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.).

Reducing perceived barriers to scaling up overdose education and naloxone distribution and medications for opioid use disorder in the United States in the HEALing (helping end addiction long-term®) communities study.

BACKGROUND: Scaling up overdose education and naloxone distribution (OEND) and medications for opioid use disorder (MOUD) is needed to reduce opioid overdose deaths, but barriers are pervasive. This study examines whether the Communities That HEAL (CTH) intervention reduced perceived barriers to expanding OEND and MOUD in healthcare/behavioral health, criminal-legal, and other/non-traditional venues. METHODS: The HEALing (Helping End Addiction Long-Term®) Communities Study is a parallel, wait-list, cluster randomized trial testing the CTH intervention in 67 communities in the United States. Surveys administered to coalition members and key stakeholders measured the magnitude of perceived barriers to scaling up OEND and MOUD in November 2019-January 2020, May-June 2021, and May-June 2022. Multilevel linear mixed models compared Wave 1 (intervention) and Wave 2 (wait-list control) respondents. Interactions by rural/urban status and research site were tested. RESULTS: Wave 1 respondents reported significantly greater reductions in mean scores for three outcomes: perceived barriers to scaling up OEND in Healthcare/Behavioral Health Venues (-0.26, 95% confidence interval, CI: -0.48, -0.05, p = 0.015), OEND in Other/Non-traditional Venues (-0.53, 95% CI: - 0.84, -0.22, p = 0.001) and MOUD in Other/Non-traditional Venues (-0.34, 95% CI: -0.62, -0.05, p = 0.020). There were significant interactions by research site for perceived barriers to scaling up OEND and MOUD in Criminal-Legal Venues. There were no significant interactions by rural/urban status. DISCUSSION: The CTH Intervention reduced perceived barriers to scaling up OEND and MOUD in certain venues, with no difference in effectiveness between rural and urban communities. More research is needed to understand facilitators and barriers in different venues.

Massachusetts Prevalence of Opioid Use Disorder Estimation Revisited: Comparing a Bayesian Approach to Standard Capture-Recapture Methods.

BACKGROUND: The National Survey on Drug Use and Health (NSDUH) estimated the prevalence of opioid use disorder (OUD) among the civilian, noninstitutionalized people aged 12 years or older in Massachusetts as 1.2% between 2015 and 2017. Accurate estimation of the prevalence of OUD is critical to the success of treatment and resource planning. Various indirect estimation approaches have been used but are subject to data availability and infrastructure-related issues. METHODS: We used 2015 data from the Massachusetts Public Health Data Warehouse (PHD) to compare the results of two approaches to estimating OUD prevalence in the Massachusetts population. First, we used a seven-dataset capture-recapture analysis under log-linear model parameterization, controlling for the source dependence and effects of age, sex, and county through stratification. Second, we applied a benchmark-multiplier method in a Bayesian framework by linking health care claims data to death certificate data assuming an extrapolation of death rates from observed untreated OUD to unobserved OUD. RESULTS: Our estimates for OUD prevalence among Massachusetts residents (aged 18-64 years) were 4.62% (95% CI = 4.59%, 4.64%) in the capture-recapture approach and 4.29% (95% CrI = 3.49%, 5.32%) in the Bayesian model. Both estimates were approximately four times higher than NSDUH estimates. CONCLUSION: The synthesis of our findings suggests that the disease surveillance system misses a large portion of the population with OUD. Our study also suggests that concurrent use of multiple methods improves the justification and facilitates the triangulation and interpretation of the resulting estimates. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04111939.

Opioid Use Disorder Among Ohio's Medicaid Population: Prevalence Estimates From 19 Counties Using a Multiplier Method.

The decades-long overdose epidemic in the United States is driven by opioid misuse. Overdoses commonly, although not exclusively, occur in individuals with opioid use disorder (OUD). To allocate adequate resources and develop appropriately scaled public health responses, accurate estimation of the prevalence of OUD is needed. Indirect methods (e.g., a multiplier method) of estimating prevalence of problematic substance-use behavior circumvent some limitations of household surveys and use of administrative data. We used a multiplier method to estimate OUD prevalence among the adult Medicaid population (ages 18-64 years) in 19 Ohio counties that are highly affected by overdose. We used Medicaid claims data and the US National Vital Statistics System overdose death data, which were linked at the person level. A statistical model leveraged opioid-related death rate information from a group with known OUD to estimate prevalence among a group with unknown OUD status given recorded opioid-related deaths in that group. We estimated that 13.6% of the total study population had OUD in 2019. Men (16.7%) had a higher prevalence of OUD than women (11.4%), and persons aged 35-54 had the highest prevalence (16.7%). Our approach to prevalence estimation has important implications for OUD surveillance and treatment in the United States.

