Faculty Bibliography

Following federal regulatory changes during the COVID-19 pandemic, Rhode Island expanded methadone access for opioid treatment programs (OTPs) in March 2020. The policy, which permitted take-home dosing for patients, contrasted with longstanding restrictions on methadone. This study used patient-level OTP admission and discharge records to compare six-month retention before and after the policy change. We conducted a retrospective cohort study of 1,248 patients newly admitted to OTPs between March 18 and June 30 of 2019 (pre-policy) and 2020 (post-policy). We used logistic regression to estimate associations with retention before and after the policy and used a machine learning approach, the Heterogeneous Treatment Effect (HTE)-Scan, to explore heterogeneity in retention across subgroups. Overall, we found no change in retention following the policy, with an adjusted OR of 1.08 (95% CI: 0.80-1.45) and adjusted RR of 1.03 (0.90-1.18). Using HTE-Scan, we identified two subgroups with significantly increased retention above the overall cohort: (1) patients with below high school education and past-month arrest and (2) male, non-Hispanic white or Hispanic/Latino patients reporting heroin or fentanyl use with past-month arrest. We identified no subgroups with significantly decreased retention. Collectively, findings suggest that expanded methadone access may benefit vulnerable populations without harming overall retention.

INTRODUCTION/BACKGROUND:Specialty substance use treatment programs may adopt harm reduction practices to protect the health of their patients with opioid use disorder (OUD). Two such harm reduction strategies are distributing naloxone to clients and refraining from discharging clients if they have positive urine drug screens for drugs. The purpose of this study was to understand the prevalence of programs that adopt each of these harm reduction practices and the characteristics of clients attending programs that adopt both practices in a sample of state-licensed substance use treatment programs in New Jersey. METHODS:We conducted a cross-sectional survey of specialty treatment programs in New Jersey about a) naloxone dispensing and b) use of urine toxicology screens in client discharge decisions. We linked this survey to the treatment programs' administrative records of client admissions for OUD treatment between July 2021 to June 2022 (n = 14,838). We estimated the proportion of programs that reported that they adopted each practice. We then examined program and client characteristics associated with applying these harm reduction practices using regression methods. RESULTS:Of 108 programs included in this analysis, 55.6 % dispensed naloxone and 50.9 % did not consider toxicology screens in discharge decisions. Opioid treatment programs (OTP) were significantly more likely to adopt both harm reduction practices than non-OTPs. Clients referred by correctional programs, as opposed to self-referred to treatment, were significantly less likely to attend a program that used either harm reduction practice. CONCLUSIONS:Our findings suggest efforts are needed to increase adoption of harm reduction practices in SUD treatment settings, especially that are not OTPs, and programs serving clients referred by the criminal justice system.

IMPORTANCE/UNASSIGNED:Treatment retention for pregnant individuals with opioid use disorder (OUD) is critical, especially during the high-potency synthetic opioid (HPSO) era. Current data on the relationship between medication for opioid use disorder (MOUD) receipt in specialty substance use treatment facilities and retention are needed for this population. OBJECTIVE/UNASSIGNED:To examine the association between MOUD inclusion in treatment and 6-month treatment retention among pregnant individuals with OUD in publicly funded specialty treatment facilities during the HPSO era. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cross-sectional study pooled data from January 1, 2015, to December 31, 2021, from the Treatment Episode Data Set-Discharges, a national dataset managed by the Substance Abuse and Mental Health Services Administration that tracks annual discharges from state-licensed, publicly funded substance use treatment facilities. Individuals who were pregnant at the time of admission, reported an opioid (heroin, nonprescription methadone, or other opiates and synthetics) as their primary substance, and were discharged from ambulatory, nonintensive outpatient facilities were included. Data were analyzed November 2023 to April 2024. EXPOSURE/UNASSIGNED:MOUD inclusion in a treatment episode. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The main outcome was treatment retention (length of stay >6 months vs ≤6 months). To account for the nonrandom assignment to MOUD, inverse probability of treatment-weighted logistic regression models were estimated adjusting for sociodemographics; substance use, mental health, and treatment history; treatment admission-related variables; census division; state policy characteristics; and year fixed effects. RESULTS/UNASSIGNED:Of 29 981 treatment episodes, most involved individuals aged 25 to 34 years (19 106 [63.7%]). Approximately two-thirds of 29 071 episodes in the final analysis (19 884 [68.4%]) included MOUD across all study years. From 2015 to 2021, MOUD inclusion in treatment episodes increased by 9.1 percentage points, from 65.0% to 74.1%. Treatment episodes with MOUD were associated with greater odds of 6-month treatment retention compared with those without MOUD (adjusted odds ratio, 1.86 [95% CI, 1.72-2.01]). This finding translated to an estimated 14.2 percentage point greater adjusted probability of 6-month retention among treatment episodes with MOUD (43.1%) vs those without it (28.9%). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this cross-sectional study of treatment episodes from ambulatory, nonintensive facilities, MOUD inclusion among pregnant individuals was associated with significant improvements in treatment retention. However, retention remained low during the HPSO era. These findings underscore the importance of MOUD in improving OUD-related outcomes in this high-risk population.

