) also increased substantially during this period, from 19.4% to 72.9%. In addition, 3,817,438 forensic laboratory reports in the US that were reported to NFLIS-Drug contained an opioid, stimulant, or benzodiazepine. Reports of fentanyl and fentanyl-related compounds (FFRC) had the strongest association with OOD. Each additional FFRC exhibit was associated with a 2.97% (95% CI: 1.7%, 4.1%) increase in OOD per 100,000 persons per quarter. Interpretation: Adding to the emerging consensus, protracted growth in IMF supply was more strongly associated with OOD than all other illicit drugs reported to NFLIS-Drug over the study time period. Findings demonstrate NFLIS-Drug data usefulness for research that require proxy indicators for the illicit drugs supply. A concerted effort between public health and public safety to make NFLIS-Drug more timely could strengthen its utility as a national, public health, drug surveillance system. Funding: Sangeetha Arctic Slope Mission Services, LLC, ASMS Contract No. ASM5-00017.

Pennsylvania's Community Coordination Strategy to Reduce Opioid Overdose Deaths.

OBJECTIVE: The Pennsylvania Opioid Overdose Reduction Technical Assistance Center (ORTAC) was developed to provide community-level support across Pennsylvania with the goal of reducing the opioid-related overdose death (ODD) rate via coalition building/coordination and tailored technical assistance. This study evaluates the initial effects of ORTAC engagement on county-level opioid ODD reductions. METHOD: Using quasi-experimental difference-in-difference models, we compared ODD per 100,000 population per quarter between 2016 and 2019 in the 29 ORTAC-implementing counties against the 19 nonengaged counties while controlling for county-level time-varying confounders (e.g., naloxone administration by law enforcement). RESULTS: Before ORTAC implementation, the average ODD/100,000 was 8.92 per 100,000 (SD = 3.62) in ORTAC counties and 5.62 per 100,000 (SD = 2.17) for the 19 comparison counties. Relative to the pre-study rate, there was an estimated 30% decrease in the ODD/100,000 within implementing counties after the first two quarters of ORTAC implementation. In the second year after ORTAC implementation, the estimated difference between ORTAC and non-ORTAC counties reached a high of 3.80 fewer deaths per 100,000. Overall, analyses indicated that ORTAC's service was associated with avoiding 1,818 opioid ODD in the 29 implementing counties in the 2 years following implementation. CONCLUSIONS: Findings reinforce the impact of coordinating communities around addressing the ODD crisis. Future policy efforts should provide a suite of overdose reduction strategies and intuitive data structures that can be tailored to individual communities' needs.

Association between law enforcement seizures of illicit drugs and drug overdose deaths involving cocaine and methamphetamine, Ohio, 2014-2019.

BACKGROUND: The United States continues to experience a crisis of mounting opioid overdose deaths involving cocaine and methamphetamine (hereafter illicit stimulants). Law enforcement drug seizure data present a unique opportunity to examine the association between illicit-stimulant-involved overdose deaths (ISODs) and the illicit drug supply. Our objective is to better understand correlations between illicit drug market trends and increases in ISODs in Ohio in 2014-2019. METHODS: This observational study analyzes the universe of ISODs and drug seizures in Ohio from 2014 to 2019. We use graphs and descriptive statistics to characterize trends over time and estimate a time series model of their association. ISODs were summed to yield monthly statewide counts of seizures containing methamphetamine, cocaine, illicitly manufactured fentanyl (IMF), and other non-IMF opioids (e.g., heroin). All rates were calculated per 100,000 persons. RESULTS: Roughly 80% of ISODs in Ohio from 2014 to 2019 involved an opioid, with IMF co-occurring in 90% of ISODs by 2019. Methamphetamine and cocaine seizures containing IMF were associated with 0.439 (p < .01) and 0.457 (p < .01) additional deaths per 100,000 persons per month, respectively. IMF seizures not containing cocaine nor methamphetamine were also associated with additional ISODs (0.119, p < .01) and seizures of illicit stimulants not containing IMF were not associated with ISODs. CONCLUSIONS: The number of ISODs was extremely high when IMF was co-involved and relatively low without IMF involvement. By demonstrating how supply-side trends correspond with ISOD rates, the current study bolsters the analytical utility of law enforcement seizures and complements growing literature in the field.

Rural and urban differences in undersupply of buprenorphine provider availability in the United States, 2018.