Impact of Abstinence and of Reducing Illicit Drug Use Without Abstinence on Human Immunodeficiency Virus Viral Load.

BACKGROUND: Substance use is common among people living with human immunodeficiency virus (PLWH) and a barrier to achieving viral suppression. Among PLWH who report illicit drug use, we evaluated associations between HIV viral load (VL) and reduced use of illicit opioids, methamphetamine/crystal, cocaine/crack, and marijuana, regardless of whether or not abstinence was achieved. METHODS: This was a longitudinal cohort study of PLWH from 7 HIV clinics or 4 clinical studies. We used joint longitudinal and survival models to examine the impact of decreasing drug use and of abstinence for each drug on viral suppression. We repeated analyses using linear mixed models to examine associations between change in frequency of drug use and VL. RESULTS: The number of PLWH who were using each drug at baseline ranged from n = 568 (illicit opioids) to n = 4272 (marijuana). Abstinence was associated with higher odds of viral suppression (odds ratio [OR], 1.4-2.2) and lower relative VL (ranging from 21% to 42% by drug) for all 4 drug categories. Reducing frequency of illicit opioid or methamphetamine/crystal use without abstinence was associated with VL suppression (OR, 2.2, 1.6, respectively). Reducing frequency of illicit opioid or methamphetamine/crystal use without abstinence was associated with lower relative VL (47%, 38%, respectively). CONCLUSIONS: Abstinence was associated with viral suppression. In addition, reducing use of illicit opioids or methamphetamine/crystal, even without abstinence, was also associated with viral suppression. Our findings highlight the impact of reducing substance use, even when abstinence is not achieved, and the potential benefits of medications, behavioral interventions, and harm-reduction interventions.

Data Collection and Harmonization in HIV Research: The Seek, Test, Treat, and Retain Initiative at the National Institute on Drug Abuse.

Large-scale, multisite data sets offer the potential for exploring the public health benefits of biomedical interventions. Data harmonization is an emerging strategy to increase the comparability of research data collected across independent studies, enabling research questions to be addressed beyond the capacity of any individual study. The National Institute on Drug Abuse recently implemented this novel strategy to prospectively collect and harmonize data across 22 independent research studies developing and empirically testing interventions to effectively deliver an HIV continuum of care to diverse drug-abusing populations. We describe this data collection and harmonization effort, collectively known as the Seek, Test, Treat, and Retain Data Collection and Harmonization Initiative, which can serve as a model applicable to other research endeavors.

Intersectional inequities and longitudinal prevalence estimates of opioid use disorder in Massachusetts 2014-2020: a multi-sample capture-recapture analysis.

Background: As overdoses continue to increase worldwide, accurate estimates are needed to understand the size of the population at risk and address health disparities. Capture-recapture methods may be used in place of direct estimation at nearly any geographic level (e.g., city, state, country) to estimate the size of the population with opioid use disorder (OUD). We performed a multi-sample capture-recapture analysis with persons aged 18-64 years to estimate the prevalence of OUD in Massachusetts from 2014 to 2020, stratified by sex and race/ethnicity. Methods: We used seven statewide administrative data sources linked at the individual level. We developed log-linear models to estimate the unknown OUD-affected population. Uncertainty was characterized using 95% confidence intervals (95% CI) on the total counts and prevalence estimates. Findings: The estimated OUD prevalence increased from 5.47% (95% CI = 4.89%, 5.98%) in 2014 to 5.79% (95% CI = 5.34%, 6.19%) in 2020. Prevalence among Hispanic females doubled (2.46% in 2014 to 4.23% in 2020) and prevalence rose to nearly 10% among Black non-Hispanic males and Hispanic males from 2014 through 2019. Estimates for Black non-Hispanic females more than doubled from 2014 through 2019 (3.39% to 7.09%), and then decreased to 5.69% in 2020. Interpretation: This study is the first to provide OUD prevalence trend estimates by binary sex and race/ethnicity at a state level using capture-recapture methods. Using these methods as the international overdose crisis worsens can allow jurisdictions to appropriately allocate resources and targeted interventions to marginalised populations. Funding: NIDA.