OBJECTIVES/OBJECTIVE:To evaluate the predictive performance of different data sources to forecast fatal overdose in Rhode Island neighborhoods, with the goal of providing a template for other jurisdictions interested in predictive analytics to direct overdose prevention resources. METHODS:We evaluated seven combinations of data from six administrative data sources (American Community Survey (ACS) five-year estimates, built environment, emergency medical services non-fatal overdose response, prescription drug monitoring program, carceral release, and historical fatal overdose data). Fatal overdoses in Rhode Island census block groups (CBGs) were predicted using two machine learning approaches: linear regressions and random forests embedded in a nested cross-validation design. We evaluated performance using mean squared error and the percentage of statewide overdoses captured by CBGs forecast to be in top percentiles from 2019 to 2021. RESULTS:Linear models trained on ACS data combined with one other data source performed well, and comparably to models trained on all available data. Those including emergency medical service, prescription drug monitoring program, or carceral release data with ACS data achieved a priori goals for percentage of statewide overdoses captured by CBGs prioritized by models on average. CONCLUSIONS:Prioritizing neighborhoods for overdose prevention with forecasting is feasible using a simple-to-implement model trained on publicly available ACS data combined with only one other administrative data source in Rhode Island, offering a starting point for other jurisdictions.

OBJECTIVES/OBJECTIVE:The escalating overdose crisis in the United States points to the urgent need for new and novel data tools. Overdose data tools are growing in popularity but still face timely delays in surveillance data availability, lack of completeness, and wide variability in quality by region. As such, we need innovative tools to identify and prioritize emerging and high-need areas. Forecasting offers one such solution. Machine learning methods leverage numerous datasets that could be used to predict future vulnerability to overdose at the regional, town, and even neighborhood levels. This study aimed to understand the multi-level factors affecting the early stages of implementation for an overdose forecasting dashboard. This dashboard was developed with and for statewide harm reduction providers to increase data-driven response and resource distribution at the neighborhood level. METHODS:As part of PROVIDENT (Preventing OVerdose using Information and Data from the EnvironmeNT), a randomized, statewide community trial, we conducted an implementation study where we facilitated three focus groups with harm reduction organizations enrolled in the larger trial. Focus group participants held titles such as peer outreach workers, case managers, and program coordinators/managers. We employed the Exploration, Preparation, Implementation, Sustainment (EPIS) Framework to guide our analysis. This framework offers a multi-level, four-phase analysis unique to implementation within a human services environment to assess the exploration and preparation phases that influenced the early launch of the intervention. RESULTS:Multiple themes centering on organizational culture and resources emerged, including limited staff capacity for new interventions and repeated exposure to stress and trauma, which could limit intervention uptake. Community-level themes included the burden of data collection for program funding and statewide efforts to build stronger networks for data collection and dashboarding and data-driven resource allocation. DISCUSSION/CONCLUSIONS:Using an implementation framework within the larger study allowed us to identify multi-level and contextual factors affecting the early implementation of a forecasting dashboard within the PROVIDENT community trial. Additional investments to build organizational and community capacity may be required to create the optimal implementation setting and integration of forecasting tools.

