Faculty Bibliography

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.

BACKGROUND:Treatment with methadone and buprenorphine medications for opioid use disorder (MOUD) during incarceration may lead to better community re-entry, but evidence on these relationships have been mixed. We aimed to identify community re-entry patterns and examine the association between in-jail MOUD and a pattern of successful reentry defined by rare occurrence of reincarceration and preventable healthcare utilization. METHODS:Data came from a retrospective, observational cohort study of 6066 adults with opioid use disorder who were incarcerated in New York City jails and released to the community during 2011-14. An outcome was community re-entry patterns identified by sequence analysis of 3-year post-release reincarceration, emergency department visits, and hospitalizations. An exposure was receipt of in-jail MOUD versus out-of-treatment (42 % vs. 58 %) for the last 3 days before discharge. The study accounted for differences in baseline demographic, clinical, behavioral, housing, and criminal legal characteristics between in-jail MOUD and out-of-treatment groups via propensity score matching. RESULTS:This study identified five re-entry patterns: stability (64 %), hospitalization (23 %), delayed reincarceration (7 %), immediate reincarceration (4 %), and continuous incarceration (2 %). After addressing confounding, 64 % and 57 % followed the stability pattern among MOUD and out-of-treatment groups who were released from jail in 2011, respectively. In 2012-14, the prevalence of following the stability pattern increased year-by-year while a consistently higher prevalence was observed among those with in-jail MOUD. CONCLUSIONS:Sequence analysis helped define post-release stability based on health and criminal legal system involvement. Receipt of in-jail MOUD was associated with a marker of successful community re-entry.

OBJECTIVE:To assess whether chronic pain increases the risk of COVID-19 complications and whether opioid use disorder (OUD) differentiates this risk among New York State Medicaid beneficiaries. DESIGN, SETTING, AND SUBJECTS/METHODS:This was a retrospective cohort study of New York State Medicaid claims data. We evaluated Medicaid claims from March 2019 through December 2020 to determine whether chronic pain increased the risk of COVID-19 emergency department (ED) visits, hospitalizations, and complications and whether this relationship differed by OUD status. We included beneficiaries 18-64 years of age with 10 months of prior enrollment. Patients with chronic pain were propensity score-matched to those without chronic pain on demographics, utilization, and comorbidities to control for confounders and were stratified by OUD. Complementary log-log regressions estimated hazard ratios (HRs) of COVID-19 ED visits and hospitalizations; logistic regressions estimated odds ratios (ORs) of hospital complications and readmissions within 0-30, 31-60, and 61-90 days. RESULTS:Among 773 880 adults, chronic pain was associated with greater hazards of COVID-related ED visits (HR = 1.22 [95% CI: 1.16-1.29]) and hospitalizations (HR = 1.19 [95% CI: 1.12-1.27]). Patients with chronic pain and OUD had even greater hazards of hospitalization (HR = 1.25 [95% CI: 1.07-1.47]) and increased odds of hepatic- and cardiac-related events (OR = 1.74 [95% CI: 1.10-2.74]). CONCLUSIONS:Chronic pain increased the risk of COVID-19 ED visits and hospitalizations. Presence of OUD further increased the risk of COVID-19 hospitalizations and the odds of hepatic- and cardiac-related events. Results highlight intersecting risks among a vulnerable population and can inform tailored COVID-19 management.

BACKGROUND:The COVID-19 pandemic's impact on utilization of medications for opioid use disorder (MOUD) among patients with opioid use disorder (OUD) and chronic pain is unclear. METHODS:We analyzed New York State (NYS) Medicaid claims from pre-pandemic (August 2019-February 2020) and pandemic (March 2020-December 2020) periods for beneficiaries with and without chronic pain. We calculated monthly proportions of patients with OUD diagnoses in 6-month-lookback windows utilizing MOUD and proportions of treatment-naïve patients initiating MOUD. We used interrupted time series to assess changes in MOUD utilization and initiation rates by medication type and by race/ethnicity. RESULTS:Among 20,785 patients with OUD and chronic pain, 49.3% utilized MOUD (versus 60.3% without chronic pain). The pandemic did not affect utilization in either group but briefly disrupted initiation among patients with chronic pain (β=-0.009; 95% CI [-0.015, -0.002]). Overall MOUD utilization was not affected by the pandemic for any race/ethnicity but opioid treatment program (OTP) utilization was briefly disrupted for non-Hispanic Black individuals (β=-0.007 [-0.013, -0.001]). The pandemic disrupted overall MOUD initiation in non-Hispanic Black (β=-0.007 [-0.012, -0.002]) and Hispanic individuals (β=-0.010 [-0.019, -0.001]). CONCLUSIONS:Adults with chronic pain who were enrolled in NYS Medicaid before the COVID-19 pandemic had lower MOUD utilization than those without chronic pain. MOUD initiation was briefly disrupted, with disparities especially in racial/ethnic minority groups. Flexible MOUD policy initiatives may have maintained overall treatment utilization, but disparities in initiation and care continuity remain for patients with chronic pain, and particularly for racial/ethnic minoritized subgroups.

