Evaluation of Strategies to Enhance Community-Based Naloxone Distribution Supported by an Opioid Settlement.

Importance: Many US states are substantially increasing community-based naloxone distribution, supported in part through settlements from opioid manufacturers and distributors. Objectives: To evaluate the potential impact of increased naloxone availability on opioid overdose deaths (OODs) and explore strategies to enhance this impact by integrating interventions to address solitary drug use. Design, Setting, and Participants: This decision analytical modeling study used PROFOUND (Prevention and Rescue of Fentanyl and Other Opioid Overdoses Using Optimized Naloxone Distribution Strategies), a previously published simulation model, to forecast annual OODs between January 2023 and December 2025. The simulated study population included individuals from Rhode Island who misused opioids and stimulants and were at risk for opioid overdose. Exposures: The study modeled expanded naloxone distribution supported by the state's opioid settlement (50 000 naloxone nasal spray kits each year). Two approaches to expanding naloxone distribution were evaluated: one based on historical spatial patterns of naloxone distribution (supply-based approach) and one based on the spatial distribution of individuals at risk (demand-based approach). In addition, hypothetical interventions to enhance the likelihood of witnessed overdoses in private or semiprivate settings were considered. Main Outcomes and Measures: Annual number of OODs and ratio of fatal to nonfatal opioid overdoses. Results: Modeling results indicated that distributing more naloxone supported by the state's opioid settlement could reduce OODs by 6.3% (95% simulation interval [SI], 0.3%-13.7%) and 8.8% (95% SI, 1.8%-17.5%) in 2025 with the supply-based and demand-based approaches, respectively. However, increasing witnessed overdoses by 20% to 60% demonstrated greater potential for reducing OODs, ranging from 8.5% (95% SI, 0.0%-20.3%) to 24.1% (95% SI, 8.6%-39.3%). Notably, synergistic associations were observed when combining both interventions: increased naloxone distribution with the 2 approaches and a 60% increase in witnessed overdoses could reduce OODs in 2025 by 33.5% (95% SI, 17.1%-50.4%) and 37.4% (95% SI, 19.6%-56.3%), respectively. Conclusions and Relevance: These findings suggest that interventions to address solitary drug use are needed to maximize the impact of continued efforts to increase community-based naloxone distribution, which may be particularly important for jurisdictions that have strong community-based naloxone distribution programs.

Public Health Dashboards in Overdose Prevention: The Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action.

As the field of public health rises to the demands of real-time surveillance and rapid data-sharing needs in a postpandemic world, it is time to examine our approaches to the dissemination and accessibility of such data. Distinct challenges exist when working to develop a shared public health language and narratives based on data. It requires that we assess our understanding of public health data literacy, revisit our approach to communication and engagement, and continuously evaluate our impact and relevance. Key stakeholders and cocreators are critical to this process and include people with lived experience, community organizations, governmental partners, and research institutions. In this viewpoint paper, we offer an instructive approach to the tools we used, assessed, and adapted across 3 unique overdose data dashboard projects in Rhode Island, United States. We are calling this model the "Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action." This approach reflects the iterative lessons learned about the improvement of data dashboards through collaboration and strong partnerships across community members, state agencies, and an academic research team. We will highlight key tools and approaches that are accessible and engaging and allow developers and stakeholders to self-assess their goals for their data dashboards and evaluate engagement with these tools by their desired audiences and users.

PROVIDENT: Development and Validation of a Machine Learning Model to Predict Neighborhood-level Overdose Risk in Rhode Island.