BACKGROUND:Medicaid expansion via the Affordable Care Act, more recent legislation and Medicaid 1115 waivers offer opportunity to increase health care access among individuals involved in the carceral system. Effective enrollment of new beneficiaries and temporary suspension and reactivation of existing Medicaid benefits upon release is key to the success of these efforts. This study aims to characterize how jails, prisons and Medicaid agencies are implementing Medicaid suspension and enrollment programs and identifies barriers and facilitators to implementation. METHODS:We conducted 19 semi-structured interviews with 36 multi-state leaders in carceral facilities, Medicaid agencies, local health departments and national policy experts from 2020 to 2021. Interviews covered 4 domains: (1) the role of policy in influencing carceral and reentry Medicaid practices, (2) implementation strategies to suspend and enroll incarcerated individuals into Medicaid, (3) barriers and facilitators to successful implementation, and (4) variation in implementation between jails and prisons. RESULTS:Participants identified logistical challenges with suspension and enrollment, including limited infrastructure for data sharing between carceral facilities and Medicaid agencies, burdensome bureaucratic requirements, and challenges with Medicaid renewal, particularly in the jail environment. They offered opportunities to overcome barriers, such as the creation of specialized incarcerated Medicaid benefit categories and provision of in-reach services via managed care organizations. Participants also called for improvements to Medicaid reactivation processes, as even when facilities successfully suspended benefits, individuals faced significant challenges and delays reactivating benefits upon release. Participants also called for further loosening of the Medicaid Inmate Exclusion Policy. DISCUSSION/CONCLUSIONS:Findings highlight the need to update data sharing infrastructure, which will be critical to the implementation of the 1115 waivers, as carceral facilities will be subject to Medicaid billing and reporting requirements. In addition to investing in the ability to newly enroll and suspend Medicaid benefits, attention towards improving timely reactivation practices is needed, particularly given the highly elevated risk of mortality immediately after release. Participants calls for further reforms to the Medicaid Inmate Exclusion Policy are consistent with proposed legislation. CONCLUSIONS:Findings can critically inform the successful implementation of Medicaid-based reforms to improve the health of incarcerated and formerly incarcerated people.

OBJECTIVE:To evaluate the completeness and quality of Medicaid comprehensive managed care (CMC) data in national MAX/TAF research files. STUDY SETTING AND DESIGN/METHODS:This observational study compared CMC with fee-for-service (FFS) enrollee data in 2001-2019 Medicaid MAX/TAF inpatient, outpatient, and pharmacy files. Completeness was assessed as the proportion of enrollees with any claim and mean claims per enrollee with any claim. Quality was assessed as the proportion of inpatient and outpatient claims with primary diagnosis and procedure codes and the proportion of prescription drug claims with fill dates, National Drug Codes (NDC), days supplied, and quantity dispensed. Acceptable ranges for each study measure were defined as the national FFS mean ± 2 standard deviations. DATA SOURCES AND ANALYTIC SAMPLE/UNASSIGNED:We analyzed secondary data on 45 states from 2001 to 2013 (MAX) and 50 states and DC from 2014 to 2019 (TAF). The sample included adults aged 18-64 with continuous calendar-year enrollment who were eligible for full Medicaid benefits and ineligible for Medicare. We determined CMC enrollment rates and assessed data completeness and quality among state-years with ≥10% CMC penetration, comparing CMC with FFS enrollees. PRINCIPAL FINDINGS/RESULTS:Across 891 state-years, 194,364,647 enrollees met inclusion criteria. Of 540 state-years (60.6%) with ≥10% CMC enrollment, CMC data were largely comparable to national FFS distributions for all inpatient (n = 430; 79.6%), outpatient (n = 467, 86.5%), and prescription (n = 459, 85.0%) completeness criteria and for all inpatient (n = 449, 83.1%), outpatient (n = 511, 94.6%), and prescription (n = 528, 97.8%) quality criteria. Overall completeness (92.3%) and quality (84.6%) improved substantially by 2019. CONCLUSIONS:Completeness and quality of CMC data were largely comparable to FFS data, with increasing state-years meeting criteria over time. Further research on national Medicaid populations should assess and address differences in data completeness and quality by plan type across states, over time, and in relation to specific study samples and measures of interest.

