Faculty Bibliography

Policy implementation is a key component of scaling effective chronic disease prevention and management interventions. Policy can support scale-up by mandating or incentivizing intervention adoption, but enacting a policy is only the first step. Fully implementing a policy designed to facilitate implementation of health interventions often requires a range of accompanying implementation structures, like health IT systems, and implementation strategies, like training. Decision makers need to know what policies can support intervention adoption and how to implement those policies, but to date research on policy implementation is limited and innovative methodological approaches are needed. In December 2021, the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness and the Johns Hopkins Center for Mental Health and Addiction Policy convened a forum of research experts to discuss approaches for studying policy implementation. In this report, we summarize the ideas that came out of the forum. First, we describe a motivating example focused on an Affordable Care Act Medicaid health home waiver policy used by some US states to support scale-up of an evidence-based integrated care model shown in clinical trials to improve cardiovascular care for people with serious mental illness. Second, we define key policy implementation components including structures, strategies, and outcomes. Third, we provide an overview of descriptive, predictive and associational, and causal approaches that can be used to study policy implementation. We conclude with discussion of priorities for methodological innovations in policy implementation research, with three key areas identified by forum experts: effect modification methods for making causal inferences about how policies' effects on outcomes vary based on implementation structures/strategies; causal mediation approaches for studying policy implementation mechanisms; and characterizing uncertainty in systems science models. We conclude with discussion of overarching methods considerations for studying policy implementation, including measurement of policy implementation, strategies for studying the role of context in policy implementation, and the importance of considering when establishing causality is the goal of policy implementation research.

INTRODUCTION/BACKGROUND:Medications for opioid use disorder (MOUD), including buprenorphine, reduce overdose risk and improve outcomes for individuals with opioid use disorder (OUD). However, historically, most non-opioid treatment program (non-OTP) specialty substance use treatment programs have not offered buprenorphine. Understanding barriers to offering buprenorphine in specialty substance use treatment settings is critical for expanding access to buprenorphine. This study aims to examine program-level attitudinal, financial, and regulatory factors that influence clients' access to buprenorphine in state-licensed non-OTP specialty substance use treatment programs. METHODS:We surveyed leadership from state-licensed non-OTP specialty substance use treatment programs in New Jersey about organizational characteristics, including medications provided on- and off-site and percentage of OUD clients receiving any type of MOUD, and perceived attitudinal, financial, and regulatory barriers and facilitators to buprenorphine. The study estimated prevalence of barriers and compared high MOUD reach (n = 36, 35 %) and low MOUD reach (n = 66, 65 %) programs. RESULTS:Most responding organizations offered at least one type of MOUD either on- or off-site (n = 80, 78 %). However, 71 % of organizations stated that fewer than a quarter of their clients with OUD use any type of MOUD. Endorsement of attitudinal, financial, and institutional barriers to buprenorphine were similar among high and low MOUD reach programs. The most frequently endorsed government actions suggested to increase use of buprenorphine were facilitating access to long-acting buprenorphine (n = 95, 96 %), education and stigma reduction for clients and families (n = 95, 95 %), and financial assistance to clients to pay for medications (n = 90, 90 %). CONCLUSIONS:Although non-OTP specialty substance use programs often offer clients access to MOUD, including buprenorphine, most OUD clients do not actually receive MOUD. Buprenorphine uptake in these settings may require increased financial support for programs and clients, more robust education and training for providers, and efforts to reduce the stigma associated with medication among clients and their families.

BACKGROUND:Hospitals are a key touchpoint to reach patients with substance use disorders (SUDs) and link them with ongoing community-based services. Although there are many acute care interventions to initiate SUD treatment in hospital settings, less is known about what services are offered to transition patients to ongoing care after discharge. In this study, we explore what SUD care transition strategies are offered across nonprofit US hospitals. METHODS:We analyzed administrative documents from a national sample of US hospitals that indicated SUD as a top 5 significant community need in their Community Health Needs Assessment reports (2019-2021). Data were coded and categorized based on the nature of described services. We used data on hospitals and characteristics of surrounding counties to identify factors associated with hospitals' endorsement of transition interventions for SUD. RESULTS:Of 613 included hospitals, 313 prioritized SUD as a significant community need. Fifty-three of these hospitals (17%) offered acute care interventions to support patients' transition to community-based SUD services. Most (68%) of the 53 hospitals described transition strategies without further detail, 23% described scheduling appointments before discharge, and 11% described discussing treatment options before discharge. No hospital characteristics were associated with offering transition interventions, but such hospitals were more likely to be in the Northeast, in counties with higher median income, and states that expanded Medicaid. CONCLUSIONS:Despite high need, most US hospitals are not offering interventions to link patients with SUD from acute to community care. Efforts to increase acute care interventions for SUD should identify and implement best practices to support care continuity.