BACKGROUND: Drug overdose persists as a leading cause of death in the United States, but resources to address it remain limited. As a result, health authorities must consider where to allocate scarce resources within their jurisdictions. Machine learning offers a strategy to identify areas with increased future overdose risk to proactively allocate overdose prevention resources. This modeling study is embedded in a randomized trial to measure the effect of proactive resource allocation on statewide overdose rates in Rhode Island (RI). METHODS: We used statewide data from RI from 2016 to 2020 to develop an ensemble machine learning model predicting neighborhood-level fatal overdose risk. Our ensemble model integrated gradient boosting machine and super learner base models in a moving window framework to make predictions in 6-month intervals. Our performance target, developed a priori with the RI Department of Health, was to identify the 20% of RI neighborhoods containing at least 40% of statewide overdose deaths, including at least one neighborhood per municipality. The model was validated after trial launch. RESULTS: Our model selected priority neighborhoods capturing 40.2% of statewide overdose deaths during the test periods and 44.1% of statewide overdose deaths during validation periods. Our ensemble outperformed the base models during the test periods and performed comparably to the best-performing base model during the validation periods. CONCLUSIONS: We demonstrated the capacity for machine learning models to predict neighborhood-level fatal overdose risk to a degree of accuracy suitable for practitioners. Jurisdictions may consider predictive modeling as a tool to guide allocation of scarce resources.

Translating Predictive Analytics for Public Health Practice: A Case Study of Overdose Prevention in Rhode Island.

Prior applications of machine learning to population health have relied on conventional model assessment criteria, limiting the utility of models as decision support tools for public health practitioners. To facilitate practitioners' use of machine learning as a decision support tool for area-level intervention, we developed and applied 4 practice-based predictive model evaluation criteria (implementation capacity, preventive potential, health equity, and jurisdictional practicalities). We used a case study of overdose prevention in Rhode Island to illustrate how these criteria could inform public health practice and health equity promotion. We used Rhode Island overdose mortality records from January 2016-June 2020 (n = 1,408) and neighborhood-level US Census data. We employed 2 disparate machine learning models, Gaussian process and random forest, to illustrate the comparative utility of our criteria to guide interventions. Our models predicted 7.5%-36.4% of overdose deaths during the test period, illustrating the preventive potential of overdose interventions assuming 5%-20% statewide implementation capacities for neighborhood-level resource deployment. We describe the health equity implications of use of predictive modeling to guide interventions along the lines of urbanicity, racial/ethnic composition, and poverty. We then discuss considerations to complement predictive model evaluation criteria and inform the prevention and mitigation of spatially dynamic public health problems across the breadth of practice. This article is part of a Special Collection on Mental Health.

Brief Report: Use of Pre-Exposure Prophylaxis to Prevent Rapid HIV Transmission Among People Who Inject Drugs in Rural Counties in the United States: A Modeling Study.

BACKGROUND: Despite recent HIV outbreaks among people who inject drugs (PWID) in nonurban US settings, syringe service programs (SSP) are often inaccessible in these communities. Furthermore, pre-exposure prophylaxis (PrEP) awareness and coverage for PWID is limited. We aimed to model the impact of PrEP on HIV transmission among PWID in a rural setting. SETTING: Using a calibrated agent-based model, we simulated HIV transmission in an adult population (n = 14,573 agents) in Scott County, Indiana between 2015 and 2024. METHODS: We modeled PrEP eligibility according to CDC guidelines for PWID. PrEP coverage increased by 15% points in the range 10%-70%. Two counterfactual scenarios were modeled: Unrestricted access for PWID and PrEP for SSP attendees . We calculated the number of new HIV infections and number of person-years on PrEP per averted infection. RESULTS: In the status quo scenario, 153 (95% Simulation Interval: 85, 259) new HIV infections occurred among PWID over 10 years. Compared with the status quo, 40% PrEP coverage resulted in 25% fewer HIV infections in the Unrestricted access for PWID scenario and 10% fewer HIV infections in the PrEP for SSP attendees scenario. The PYPAI was 21 and 43 in the Unrestricted access for PWID and PrEP for SSP attendees scenarios, respectively. CONCLUSION: Our modeling suggests that PrEP provides substantial benefit to PWID in rural US communities, with fewer restrictions on access providing the greatest effect. Control of HIV outbreaks will require expansion of public health interventions that meet the needs of all individuals.

Preventing Overdose Using Information and Data from the Environment (PROVIDENT): protocol for a randomized, population-based, community intervention trial.