BACKGROUND:Individuals with opioid use disorder have high rates of hospital admissions, which represent a critical opportunity to engage patients and initiate medications for opioid use disorder (MOUD). However, few patients receive MOUD and, even if MOUD is initiated in the hospital, patients may encounter barriers to continuing MOUD in the community. OBJECTIVE:Describe hospital providers' experiences and perspectives to inform initiatives and policies that support hospital-based MOUD initiation and continuation in community treatment programs. DESIGN/METHODS:As part of a broader implementation study focused on inpatient MOUD (NCT#04921787), we conducted semi-structured interviews with hospital providers. PARTICIPANTS/METHODS:Fifty-seven hospital providers from 12 community hospitals. APPROACH/METHODS:Thematic analysis examined an emergent topic on challenges transitioning patients to outpatient MOUD treatment and related impacts on MOUD initiation by inpatient providers. KEY RESULTS/RESULTS:Participants described structural barriers to transitioning hospitalized patients to continuing outpatient MOUD including (a) limited outpatient buprenorphine prescriber availability, (b) the siloed nature of addiction treatment, and (c) long wait times. As a result of observing these structural barriers, participants experienced a sense of futility that deterred them from initiating MOUD. Participants proposed strategies that could better support these patient transitions, including developing partnerships between hospitals and outpatient addiction treatment and supporting in-reach services from community providers. CONCLUSIONS:We identified concerns about inadequate and inaccessible community-based care and transition pathways that discouraged hospital providers from prescribing MOUD. As hospital-based opioid treatment models continue to expand, programmatic and policy strategies to support inpatient transitions to outpatient addiction treatment are needed. NCT TRIAL NUMBER/UNASSIGNED:04921787.

BACKGROUND AND AIMS/OBJECTIVE:Evidence from high-income countries has linked duration and compliance with treatment for substance use disorders (SUDs) with reductions in substance use and improvements in mental health. Generalizing these findings to other regions like South America, where opioid and injection drug use is uncommon, is not straightforward. We examined if length of time in treatment and compliance with treatment reduced subsequent substance use and presence of psychiatric comorbidities. DESIGN/METHODS:Prospective cohort analysis (3 assessments, 18 months) using inverse probability weighting to account for confounding and loss to follow-up. SETTINGS/METHODS:Outpatient/inpatient programs in Región Metropolitana, Chile. PARTICIPANTS/METHODS:Individuals initiating publicly funded treatment (n = 399). MEASUREMENTS/METHODS:Exposures included length of time in (0-3, 4-7, 8 + months, currently in) and compliance with treatment (not completed, completed, currently in) measured in the intermediate assessment (12 months). Primary outcomes were past-month use of primary substance (most problematic) and current psychiatric comorbidities (major depressive episode, panic, anxiety or post-traumatic stress disorders) measured 6 months later (18 months). Secondary outcomes included past month use of alcohol, cannabis, cocaine powder and cocaine paste. FINDINGS/RESULTS:18.3% [95% confidence interval (CI) = 14.7%-22.6%] of individuals participated for 3 or fewer months in treatment and 50.1% (95% CI = 45.2%-55.1%) did not complete their treatment plan at 12 months. Participating for 8 + months in treatment was associated with lower risk of past month use of primary substance at 18 months [vs. 0-3 months, risk ratio (RR) = 0.62, 95% CI = 0.38-1.00] and completion of treatment (vs. not completed, RR = 0.49, 95% CI = 0.30-0.80). Neither participating 8 + months (vs. 0-3 months, RR = 0.83, 95% CI = 0.57-1.22) nor treatment completion (vs. not completed, RR = 1.02, 95% CI = 0.72-1.46) were associated with lower risk of psychiatric comorbidity at 18 months. CONCLUSIONS:Longer time in treatment and compliance with treatment for substance use disorders in Chile appears to be associated with lower risk of substance use but not current comorbid psychiatric conditions 18 months after treatment initiation.