Development and validation of a community-level social determinants of health index for drug overdose deaths in the HEALing Communities Study.

INTRODUCTION: Social determinants of health (SDoH), such as socioeconomic status, education level, and food insecurity, are believed to influence the opioid crisis. While global SDoH indices such as the CDC's Social Vulnerability Index (SVI) and Area Deprivation Index (ADI) combine the explanatory power of multiple social factors for understanding health outcomes, they may be less applicable to the specific challenges of opioid misuse and associated outcomes. This study develops a novel index tailored to opioid misuse outcomes, tests the efficacy of this index in predicting drug overdose deaths across contexts, and compares the explanatory power of this index to other SDoH indices. METHODS: Focusing on four HEALing Communities Study (HCS) states (Kentucky, Massachusetts, New York and Ohio; encompassing 4269 ZIP codes), we identified multilevel SDoH potentially associated with opioid misuse and aggregated publicly available data for each measure. We then leveraged a random forest model to develop a composite measure that predicts age-adjusted drug overdose mortality rates based on SDoH. We used this composite measure to understand HCS and non-HCS communities in terms of overdose risk across areas of varying racial composition. Finally, we compared variance in drug overdose deaths explained by this index to variance explained by the SVI and ADI. RESULTS: Our composite measure included 28 SDoH measures and explained approximately 89 % percent of variance in age-adjusted drug overdose mortality across HCS states. Health care measures, including emergency department visits and primary care provider availability, were top predictors within the index. Index accuracy was robust within and outside of HCS communities and states. This measure identified high levels of overdose mortality risk in segregated communities. CONCLUSIONS: Existing SDoH indices fail to explain much variation in area-level overdose mortality rates. Having tailored composite indices can help us to identify places in which residents are at highest risk based on their composite contexts. A comprehensive index can also help to develop effective community interventions for programs such as HCS by considering the context in which people live.

Assessing the impact of jail-initiated medication for opioid use disorder: A multisite analysis of the SOMATICS collaborative.

The objective of this study was to estimate the associations of jail-initiated medication for opioid use disorder (MOUD) and patient navigation (PN) with opioid use disorder (OUD) at 6 months post-release. Three randomized trials (combined N = 330) were combined to assess whether MOUD (extended-release naltrexone or interim methadone) initiated prior to release from jail with or without PN would reduce the likelihood of a DSM-5 diagnosis of OUD 6 months post-release relative to enhanced treatment-as-usual (ETAU). Across the three studies, assignment to MOUD compared to ETAU was not associated with an OUD diagnosis at 6 months post-release (69% vs. 75%, respectively, OR = 0.67, 95% CI: 0.42 to 1.20). Similarly, PN compared to MOUD without PN was not associated with an OUD diagnosis (63% vs 77%, respectively, OR = 0.61, 95% CI: 0.27 to 1.53). Results underscore the need to further optimize the effectiveness of MOUD for patients initiating treatment in jail, beginning with an emphasis on post-release treatment adherence.

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.

The prevalence of opioid use disorder in Kentucky's counties: A two-year multi-sample capture-recapture analysis.