BACKGROUND AND AIMS: In light of the accelerating drug overdose epidemic in North America, new strategies are needed to identify communities most at risk to prioritize geographically the existing public health resources (e.g. street outreach, naloxone distribution efforts). We aimed to develop PROVIDENT (Preventing Overdose using Information and Data from the Environment), a machine learning-based forecasting tool to predict future overdose deaths at the census block group (i.e. neighbourhood) level. DESIGN: Randomized, population-based, community intervention trial. SETTING: Rhode Island, USA. PARTICIPANTS: All people who reside in Rhode Island during the study period may contribute data to either the model or the trial outcomes. INTERVENTION: Each of the state's 39 municipalities will be randomized to the intervention (PROVIDENT) or comparator condition. An interactive, web-based tool will be developed to visualize the PROVIDENT model predictions. Municipalities assigned to the treatment arm will receive neighbourhood risk predictions from the PROVIDENT model, and state agencies and community-based organizations will direct resources to neighbourhoods identified as high risk. Municipalities assigned to the control arm will continue to receive surveillance information and overdose prevention resources, but they will not receive neighbourhood risk predictions. MEASUREMENTS: The primary outcome is the municipal-level rate of fatal and non-fatal drug overdoses. Fatal overdoses will be defined as unintentional drug-related death; non-fatal overdoses will be defined as an emergency department visit for a suspected overdose reported through the state's syndromic surveillance system. Intervention efficacy will be assessed using Poisson or negative binomial regression to estimate incidence rate ratios comparing fatal and non-fatal overdose rates in treatment vs. control municipalities. COMMENTS: The findings will inform the utility of predictive modelling as a tool to improve public health decision-making and inform resource allocation to communities that should be prioritized for prevention, treatment, recovery and overdose rescue services.

Comparison of Characteristics of Deaths From Drug Overdose Before vs During the COVID-19 Pandemic in Rhode Island.

Importance: The rate of deaths from overdose has increased during the COVID-19 pandemic, and recent US overdose mortality rates have been markedly high. However, scant data are available on the causes of this increase or subpopulations at elevated risk. Objective: To evaluate the rates and characteristics of deaths from drug overdose before vs during the COVID-19 pandemic. Design, Setting, and Participants: This retrospective, population-based cohort study used data from 4 statewide databases linked at the person level via the Rhode Island Data Ecosystem on adults with deaths due to overdose in Rhode Island from January 1 to August 31, 2019, and January 1 to August 31, 2020. Main Outcomes and Measures: The rates of unintentional deaths from drug-related overdose during the 2019 and 2020 observation periods overall and by sociodemographic characteristics, drugs contributing to the cause of death, location of death, and socioeconomic factors were evaluated. In subgroup analyses restricted to Medicaid beneficiaries (n = 271), the proportions of deaths from overdose by behavioral health treatment and diagnosis claims in the year before death were also examined. Results: A total of 470 adults who died of drug overdose were included in the analysis (353 men [75%]; mean [SD] age, 43.5 [12.1] years). The rate of deaths from overdose in Rhode Island increased 28.1%, from 29.2 per 100 000 person-years in 2019 to 37.4 per 100 000 person-years in 2020 (P = .009). Compared with 2019, rates of deaths due to overdose during 2020 were higher among men (43.2 vs 59.2 per 100 000 person-years; P = .003), non-Hispanic White individuals (31.0 vs 42.0 per 100 000 person-years; P = .005), single individuals (54.8 vs 70.4 per 100 000 person-years; P = .04), deaths involving synthetic opioids (20.8 vs 28.3 per 100 000 person-years; P = .005), and deaths occurring in a personal residence (13.2 vs 19.7 per 100 000 person-years; P = .003). A decrease in the proportion of deaths from overdose involving heroin (11 of 206 [5%] vs <2% [exact value suppressed]; P = .02) and an increase among persons experiencing job loss (16 of 206 [8%] vs 41 of 264 [16%]; P = .01) from 2019 to 2020 were observed. Among individuals who died of overdose and were Medicaid beneficiaries, the proportions of those aged 50 to 59 years with anxiety (11 of 121 [9%] vs 29 of 150 [19%]; P = .03), men with depression (27 of 121 [22%] vs 57 of 150 [38%]; P = .008), and men with anxiety (28 of 121 [23%] vs 55 of 150 [37%]; P = .02) increased during 2020 compared with 2019. Conclusions and Relevance: In this cohort study, during the first 8 months of 2020, the rate of deaths from overdose increased in Rhode Island compared with the same period in 2019, and several emerging characteristics of deaths from drug overdose during the first year of the COVID-19 pandemic were identified. These findings may inform interventions that address macroenvironmental changes associated with the pandemic.