OBJECTIVE:Examine differences in neighborhood characteristics and services between overdose hotspot and non-hotspot neighborhoods and identify neighborhood-level population factors associated with increased overdose incidence. METHODS:We conducted a population-based retrospective analysis of Rhode Island, USA residents who had a fatal or non-fatal overdose from 2016 to 2020 using an environmental scan and data from Rhode Island emergency medical services, State Unintentional Drug Overdose Reporting System, and the American Community Survey. We conducted a spatial scan via SaTScan to identify non-fatal and fatal overdose hotspots and compared the characteristics of hotspot and non-hotspot neighborhoods. We identified associations between census block group-level characteristics using a Besag-York-Mollié model specification with a conditional autoregressive spatial random effect. RESULTS:We identified 7 non-fatal and 3 fatal overdose hotspots in Rhode Island during the study period. Hotspot neighborhoods had higher proportions of Black and Latino/a residents, renter-occupied housing, vacant housing, unemployment, and cost-burdened households. A higher proportion of hotspot neighborhoods had a religious organization, a health center, or a police station. Non-fatal overdose risk increased in a dose responsive manner with increasing proportions of residents living in poverty. There was increased relative risk of non-fatal and fatal overdoses in neighborhoods with crowded housing above the mean (RR 1.19 [95 % CI 1.05, 1.34]; RR 1.21 [95 % CI 1.18, 1.38], respectively). CONCLUSION/CONCLUSIONS:Neighborhoods with increased prevalence of housing instability and poverty are at highest risk of overdose. The high availability of social services in overdose hotspots presents an opportunity to work with established organizations to prevent overdose deaths.

The rise in drug overdoses and harms associated with the use of more than one substance has led to increased use of the term "polysubstance use" among researchers, clinicians, and public health officials. However, the term retains no consistent definition across contexts. The current authors convened from disciplines including sociology, epidemiology, neuroscience, and addiction psychiatry to propose a recommended definition of polysubstance use. An iterative process considered authors' formal and informal conversations, insights from relevant symposia, talks, and conferences, as well as their own research and clinical experiences to propose the current definition. Three key concepts were identified as necessary to define polysubstance use: (1) substances involved, (2) timing, and (3) intent. Substances involved include clarifying either (1) the number and type of substances used, (2) presence of more than one substance use disorder, or (3) primary and secondary substance use. The concept of timing is recommended to use clear terms such as simultaneous, sequential, and same-day polysubstance use to describe short-term behaviors (e.g., 30-day windows). Finally, the concept of intent refers to clarifying unintentional use or exposure when possible, and greater attention to motivations of polysubstance use. These three components should be clearly defined in research on polysubstance use to improve consistency across disciplines. Consistent definitions of polysubstance use can aid in the synthesis of evidence to better address an overdose crisis that increasingly involves multiple substances.

We sought to disentangle effects of the components of a peer-education intervention on self-reported injection risk behaviors among people who inject drugs (n = 560) in Philadelphia, US. We examined 226 egocentric groups/networks randomized to receive (or not) the intervention. Peer-education training consisted of two components delivered to the intervention network index individual only: (1) an initial training and (2) "booster" training sessions during 6- and 12-month follow up visits. In this secondary data analysis, using inverse-probability-weighted log-binomial mixed effects models, we estimated the effects of the components of the network-level peer-education intervention upon subsequent risk behaviors. This included contrasting outcome rates if a participant is a network member [non-index] under the network exposure versus under the network control condition (i.e., spillover effects). We found that compared to control networks, among intervention networks, the overall rates of injection risk behaviors were lower in both those recently exposed (i.e., at the prior visit) to a booster (rate ratio [95% confidence interval]: 0.61 [0.46-0.82]) and those not recently exposed to it (0.81 [0.67-0.98]). Only the boosters had statistically significant spillover effects (e.g., 0.59 [0.41-0.86] for recent exposure). Thus, both intervention components reduced injection risk behaviors with evidence of spillover effects for the boosters. Spillover should be assessed for an intervention that has an observable behavioral measure. Efforts to fully understand the impact of peer education should include routine evaluation of spillover effects. To maximize impact, boosters can be provided along with strategies to recruit especially committed peer educators and to increase attendance at trainings. Clinical Trials Registration Clinicaltrials.gov NCT00038688 June 5, 2002.