BACKGROUND: Kentucky has one of the highest opioid overdose mortality rates in the United States. Accurate estimates of people with opioid use disorder (OUD) are critical to plan for the scope of interventions required to reduce overdose and opioid misuse. Commonly used household surveys are known to underestimate OUD at the state-level and do not provide county-level estimates. METHODS: We performed a multi-sample capture-recapture analysis to estimate OUD prevalence in Kentucky in 2018 and 2019. We utilized four statewide datasets that were linked at the individual level: 1) Registry of Vital Statistics, 2) Emergency Medical Services (EMS), 3) Kentucky's Prescription Drug Monitoring Program (PDMP), and 4) Kentucky Medicaid. We included persons aged 18-64 years who resided in Kentucky between 2018 and 2019. We identified individuals with administrative data consistent with OUD in each of the datasets, including a fatal opioid-involved overdose (Vital Statistics), EMS runs for suspected opioid overdose, receipt of buprenorphine for OUD treatment (PDMP), or Medicaid claims for OUD. Observed and estimated counts of OUD cases and prevalence of OUD among the adult population in Kentucky. RESULTS: The estimated statewide OUD prevalence was 5.5 % and 5.9 % for 2018 and 2019, respectively, ranging from 1.3 % to 17.7 % across Kentucky counties. As expected, counties with the highest OUD rates were Appalachian counties (eastern area) of the state. CONCLUSIONS: Our analysis reveals a substantially larger proportion of KY residents have OUD than previously estimated. Our approach offers a model for states needing county-level estimates of OUD.

The policy landscape for naloxone distribution in four states highly impacted by fatal opioid overdoses.

Background: Expanding access to naloxone is one of the most impactful interventions in decreasing opioid-related mortality. However, state distribution rates of naloxone are insufficient to meet community need. The current study sought to better understand this gap by focusing on state policies that may facilitate or impede naloxone distribution in four states highly impacted by fatal opioid overdoses - Kentucky, Massachusetts, New York, and Ohio. Methods: We provide a descriptive analysis of the policy landscape impacting naloxone distribution through pharmacy and community channels in the four states participating in the HEALing Communities Study (HCS). Publicly available data and the expertise of the research team were used to describe each state's naloxone access laws (NALs), Medicaid coverage of naloxone, and community overdose education and naloxone distribution infrastructure. Data presented in this study represent the most current policy landscape through September 2022. Results: Variation exists between specific components of the NALs of each state, the structure of Medicaid coverage of naloxone, and the community distribution infrastructure networks. Massachusetts and New York have a statewide standing order, but other states use different strategies short of a statewide standing order to expand access to naloxone. Quantity limits specific to naloxone may limit access to Medicaid beneficiaries in some states. Conclusion: States participating in the HCS have developed innovative but different mechanisms to ensure naloxone access. Policies were dynamic and moved towards greater access. Research should consider the policy landscape in the implementation and sustainability of interventions as well as the analysis of outcomes.

Telemedicine Buprenorphine Initiation and Retention in Opioid Use Disorder Treatment for Medicaid Enrollees.

Importance: Early COVID-19 mitigation strategies placed an additional burden on individuals seeking care for opioid use disorder (OUD). Telemedicine provided a way to initiate and maintain transmucosal buprenorphine treatment of OUD. Objective: To examine associations between transmucosal buprenorphine OUD treatment modality (telemedicine vs traditional) during the COVID-19 public health emergency and the health outcomes of treatment retention and opioid-related nonfatal overdose. Design, Setting, and Participants: This retrospective cohort study was conducted using Medicaid claims and enrollment data from November 1, 2019, to December 31, 2020, for individuals aged 18 to 64 years from Kentucky and Ohio. Data were collected and analyzed in June 2022, with data updated during revision in August 2023. Exposures: The primary exposure of interest was the modality of the transmucosal buprenorphine OUD treatment initiation. Relevant patient demographic and comorbidity characteristics were included in regression models. Main Outcomes and Measures: There were 2 main outcomes of interest: retention in treatment after initiation and opioid-related nonfatal overdose after initiation. For outcomes measured after initiation, a 90-day follow-up period was used. The main analysis used a new-user study design; transmucosal buprenorphine OUD treatment initiation was defined as initiation after more than a 60-day gap in buprenorphine treatment. In addition, uptake of telemedicine for buprenorphine was examined, overall and within patients initiating treatment, across quarters in 2020. Results: This study included 41 266 individuals in Kentucky (21 269 women [51.5%]; mean [SD] age, 37.9 [9.0] years) and 50 648 individuals in Ohio (26 425 women [52.2%]; mean [SD] age, 37.1 [9.3] years) who received buprenorphine in 2020, with 18 250 and 24 741 people initiating buprenorphine in Kentucky and Ohio, respectively. Telemedicine buprenorphine initiations increased sharply at the beginning of 2020. Compared with nontelemedicine initiation, telemedicine initiation was associated with better odds of 90-day retention with buprenorphine in both states (Kentucky: adjusted odds ratio, 1.13 [95% CI, 1.01-1.27]; Ohio: adjusted odds ratio, 1.19 [95% CI, 1.06-1.32]) in a regression analysis adjusting for patient demographic and comorbidity characteristics. Telemedicine initiation was not associated with opioid-related nonfatal overdose (Kentucky: adjusted odds ratio, 0.89 [95% CI, 0.56-1.40]; Ohio: adjusted odds ratio, 1.08 [95% CI, 0.83-1.41]). Conclusions and Relevance: In this cohort study of Medicaid enrollees receiving buprenorphine for OUD, telemedicine buprenorphine initiation was associated with retention in treatment early during the COVID-19 pandemic. These findings add to the literature demonstrating positive outcomes associated with the use of telemedicine for treatment of OUD.