Machine learning takes a village: Assessing neighbourhood-level vulnerability for an overdose and infectious disease outbreak.

BACKGROUND: Multiple areas in the United States of America (USA) are experiencing high rates of overdose and outbreaks of bloodborne infections, including HIV and hepatitis C virus (HCV), due to non-sterile injection drug use. We aimed to identify neighbourhoods at increased vulnerability for overdose and infectious disease outbreaks in Rhode Island, USA. The primary aim was to pilot machine learning methods to identify which neighbourhood-level factors were important for creating "vulnerability assessment scores" across the state. The secondary aim was to engage stakeholders to pilot an interactive mapping tool and visualize the results. METHODS: From September 2018 to November 2019, we conducted a neighbourhood-level vulnerability assessment and stakeholder engagement process named The VILLAGE Project (Vulnerability Investigation of underlying Local risk And Geographic Events). We developed a predictive analytics model using machine learning methods (LASSO, Elastic Net, and RIDGE) to identify areas with increased vulnerability to an outbreak of overdose, HIV and HCV, using census tract-level counts of overdose deaths as a proxy for injection drug use patterns and related health outcomes. Stakeholders reviewed mapping tools for face validity and community distribution. RESULTS: Machine learning prediction models were suitable for estimating relative neighbourhood-level vulnerability to an outbreak. Variables of importance in the model included housing cost burden, prior overdose deaths, housing density, and education level. Eighty-nine census tracts (37%) with no prior overdose fatalities were identified as being vulnerable to such an outbreak, and nine of those were identified as having a vulnerability assessment score in the top 25%. Results were disseminated as a vulnerability stratification map and an online interactive mapping tool. CONCLUSION: Machine learning methods are well suited to predict neighborhoods at higher vulnerability to an outbreak. These methods show promise as a tool to assess structural vulnerabilities and work to prevent outbreaks at the local level.

Network structure and rapid HIV transmission among people who inject drugs: A simulation-based analysis.

As HIV incidence among people who inject drugs grows in the context of an escalating drug overdose epidemic in North America, investigating how network structure may affect vulnerability to rapid HIV transmission is necessary for preventing outbreaks. We compared the characteristics of the observed contact tracing network from the 2015 outbreak in rural Indiana with 1000 networks generated by an agent-based network model with approximately the same number of individuals (n = 420) and ties between them (n = 913). We introduced an initial HIV infection into the simulated networks and compared the subsequent epidemic behavior (e.g., cumulative HIV infections over 5 years). The model was able to produce networks with largely comparable characteristics and total numbers of incident HIV infections. Although the model was unable to produce networks with comparable cohesiveness (where the observed network had a transitivity value 35.7 standard deviations from the mean of the simulated networks), the structural variability of the simulated networks allowed for investigation into their potential facilitation of HIV transmission. These findings emphasize the need for continued development of injection network simulation studies in tandem with empirical data collection to further investigate how network characteristics played a role in this and future outbreaks.

Predictors of enrollment in opioid agonist therapy after opioid overdose or diagnosis with opioid use disorder: A cohort study.