BACKGROUND: Medications to treat opioid use disorder (OUD) including buprenorphine products are evidence-based and cost-effective tools for combating the opioid crisis. However, limited availability to buprenorphine is pervasive in the United States (US) and may serve to exacerbate the deadly epidemic. Although prior research points to rural counties as especially needy of strategies that improve buprenorphine availability, it is important to investigate the availability of waivered providers according to treatment need as defined by the county-level rate of opioid-overdose deaths (OOD). This study examined differences in buprenorphine provider availability relative to treatment need among rural and urban counties in the US. METHODS: Buprenorphine provider availability relative to need in each county was defined as the number of waivered providers divided by the rate of OODs (i.e., number of OODs/100,000 population), according to 2018 data. Counties with ratios in the bottom tertile of their state were classified as buprenorphine undersupplied. We estimated logit models to statistically test the association of rurality and state main effects and their interaction terms (independent variables) and the county classified as buprenorphine undersupplied (dependent variable). RESULTS: A total of 38 states and 2595 counties had sufficient non-suppressed data to remain in the analysis. A larger percent of urban counties (36.43%) than rural counties (32.01%) were classified as buprenorphine undersupplied (p = 0.001). The likelihood of a rural county being undersupplied varied considerably by state (Chi Square = 82.88, p = 0.000). All states with significant (p < 0.05 or p < 0.10) interaction terms showed lower likelihood of buprenorphine undersupply in rural counties. CONCLUSIONS: The rural-urban distribution in undersupply of waivered buprenorphine providers relative to need varied markedly by state. Strategies for improving access to buprenorphine-waivered providers should be state-centric and informed by county-specific indicators of need.

The Relationship Between Reductions in WHO Risk Drinking Levels During Treatment and Subsequent Healthcare Costs for the ACTIVE Workgroup.

BACKGROUND: Abstinence has historically been considered the target outcome for alcohol use disorder (AUD) treatment, yet recent work has found drinking reductions after AUD treatment, as measured by World Health Organization (WHO) risk drinking levels, are associated with meaningful improvements in functioning, physical health, and quality of life. OBJECTIVES: This study extends previous analyses of AUD treatment outcomes by estimating the association between changes in WHO risk drinking levels (very high, high, medium, and low, based on average daily alcohol consumption) and healthcare costs. METHODS: Secondary data analysis of the COMBINE study, a multisite randomized clinical trial of acamprosate, naltrexone and behavioral interventions for AUD. Generalized gamma regression models were used to estimate relationships between WHOrisk drinking level reductions over the course of treatment and healthcare costs in the year after treatment (N = 964) and up to 3 years following treatment (N = 651). RESULTS: SustainedWHOrisk drinking reductions of 2 or more levels throughout treatment were associated with 52.0% lower healthcare costs ( P < 0.001) in the year following treatment, and 44.0% lower costs ( P < 0.0025) over 3 years. A reduction of exactly 1 level was associated with 34.8% lower costs over 3 years, which was not significant ( P = 0.05). Cost reductions were driven by lower inpatient behavioral health and emergency department utilization. CONCLUSIONS: Reduction in WHO risk drinking levels of at least 2 levels was associated with lower healthcare costs over 1 and 3 years. Our results add to literature showing drinking reductions are associated with improvement in health.

Individual and Community Social Determinants of Health and Recovery from Alcohol Use Disorder Three Years following Treatment.

Prior research on recovery from alcohol use disorder (AUD) has often focused on individual-level factors that promote recovery. Given systemic health inequities, it is also important to study community-level social determinants of health (SDOH) that may promote recovery from AUD. This study extended prior work examining individual profiles of recovery from AUD to assess how individual and community SDOH at the time of treatment entry were associated with recovery from AUD three years after treatment. Data were utilized from the COMBINE study (n = 664), a multisite randomized clinical trial evaluating pharmacological and behavioral treatments for AUD. Public community data sources associated with participants' study sites were used to measure community SDOH. Multilevel latent profile analyses with individual- and community-level variables as predictors of recovery profiles were estimated. Four profiles were identified based on participants' alcohol consumption and functioning. Individual SDOH variables, such as fewer years of education and lower income, and community SDOH, including lower rates of health insurance, lower income, and greater income inequality, were each associated with lower functioning profiles. The findings highlight the importance of community SDOH in AUD recovery and the value of including both individual and community SDOH variables in research on long-term recovery.

Stability of Drinking Reductions and Long-term Functioning Among Patients with Alcohol Use Disorder.