Community selected strategies to reduce opioid-related overdose deaths in the HEALing (Helping to End Addiction Long-term SM) communities study.

The Helping End Addictions Long Term (HEALing) Communities Study (HCS) seeks to significantly reduce overdose deaths in 67 highly impacted communities in Kentucky (KY), Massachusetts (MA), New York (NY), and Ohio (OH) by implementing evidence-based practices (EBPs) to reduce overdose deaths. The Opioid-overdose Reduction Continuum of Care Approach (ORCCA) organizes EBP strategies under three menus: Overdose Education and Naloxone Distribution (OEND), Medication Treatment for Opioid Use Disorder (MOUD), and Safer Prescribing and Dispensing Practices (SPDP). The ORCCA sets requirements for strategy selection but allows flexibility to address community needs. This paper describes and compiles strategy selection and examines two hypotheses: 1) OEND selections will differ significantly between communities with higher versus lower opioid-involved overdose deaths; 2) MOUD selections will differ significantly between urban versus rural settings. METHODS: Wave 1 communities (n = 33) provided data on EBP strategy selections. Selections were recorded as a combination of EBP menu, sector (behavioral health, criminal justice, and healthcare), and venue (e.g., jail, drug court, etc.); target medication(s) were recorded for MOUD strategies. Strategy counts and proportions were calculated overall and by site (KY, MA, NY, OH), setting (rural/urban), and opioid-involved overdose deaths (high/low). RESULTS: Strategy selection exceeded ORCCA requirements across all 33 communities, with OEND strategies accounting for more (40.8%) than MOUD (35.1%), or SPDP (24.1%) strategies. Site-adjusted differences were not significant for either hypothesis related to OEND or MOUD strategy selection. CONCLUSIONS: HCS communities selected strategies from the ORCCA menu well beyond minimum requirements using a flexible approach to address unique needs.

Protocol for community-driven selection of strategies to implement evidence-based practices to reduce opioid overdoses in the HEALing Communities Study: a trial to evaluate a community-engaged intervention in Kentucky, Massachusetts, New York and Ohio.

INTRODUCTION: Opioid-involved overdose deaths continue to surge in many communities, despite numerous evidence-based practices (EBPs) that exist to prevent them. The HEALing Communities Study (HCS) was launched to develop and test an intervention (ie, Communities That HEAL (CTH)) that supports communities in expanding uptake of EBPs to reduce opioid-involved overdose deaths. This paper describes a protocol for a process foundational to the CTH intervention through which community coalitions select strategies to implement EBPs locally. METHODS AND ANALYSIS: The CTH is being implemented in 67 communities (randomised to receive the intervention) in four states in partnership with coalitions (one per community). Coalitions must select at least five strategies, including one to implement each of the following EBPs: (a) overdose education and naloxone distribution; expanded (b) access to medications for opioid use disorder (MOUD), (c) linkage to MOUD, (d) retention in MOUD and (e) safer opioid prescribing/dispensing. Facilitated by decision aid tools, the community action planning process includes (1) data-driven goal setting, (2) discussion and prioritisation of EBP strategies, (3) selection of EBP strategies and (4) identification of next steps. Following review of epidemiologic data and information on existing local services, coalitions set goals and discuss, score and/or rank EBP strategies based on feasibility, appropriateness within the community context and potential impact on reducing opioid-involved overdose deaths with a focus on three key sectors (healthcare, behavioural health and criminal justice) and high-risk/vulnerable populations. Coalitions then select EBP strategies through consensus or majority vote and, subsequently, suggest or choose agencies with which to partner for implementation. ETHICS AND DISSEMINATION: The HCS protocol was approved by a central Institutional Review Board (Advarra). Results of the action planning process will be disseminated in academic conferences and peer-reviewed journals, online and print media, and in meetings with community stakeholders. TRIAL REGISTRATION NUMBER: NCT04111939.