BACKGROUND: Medicaid recipients have a high burden of opioid overdose and opioid use disorder (OUD). Opioid agonist therapies are an effective treatment for OUD, but there is a wide and persisting gap between those who are indicated and those who receive treatment. The objective of this study was to identify the predictors of enrollment in opioid agonist therapy within 6 months of an opioid overdose or OUD diagnosis in a cohort of Medicaid recipients. METHODS: Using multiple linked, state-level databases, we conducted a retrospective cohort study of 17,449 Medicaid recipients in Rhode Island who had an opioid overdose or an OUD diagnosis between July 2013 and June 2018. RESULTS: The majority (58 %) of Medicaid recipients did not enroll in opioid agonist therapy within 6 months. In adjusted models, having one or more prior overdose (adjusted risk ratio [ARR] = 0.33, 95 % CI: 0.28, 0.38), alcohol use disorder (ARR = 0.56, 95 % CI: 0.52, 0.60), or back problems (ARR = 0.58, 95 % CI: 0.55, 0.61) were strong predictors of non-enrollment. Conversely, emergency department (ARR = 1.31, 95 % CI: 1.28-1.34) and primary care provider (ARR = 1.03, 95 % CI: 1.01-1.34) visit frequency above the 75th percentile were associated with timely enrollment in opioid agonist therapy. CONCLUSIONS: Our findings underscore the need to enhance pathways to treatment for OUD through varied nodes of engagement with healthcare systems. Interventions to improve screening for OUD and referrals to opioid agonist therapies should include high-impact settings, such as treatment programs for alcohol and substance use disorders, pain clinics, and outpatient behavioral care settings.

A randomized clinical trial of a theory-based fentanyl overdose education and fentanyl test strip distribution intervention to reduce rates of opioid overdose: study protocol for a randomized controlled trial.

BACKGROUND: Opioid overdose deaths involving synthetic opioids, particularly illicitly manufactured fentanyl, remain a substantial public health concern in North America. Responses to overdose events (e.g., administration of naloxone and rescue breathing) are effective at reducing mortality; however, more interventions are needed to prevent overdoses involving illicitly manufactured fentanyl. This study protocol aims to evaluate the effectiveness of a behavior change intervention that incorporates individual counseling, practical training in fentanyl test strip use, and distribution of fentanyl test strips for take-home use among people who use drugs. METHODS: Residents of Rhode Island aged 18-65 years who report recent substance use (including prescription pills obtained from the street; heroin, powder cocaine, crack cocaine, methamphetamine; or any drug by injection) (n = 500) will be recruited through advertisements and targeted street-based outreach into a two-arm randomized clinical trial with 12 months of post-randomization follow-up. Eligible participants will be randomized (1:1) to receive either the RAPIDS intervention (i.e., fentanyl-specific overdose education, behavior change motivational interviewing (MI) sessions focused on using fentanyl test strips to reduce overdose risk, fentanyl test strip training, and distribution of fentanyl test strips for personal use) or standard overdose education as control. Participants will attend MI booster sessions (intervention) or attention-matched control sessions at 1, 2, and 3 months post-randomization. All participants will be offered naloxone at enrolment. The primary outcome is a composite measure of self-reported overdose in the previous month at 6- and/or 12-month follow-up visit. Secondary outcome measures include administratively linked data regarding fatal (post-mortem investigation) and non-fatal (hospitalization or emergency medical service utilization) overdoses. DISCUSSION: If the RAPIDS intervention is found to be effective, its brief MI and fentanyl test strip training components could be easily incorporated into existing community-based overdose prevention programming to help reduce the rates of fentanyl-related opioid overdose. TRIAL REGISTRATION: ClinicalTrials.gov NCT04372238 . Registered on 01 May 2020.

US drug overdose mortality: 2009-2018 increases affect young people who use drugs.

PURPOSE: Drug overdose mortality remains a public health concern in many countries globally. In the US, overdoses involving synthetic opioids are the primary contributor to overdose mortality. We aimed to assess trends in overdose death due to synthetic opioids among young people and describe key demographic and temporal changes. METHODS: Data from the US National Vital Statistics System Multiple Cause of Death files for 2009-2018 were analysed to determine age-specific overdose death rates by region (i.e. east versus west of the Mississippi River). Age-adjusted overdose mortality rates were used to compare demographic differences in all drug and synthetic opioid overdose among young people (aged 15-34 years) using a joinpoint regression with Poisson-approximated standard errors. RESULTS: Driven by synthetic opioid overdose, the age burden of mortality shifted towards young people in eastern states and remained approximately constant in western states over the study period. The highest increases in drug overdose mortality rates were observed in young Black and Hispanic people and those living in large metropolitan areas. CONCLUSIONS: Rapid changes in the demographics of overdose demonstrate distinct but overlapping US overdose sub-epidemics, and highlight the need for targeted interventions to reduce overdose risk in young people.