IMPORTANCE/UNASSIGNED:Two states modified laws to remove or substantially reduce criminal penalties for any drug possession. The hypothesis was that removing criminal penalties for drug possession may reduce fatal drug overdoses due to reduced incarceration and increased calls for help at the scene of an overdose. OBJECTIVE/UNASSIGNED:To evaluate whether decriminalization of drug possession in Oregon and Washington was associated with changes in either direction in fatal drug overdose rates. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cohort study used a synthetic control method approach to examine whether there were changes in drug possession laws and fatal drug overdose rates in Oregon and Washington in the postpolicy period (February 1, 2021, to March 31, 2022, in Oregon and March 1, 2021, to March 31, 2022, in Washington). A counterfactual comparison group (synthetic controls) was created for Oregon and Washington, using 48 states and the District of Columbia, that did not implement similar policies during the study period (January 1, 2018, to March 31, 2022). For 2018-2021, final multiple cause-of-death data from the National Vital Statistics System (NVSS) were used. For 2022, provisional NVSS data were used. Drug overdose deaths were identified using International Statistical Classification of Diseases and Related Health Problems, 10th Revision underlying cause-of-death codes X40-X44, X60-X64, X85, and Y10-Y14. EXPOSURES/UNASSIGNED:In Oregon, Measure 110 went into effect on February 1, 2021. In Washington, the Washington Supreme Court decision in State v Blake occurred on February 25, 2021. MAIN OUTCOME/UNASSIGNED:Monthly fatal drug overdose rates. RESULTS/UNASSIGNED:Following the implementation of Measure 110, absolute monthly rate differences between Oregon and its synthetic control were not statistically significant (probability = 0.26). The average rate difference post Measure 110 was 0.268 fatal drug overdoses per 100 000 state population. Following the implementation of the policy change in Washington, the absolute monthly rate differences between Washington and synthetic Washington were not statistically significant (probability = 0.06). The average rate difference post Blake was 0.112 fatal drug overdoses per 100 000 state population. CONCLUSIONS AND RELEVANCE/UNASSIGNED:This study found no evidence of an association between legal changes that removed or substantially reduced criminal penalties for drug possession in Oregon and Washington and fatal drug overdose rates. Additional research could examine potential other outcomes as well as longer-term associations with fatal drug overdose overall and across racial and ethnic groups.

OBJECTIVE:The COVID-19 pandemic contributed to healthcare disruptions for patients with chronic pain. Following initial disruptions, national policies were enacted to expand access to long-term opioid therapy (LTOT) for chronic pain and opioid use disorder (OUD) treatment services, which may have modified risk of opioid overdose. We examined associations between LTOT and/or OUD with fatal and non-fatal opioid overdoses, and whether the pandemic moderated overdose risk in these groups. METHODS:We analyzed New York State Medicaid claims data (3/1/2019-12/31/20) of patients with chronic pain (N = 236,391). We used generalized estimating equations models to assess associations between LTOT and/or OUD (neither LTOT or OUD [ref], LTOT only, OUD only, and LTOT and OUD) and the pandemic (03/2020-12/2020) with opioid overdose. RESULTS:The pandemic did not significantly (ns) affect opioid overdose among patients with LTOT and/or OUD. While patients with LTOT (vs. no LTOT) had a slight increase in opioid overdose during the pandemic (pre-pandemic: aOR:1.65, 95% CI:1.05, 2.57; pandemic: aOR:2.43, CI:1.75,3.37, ns), patients with OUD had a slightly attenuated odds of overdose during the pandemic (pre-pandemic: aOR:5.65, CI:4.73, 6.75; pandemic: aOR:5.16, CI:4.33, 6.14, ns). Patients with both LTOT and OUD also experienced a slightly reduced odds of opioid overdose during the pandemic (pre-pandemic: aOR:5.82, CI:3.58, 9.44; pandemic: aOR:3.70, CI:2.11, 6.50, ns). CONCLUSIONS:Findings demonstrated no significant effect of the pandemic on opioid overdose among people with chronic pain and LTOT and/or OUD, suggesting pandemic policies expanding access to chronic pain and OUD treatment services may have mitigated the risk of opioid overdose.