We examined a natural history of opioid overdose deaths from 1999-2021 in the United States to describe state-level spatio-temporal heterogeneity in the waves of the epidemic. We obtained overdose death counts by state from 1999-2021, categorized as involving prescription opioids, heroin, synthetic opioids, or unspecified drugs. We developed a Bayesian multivariate multiple change point model to flexibly estimate the timing and magnitude of state-specific changes in death rates involving each drug type. We found substantial variability around the timing and severity of each wave across states. The first wave of prescription-involved deaths started between 1999 and 2005, the second wave of heroin-involved deaths started between 2010 and 2014, and the third wave of synthetic opioid-involved deaths started between 2014 and 2021. The severity of the second and third waves was greater in states in the eastern half of the country. Our study highlights state-level variation in the timing and severity of the waves of the opioid epidemic by presenting a 23-year natural history of opioid overdose mortality in the United States. While reinforcing the general notion of three waves, we find that states did not uniformly experience the impacts of each wave.

Locating undiagnosed HIV infections is important for limiting transmission. However, there is limited evidence about how best to do so. In South Africa, men have been particularly challenging to reach for HIV testing due, in part, to stigma. We pilot-tested two versions of a network-based case-finding and care-linkage intervention. The first, TRIP, asked "seeds" (original participants) to recruit their sexual and/or injection partners. The second, TRIPLE, aimed to circumvent some stigma-related issues by asking seeds to recruit anyone they know who might be at risk of being HIV-positive-unaware. We recruited 11 (18% male) newly diagnosed HIV-positive (NDP) seeds from two clinics in KwaZulu-Natal, South Africa and randomly assigned them to either TRIP or TRIPLE. Network members were recruited two steps from each seed. The TRIP arm recruited 12 network members; the TRIPLE arm recruited 62. Both arms recruited NDPs at higher rates than local clinic testing, with TRIP (50.0%) outperforming (p = 0.012) TRIPLE (14.5%). However, TRIPLE (53.2%) was far superior to clinics (27.8%) and to TRIP (25.0%) at recruiting men. Given challenges around testing and treating men for HIV in this context, these findings suggest that the TRIPLE expanded network-tracing approach should be tested formally among larger samples in multiple settings.

INTRODUCTION/BACKGROUND:Hospitals are an ideal setting to stage opioid-related interventions with patients who are hospitalized due to overdose or other substance use-related complications. Transitional opioid programs-which initiate care and provide linkages upon discharge, such as screening, initiation of medications for opioid use disorder, and addiction consult services-have become the gold standard, but implementation has been uneven. The purpose of this study was to assess disparities in the availability of hospital-based transitional opioid programs, across rural and urban hospital settings in the United States. METHODS:Using hospital administrative data paired with county-level demographic data, we conducted bivariate and regression analyses to assess rural-urban differences in the availability of transitional opioid services including screening, addiction consult services, and MOUD in U.S general medical centers, controlling for hospital- and community-level factors. Our sample included 2846 general medical hospitals that completed the 2021 American Hospital Association (AHA) Annual Survey of Hospitals. Our primary outcomes were five self-reported measures: whether the hospital provided screening in the ED; provided screening in the inpatient setting; whether the hospital provided addiction consult services in the ED; provided addiction consult services in the inpatient setting; and whether the hospital provided medications for opioid use disorder. RESULTS:Rural hospitals did not have lower odds of screening for OUD or other SUDs than urban hospitals, but both micropolitan rural counties and noncore rural counties had significantly lower odds of having addiction consult services in either the ED (OR: 0.74, 95 % CI: 0.58, 0.95; OR: 0.68, 95 % CI: 0.50, 0.91) or inpatient setting (OR: 0.76, 95 % CI: 0.59, 0.97; OR: 0.68, 95 % CI: 0.50, 0.93), respectively, or of offering MOUD (OR: 0.69, 95 % CI: 0.52, 0.90; OR: 0.52, 95 % CI: 0.37, 0.74). CONCLUSIONS:Our study suggests that evidence-based interventions, such as medications for opioid use disorder and addiction consult services, are less often available in rural hospitals, which may contribute to rural-urban disparities in health outcomes secondary to OUD. A priority for population health improvement should be developing implementation strategies to support rural hospital adoption of transitional opioid programs.