Randomised clinical trial of an emergency department-based peer recovery support intervention to increase treatment uptake and reduce recurrent overdose among individuals at high risk for opioid overdose: study protocol for the navigator trial.

INTRODUCTION: Effective approaches to increase engagement in treatment for opioid use disorder (OUD) and reduce the risk of recurrent overdose and death following emergency department (ED) presentation for opioid overdose remain unknown. As such, we aim to compare the effectiveness of behavioural interventions delivered in the ED by certified peer recovery support specialists relative to those delivered by licensed clinical social workers (LCSWs) in promoting OUD treatment uptake and reducing recurrent ED visits for opioid overdose. METHODS AND ANALYSIS: Adult ED patients who are at high risk for opioid overdose (ie, are being treated for an opioid overdose or identified by the treating physician as having OUD) (n=650) will be recruited from two EDs in a single healthcare system in Providence, Rhode Island into a two-arm randomised trial with 18 months of follow-up postrandomisation. Eligible participants will be randomly assigned (1:1) in the ED to receive a behavioural intervention from a certified peer recovery support specialist or a behavioural intervention from an LCSW. The primary outcomes are engagement in formal OUD treatment within 30 days of the initial ED visit and recurrent ED visits for opioid overdose within 18 months of the initial ED visit, as measured through statewide administrative records. ETHICS AND DISSEMINATION: This protocol was approved by the Rhode Island Hospital institutional review board (Approval Number: 212418). Data will be presented at national and international conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT03684681.

Defining a recovery-oriented cascade of care for opioid use disorder: A community-driven, statewide cross-sectional assessment.

BACKGROUND: In light of the accelerating and rapidly evolving overdose crisis in the United States (US), new strategies are needed to address the epidemic and to efficiently engage and retain individuals in care for opioid use disorder (OUD). Moreover, there is an increasing need for novel approaches to using health data to identify gaps in the cascade of care for persons with OUD. METHODS AND FINDINGS: Between June 2018 and May 2019, we engaged a diverse stakeholder group (including directors of statewide health and social service agencies) to develop a statewide, patient-centered cascade of care for OUD for Rhode Island, a small state in New England, a region highly impacted by the opioid crisis. Through an iterative process, we modified the cascade of care defined by Williams et al. for use in Rhode Island using key national survey data and statewide health claims datasets to create a cross-sectional summary of 5 stages in the cascade. Approximately 47,000 Rhode Islanders (5.2%) were estimated to be at risk for OUD (stage 0) in 2016. At the same time, 26,000 Rhode Islanders had a medical claim related to an OUD diagnosis, accounting for 55% of the population at risk (stage 1); 27% of the stage 0 population, 12,700 people, showed evidence of initiation of medication for OUD (MOUD, stage 2), and 18%, or 8,300 people, had evidence of retention on MOUD (stage 3). Imputation from a national survey estimated that 4,200 Rhode Islanders were in recovery from OUD as of 2016, representing 9% of the total population at risk. Limitations included use of self-report data to arrive at estimates of the number of individuals at risk for OUD and using a national estimate to identify the number of individuals in recovery due to a lack of available state data sources. CONCLUSIONS: Our findings indicate that cross-sectional summaries of the cascade of care for OUD can be used as a health policy tool to identify gaps in care, inform data-driven policy decisions, set benchmarks for quality, and improve health outcomes for persons with OUD. There exists a significant opportunity to increase engagement prior to the initiation of OUD treatment (i.e., identification of OUD symptoms via routine screening or acute presentation) and improve retention and remission from OUD symptoms through improved community-supported processes of recovery. To do this more precisely, states should work to systematically collect data to populate their own cascade of care as a health policy tool to enhance system-level interventions and maximize engagement in care.