Addressing opioid overdose deaths: The vision for the HEALing communities study.

The United States is facing two devastating public health crises- the opioid epidemic and the COVID-19 pandemic. Within this context, one of the most ambitious implementation studies in addiction research is moving forward. Launched in May 2019, the HEALing Communities Study (HCS) was developed by the National Institutes of Health (NIH) and the Substance Abuse and Mental Health Services Administration (SAMHSA) as part of the Helping to End Addiction Long-termSM Initiative (National Institutes of Health, 2020). The goal for this research was to reduce opioid overdose deaths by 40 % in three years by enhancing and integrating the delivery of multiple evidence-based practices (EBPs) with proven effectiveness in reducing opioid overdose deaths across health care, justice, and community settings. This paper describes the initial vision, goals, and objectives of this initiative; the impact of COVID-19; and the potential for knowledge to be generated from HCS at the intersection of an unrelenting epidemic of opioid misuse and overdoses and the ravishing COVID-19 pandemic.

Implementing Common Metrics across the NIH Clinical and Translational Science Awards (CTSA) consortium.

The Clinical and Translational Science Award (CTSA) Consortium and the National Center for Advancing Translational Science (NCATS) undertook a Common Metrics Initiative to improve research processes across the national CTSA Consortium. This was implemented by Tufts Clinical and Translational Science Institute at the 64 CTSA academic medical centers. Three metrics were collaboratively developed by NCATS staff, CTSA Consortium teams, and outside consultants for Institutional Review Board Review Duration, Careers in Clinical and Translational Research, and Pilot Award Publications and Subsequent Funding. The implementation program included training on the metric operational guidelines, data collection, data reporting system, and performance improvement framework. The implementation team provided small-group coaching and technical assistance. Collaborative learning sessions, driver diagrams, and change packages were used to disseminate best and promising practices. After 14 weeks, 84% of hubs had produced a value for one metric and about half had produced an initial improvement plan. Overall, hubs reported that the implementation activities facilitated their Common Metrics performance improvement process. Experiences implementing the first three metrics can inform future directions of the Common Metrics Initiative and other research groups implementing standardized metrics and performance improvement processes, potentially including other National Institutes of Health institutes and centers.

Evaluation of initial progress to implement Common Metrics across the NIH Clinical and Translational Science Awards (CTSA) Consortium.

INTRODUCTION: The Clinical and Translational Science Awards (CTSA) Consortium, about 60 National Institutes of Health (NIH)-supported CTSA hubs at academic health care institutions nationwide, is charged with improving the clinical and translational research enterprise. Together with the NIH National Center for Advancing Translational Sciences (NCATS), the Consortium implemented Common Metrics and a shared performance improvement framework. METHODS: Initial implementation across hubs was assessed using quantitative and qualitative methods over a 19-month period. The primary outcome was implementation of three Common Metrics and the performance improvement framework. Challenges and facilitators were elicited. RESULTS: Among 59 hubs with data, all began implementing Common Metrics, but about one-third had completed all activities for three metrics within the study period. The vast majority of hubs computed metric results and undertook activities to understand performance. Differences in completion appeared in developing and carrying out performance improvement plans. Seven key factors affected progress: hub size and resources, hub prior experience with performance management, alignment of local context with needs of the Common Metrics implementation, hub authority in the local institutional structure, hub engagement (including CTSA Principal Investigator involvement), stakeholder engagement, and attending training and coaching. CONCLUSIONS: Implementing Common Metrics and performance improvement in a large network of research-focused organizations proved feasible but required substantial time and resources. Considerable heterogeneity across hubs in data systems, existing processes and personnel, organizational structures, and local priorities of home institutions created disparate experiences across hubs. Future metric-based performance management initiatives across heterogeneous local contexts should anticipate and account for these types of differences.