BACKGROUND: The World Health Organization (WHO) categorizes alcohol consumption according to grams consumed into low-, medium-, high-, and very-high-risk drinking levels (RDLs). Although abstinence has been considered the ideal outcome of alcohol treatment, reductions in WHO RDLs have been proposed as primary outcomes for alcohol use disorder (AUD) trials. OBJECTIVE: The current study examines the stability of WHO RDL reductions and the association between RDL reductions and long-term functioning for up to 3 years following treatment. DESIGN AND PARTICIPANTS: Secondary data analysis of patients with AUD enrolled in the COMBINE Study and Project MATCH, two multi-site, randomized AUD clinical trials, who were followed for up to 3 years post-treatment (COMBINE: n = 694; MATCH: n = 806). MEASURES: Alcohol use was measured via calendar-based methods. We estimated all models in the total sample and among participants who did not achieve abstinence during treatment. KEY RESULTS: One-level RDL reductions were achieved by 84% of patients at the end of treatment, with 84.9% of those individuals maintaining that reduction at a 3-year follow-up. Two-level RDL reductions were achieved by 68% of patients at the end of treatment, with 77.7% of those individuals maintaining that reduction at a 3-year follow-up. One- and two-level RDL reductions at the end of treatment were associated with significantly better mental health, quality of life (including physical quality of life), and fewer drinking consequences 3 years after treatment (p < 0.05), as compared to no change or increased drinking. CONCLUSION: AUD patients can maintain WHO RDL reductions for up to 3 years after treatment. Patients who had WHO RDL reductions functioned significantly better than those who did not reduce their drinking. These findings are consistent with prior reports suggesting that drinking reductions, short of abstinence, yield meaningful improvements in patient health, well-being, and functioning.

Health economic design for cost, cost-effectiveness and simulation analyses in the HEALing Communities Study.

BACKGROUND: The HEALing Communities Study (HCS) is designed to implement and evaluate the Communities That HEAL (CTH) intervention, a conceptually driven framework to assist communities in selecting and adopting evidence-based practices to reduce opioid overdose deaths. The goal of the HCS is to produce generalizable information for policy makers and community stakeholders seeking to implement CTH or a similar community intervention. To support this objective, one aim of the HCS is a health economics study (HES), the results of which will inform decisions around fiscal feasibility and sustainability relevant to other community settings. METHODS: The HES is integrated into the HCS design: an unblinded, multisite, parallel arm, cluster randomized, wait list-controlled trial of the CTH intervention implemented in 67 communities in four U.S. states: Kentucky, Massachusetts, New York, and Ohio. The objectives of the HES are to estimate the economic costs to communities of implementing and sustaining CTH; estimate broader societal costs associated with CTH; estimate the cost-effectiveness of CTH for overdose deaths avoided; and use simulation modeling to evaluate the short- and long-term health and economic impact of CTH, including future overdose deaths avoided and quality-adjusted life years saved, and to develop a simulation policy tool for communities that seek to implement CTH or a similar community intervention. DISCUSSION: The HCS offers an unprecedented opportunity to conduct health economics research on solutions to the opioid crisis and to increase understanding of the impact and value of complex, community-level interventions.

Can Alcohol Use Disorder Recovery Include Some Heavy Drinking? A Replication and Extension up to 9 Years Following Treatment.

BACKGROUND: Recent research indicates some individuals who engage in heavy drinking following treatment for alcohol use disorder fare as well as those who abstain with respect to psychosocial functioning, employment, life satisfaction, and mental health. The current study evaluated whether these findings replicated in an independent sample and examined associations between recovery profiles and functioning up to 6 years later. METHODS: Data were from the 3-year and 7- to 9-year follow-ups of subsamples initially recruited for the COMBINE study (3-year follow-up: n = 694; 30.1% female, 21.0% non-White; 7- to 9-year follow-up: n = 127; 38.9% female, 27.8% non-White). Recovery at 3 years was defined by latent profile analyses including measures of health functioning, quality of life, employment, alcohol consumption, and cannabis and other drug use. Functioning at the 7- to 9-year follow-up was assessed using single items of self-rated general health, hospitalizations, and alcohol consumption. RESULTS: We identified 4 profiles at the 3-year follow-up: (i) low-functioning frequent heavy drinkers (13.9%), (ii) low-functioning infrequent heavy drinkers (15.8%), (iii) high-functioning heavy drinkers (19.4%), and (iv) high-functioning infrequent drinkers (50.9%). At the 7- to 9-year follow-up, the 2 high-functioning profiles had the best self-rated health, and the high-functioning heavy drinking profile had significantly fewer hospitalizations than the low-functioning frequent heavy drinking profile. CONCLUSIONS: Previous findings showing heterogeneity in recovery outcomes were replicated. Most treatment recipients functioned well for years after treatment, and a subset who achieved stable recovery engaged in heavy drinking and reported good health outcomes up to 9 years after treatment. Results question the long-standing emphasis on drinking practices as a primary outcome, as well as abstinence as a recovery criterion in epidemiologic and treatment outcome research and among stakeholder groups and funding/regulatory agencies. Findings support an expanded recovery research agenda that considers drinking patterns, health, life satisfaction, and functioning.

Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study.

BACKGROUND: Over the last two decades, deaths associated with opioids have escalated in number and geographic spread, impacting more and more individuals, families, and communities. Reflecting on the shifting nature of the opioid overdose crisis, Dasgupta, Beletsky, and Ciccarone offer a triphasic framework to explain that opioid overdose deaths (OODs) shifted from prescription opioids for pain (beginning in 2000), to heroin (2010 to 2015), and then to synthetic opioids (beginning in 2013). Given the rapidly shifting nature of OODs, timelier surveillance data are critical to inform strategies that combat the opioid crisis. Using easily accessible and near real-time social media data to improve public health surveillance efforts related to the opioid crisis is a promising area of research. OBJECTIVE: This study explored the potential of using Twitter data to monitor the opioid epidemic. Specifically, this study investigated the extent to which the content of opioid-related tweets corresponds with the triphasic nature of the opioid crisis and correlates with OODs in North Carolina between 2009 and 2017. METHODS: Opioid-related Twitter posts were obtained using Crimson Hexagon, and were classified as relating to prescription opioids, heroin, and synthetic opioids using natural language processing. This process resulted in a corpus of 100,777 posts consisting of tweets, retweets, mentions, and replies. Using a random sample of 10,000 posts from the corpus, we identified opioid-related terms by analyzing word frequency for each year. OODs were obtained from the Multiple Cause of Death database from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER). Least squares regression and Granger tests compared patterns of opioid-related posts with OODs. RESULTS: The pattern of tweets related to prescription opioids, heroin, and synthetic opioids resembled the triphasic nature of OODs. For prescription opioids, tweet counts and OODs were statistically unrelated. Tweets mentioning heroin and synthetic opioids were significantly associated with heroin OODs and synthetic OODs in the same year (P=.01 and P<.001, respectively), as well as in the following year (P=.03 and P=.01, respectively). Moreover, heroin tweets in a given year predicted heroin deaths better than lagged heroin OODs alone (P=.03). CONCLUSIONS: Findings support using Twitter data as a timely indicator of opioid overdose mortality, especially for heroin.

Recovery From Opioid Use Disorder (OUD) After Monthly Long-acting Buprenorphine Treatment: 12-Month Longitudinal Outcomes From RECOVER, an Observational Study.

OBJECTIVES: While evidence has mounted regarding the short-term effectiveness of pharmacotherapy for opioid use disorder (OUD), little is known about longer-term psychosocial, economic, and health outcomes. We report herein 12-month outcomes for an observational study enrolling participants who had previously taken part in a long-acting buprenorphine subcutaneous injection (BUP-XR) trial for moderate to severe OUD. METHODS: The RECOVER (Remission from Chronic Opioid Use: Studying Environmental and SocioEconomic Factors on Recovery; NCT03604861) study enrolled participants from 35 US community-based sites. Self-reported sustained opioid abstinence over 12 months and self-reported past-week abstinence at 3-, 6-, 9-, and 12-month visits were assessed. Multiple regression models assessed the association of BUP-XR duration with abstinence, controlling for potential confounders. Withdrawal, pain, health-related quality of life, depression, and employment at RECOVER baseline and 12-month visits were also compared to values collected before treatment in the BUP-XR trial. RESULTS: Of 533 RECOVER participants, 425 completed the 12-month visit (average age 42 years; 66% male); 50.8% self-reported sustained 12-month and 68.0% past-week opioid abstinence. In multiple regressions, participants receiving 12-month versus ≤2-month BUP-XR treatment duration had significantly higher likelihood of sustained opioid abstinence (75.3% vs 24.1%; P = 0.001), with similar results for past-week self-reported abstinence over time. During RECOVER, participants had fewer withdrawal symptoms, lower pain, positive health-related quality of life, minimal depression, and higher employment versus pre-trial visit. CONCLUSIONS: RECOVER participants reported positive outcomes over the 12-month observational period, including high opioid abstinence and stable or improved humanistic outcomes. These findings provide insights into the long-term impact of pharmacotherapy in OUD recovery.