Prevalence and Correlates of Depressive Symptomology among Young Adults Who Use Prescription Opioids Non-medically.

Non-medical prescription opioid (NMPO) use and depression frequently co-occur and are mutually reinforcing in adults, yet NMPO use and depression in younger populations has been under-studied. We examined the prevalence and correlates of depressive symptomology among NMPO-using young adults. The Rhode Island Young Adult Prescription Drug Study (RAPiDS) recruited young adults in Rhode Island who reported past 30-day NMPO use. We administered the Center for Epidemiologic Studies Short Depression Scale (CES-D 10), and used modified Poisson regression to identify the independent correlates of depressive symptomology (CES-D 10 score ≥10). Over half (59.8%, n = 119) screened positive for depressive symptomology. In modified Poisson regression analysis, diagnostic history of depressive disorder and childhood verbal abuse were associated with depressive symptomology. Participants with depressive symptomology were more likely to report using prescription opioids non-medically to feel less depressed or anxious, to avoid withdrawal symptoms, and as a substitute when other drugs are not available. Among young adult NMPO users, depressive symptomology is prevalent and associated with distinct motivations for engaging in NMPO use and represents a potential subgroup for intervention. Improving guidelines with tools such as screening for depressive symptomology among young adult NMPO users may help prevent NMPO-related harms.

Perspectives on rapid fentanyl test strips as a harm reduction practice among young adults who use drugs: a qualitative study.

BACKGROUND: In 2016, drug overdose deaths exceeded 64,000 in the United States, driven by a sixfold increase in deaths attributable to illicitly manufactured fentanyl. Rapid fentanyl test strips (FTS), used to detect fentanyl in illicit drugs, may help inform people who use drugs about their risk of fentanyl exposure prior to consumption. This qualitative study assessed perceptions of FTS among young adults. METHODS: From May to September 2017, we recruited a convenience sample of 93 young adults in Rhode Island (age 18-35 years) with self-reported drug use in the past 30 days to participate in a pilot study aimed at better understanding perspectives of using take-home FTS for personal use. Participants completed a baseline quantitative survey, then completed a training to learn how to use the FTS. Participants then received ten FTS for personal use and were asked to return 2-4 weeks later to complete a brief quantitative and structured qualitative interview. Interviews were transcribed, coded, and double coded in NVivo (Version 11). RESULTS: Of the 81 (87%) participants who returned for follow-up, the majority (n = 62, 77%) used at least one FTS, and of those, a majority found them to be useful and straightforward to use. Positive FTS results led some participants to alter their drug use behaviors, including discarding their drug supply, using with someone else, and keeping naloxone nearby. Participants also reported giving FTS to friends who they felt were at high risk for fentanyl exposure. CONCLUSION: These findings provide important perspectives on the use of FTS among young adults who use drugs. Given the high level of acceptability and behavioral changes reported by study participants, FTS may be a useful harm reduction intervention to reduce fentanyl overdose risk among this population. TRIAL REGISTRATION: The study protocol is registered with the US National Library of Medicine, Identifier NCT03373825, 12/24/2017, registered retrospectively. https://clinicaltrials.gov/ct2/show/NCT03373825?id=NCT03373825&rank=1.

Implementing peer recovery services for overdose prevention in Rhode Island: An examination of two outreach-based approaches.

BACKGROUND: Rhode Island has the tenth highest rate of accidental drug overdose deaths in the United States. In response to this crisis, Anchor Recovery Center, a community-based peer recovery program, developed programs deploying certified Peer Recovery Specialists to emergency departments (AnchorED) and communities with high rates of accidental opioid overdoses (AnchorMORE). OBJECTIVES: The purpose of this paper is to describe AnchorED and AnchorMORE's activities and implementation process. METHODS: AnchorED data were analyzed from a standard enrollment questionnaire that includes participant contact information, demographics, and a needs assessment. The AnchorED program outcomes include number of clients enrolled, number of naloxone training sessions, and number of referrals to recovery and treatment services. Overdose deaths and naloxone distribution through AnchorMORE were mapped using Tableau software. RESULTS: From July 2016-June 2017, AnchorED had 1329 contacts with patients visiting an emergency department for reported substance misuse cases or suspected overdose. Among the contacts, 88.7% received naloxone training and 86.8% agreed to continued outreach with a Peer Recovery Specialist after their ED discharge. Of those receiving peer recovery services from the Anchor Recovery Community Center, 44.7% (n = 1055/2362) were referred from an AnchorED contact. From July 2016-June 2017, AnchorMORE distributed 854 naloxone kits in high-risk communities and provided 1311 service referrals. CONCLUSION: These findings indicate the potential impact peer recovery programs may have on engaging high-risk populations in treatment, overdose prevention, and other harm reduction activities. Additional research is needed to evaluate the reach of implementation and services uptake.

Action-focused, plain language communication for overdose prevention: A qualitative analysis of Rhode Island's overdose surveillance and information dashboard.

BACKGROUND: In 2015, the state of Rhode Island reported the fifth highest drug overdose mortality rate in the United States. In response to this crisis, Rhode Island created a statewide, publicly accessible drug surveillance and information system, www.PreventOverdoseRI.org (PORI). Alongside near real-time overdose surveillance data, PORI provides plain language materials and resources regarding overdose prevention, recognition and response. We sought to determine how people who use drugs (PWUD) perceive and utilize overdose prevention material, and to evaluate PORI's action-based, plain language content. METHODS: We conducted 21 semi-structured qualitative interviews with PWUD from February-June 2017 in the state of Rhode Island. Data were audio-recorded, transcribed, coded in NVivo (Version 11), and key themes were developed. RESULTS: Participants viewed online health promotion and harm reduction materials as a useful approach for overdose prevention. Information displayed as accessible, action-driven statements was seen as most desirable for learning and dissemination. After viewing overdose prevention material, participants reported feeling better prepared for responding to an accidental overdose and motivated to share the infographics and website to other people either at risk for or likely to witness an overdose. CONCLUSION: Action-focused, plain language approaches for overdose prevention materials can be of particular use for public health campaigns addressing opioid overdose crises. Overdose prevention health campaigns should incorporate evidence-based testing to ensure that outreach material is grounded in plain language techniques.

High willingness to use rapid fentanyl test strips among young adults who use drugs.

BACKGROUND: Synthetic opioid overdose mortality among young adults has risen more than 300% in the USA since 2013, primarily due to the contamination of heroin and other drugs with illicitly manufactured fentanyl. Rapid test strips, which can be used to detect the presence of fentanyl in drug samples (before use) or urine (after use), may help inform people about their exposure risk. The purpose of this study was to determine whether young adults who use drugs were willing to use rapid test strips as a harm reduction intervention to prevent overdose. We hypothesized that those who had ever overdosed would be more willing to use the test strips. METHODS: We recruited a convenience sample of young adults who use drugs in Rhode Island from May to September 2017. Eligible participants (aged 18 to 35 with past 30-day drug use) completed an interviewer-administered survey. The survey assessed participant's socio-demographic and behavioral characteristics, overdose risk, as well as suspected fentanyl exposure, and willingness to use take-home rapid test strips to detect fentanyl contamination in drugs or urine. Participants were then trained to use the test strips and were given ten to take home. RESULTS: Among 93 eligible participants, the mean age was 27 years (SD = 4.8), 56% (n = 52) of participants were male, and 56% (n = 52) were white. Over one third (n = 34, 37%) had a prior overdose. The vast majority (n = 86, 92%) of participants wanted to know if there was fentanyl in their drug supply prior to their use. Sixty-five (70%) participants reported concern that their drugs were contaminated with fentanyl. After the brief training, nearly all participants (n = 88, 95%) reported that they planned to use the test strips. CONCLUSIONS: More than 90% of participants reported willingness to use rapid test strips regardless of having ever overdosed, suggesting that rapid fentanyl testing is an acceptable harm reduction intervention among young people who use drugs in Rhode Island. Study follow-up is ongoing to determine whether, how, and under what circumstances participants used the rapid test strips and if a positive result contributed to changes in overdose risk behavior.