Faculty Bibliography

BACKGROUND:Mandates for prescriber use of prescription drug monitoring programs (PDMPs), databases tracking controlled substance prescriptions, are associated with reduced opioid analgesic (OA) prescribing but may contribute to care discontinuity and chronic opioid therapy (COT) cycling, or multiple initiations and terminations. OBJECTIVE:To estimate risks of COT cycling in New York City (NYC) due to the New York State (NYS) PDMP mandate, compared to risks in neighboring New Jersey (NJ) counties. DESIGN/METHODS:We estimated cycling risk using Prentice, Williams, and Peterson gap-time models adjusted for age, sex, OA dose, payment type, and county population density, using a life-table difference-in-differences design. Failure time was duration between cycles. In a subgroup analysis, we estimated risk among patients receiving high-dose prescriptions. Sensitivity analyses tested robustness to cycle volume considering only first cycles using Cox proportional hazard models. PARTICIPANTS/METHODS:The cohort included 7604 patients dispensed 12,695 prescriptions. INTERVENTIONS/METHODS:The exposure was the August 2013 enactment of the NYS PDMP prescriber use mandate. MAIN MEASURES/METHODS:We used monthly, patient-level data on OA prescriptions dispensed in NYC and NJ between August 2011 and July 2015. We defined COT as three sequential months of prescriptions, permitting 1-month gaps. We defined recurrence as re-initiation of COT after at least 2 months without prescriptions. The exposure was enactment of the PDMP mandate in NYC; NJ was unexposed. KEY RESULTS/RESULTS:Enactment of the NYS PDMP mandate was associated with an adjusted hazard ratio (HR) for cycling of 1.01 (95% CI, 0.94-1.08) in NYC. For high-dose prescriptions, the risk was 1.16 (95% CI, 1.01-1.34). Sensitivity analyses estimated an overall risk of 1.01 (95% CI, 0.94-1.11) and high-dose risk of 1.09 (95% CI, 0.91-1.31). CONCLUSIONS:The PDMP mandate had no overall effect on COT cycling in NYC but increased cycling risk among patients receiving high-dose opioid prescriptions by 16%, highlighting care discontinuity.

OBJECTIVE:Suicidal behavior and bullying victimization are important indicators of adolescent psychological distress, and are patterned by sex, race/ethnicity and sexual identity. This study aimed to estimate trends and disparities in these factors along key demographics. METHOD/METHODS:Youth Risk Behavior Survey data (2015-2019, N=44,066) were collected biennially through national cross-sectional surveys of US school-attending adolescents. Survey-weighted logistic regressions examined disparities in past-year bullying and suicidal behavior, overall and by demographics. RESULTS:Bullying in 2019 was highest for female (vs. male) students (OR=1.82, 95% CI:[1.62, 2.06]), American Indian/Alaskan Native (vs White) students (OR= 1.48, [0.91, 2.41], p>.05), and gay/lesbian (vs heterosexual) students (OR= 2.81, [2.07, 3.81]). Suicidal behavior disparities affected similar groups. There was minimal evidence for shifts in disparities since 2015, with the exception of bullying for gay/lesbian adolescents. The prevalence of bullying victimization among gay and lesbian adolescents went from 31.6% to 44.5% between 2015 and 2019, surpassing the bisexual and "Not Sure" groups to be the sexual identity group with the highest rate of bullying victimization. CONCLUSION/CONCLUSIONS:Interventions that operate on multiple structural levels and empower marginalized youth are needed.

BACKGROUND AND AIMS/OBJECTIVE:In 2013, Uruguay became the first country to legalize and regulate the production and distribution of cannabis for recreational use. We measured whether Uruguay's non-commercial model of recreational cannabis legalization was associated with changes in the prevalence of risky and frequent cannabis use among secondary school students. DESIGN/METHODS:We used data from repeated cross-sectional surveys of secondary students in Uruguay and Chile (2007-2018). Using a difference-in-difference approach, we evaluated changes in the prevalence of past-year, past-month, any risky and frequent cannabis use following enactment (2014) and implementation (2016) of cannabis legalization among the full sample of secondary students and among students who reported past-year/month use. We examined changes separately for students aged 12-17, and students for whom cannabis became legally accessible, ages 18-21. SETTING/METHODS:Uruguay and Chile (2007-2018). PARTICIPANTS/METHODS:grade (n=204,730). MEASUREMENTS/METHODS:Past-year and past-month cannabis use; any risky cannabis use measured with the Cannabis Abuse Screening Test (CAST); and frequent cannabis use (10+ days in the past-month). FINDINGS/RESULTS:We found a decrease in past-year and past-month use following enactment or implementation. Among students ages 18-21, post-enactment, we observed a transitory increase in 2014 that decreased thereafter for: any risky use among those who reported past-year use (prevalence difference [PD]=13.5%; 95% confidence interval [CI]: 2.0, 24.9), frequent use in the full sample (PD=4.5%; 95%CI: 1.0, 8.1), and frequent use among those who reported past-month use (PD=16.8%; 95%CI: 1.9, 31.8). CONCLUSION/CONCLUSIONS:The legalization of recreational cannabis in Uruguay was not associated with overall increases in either past-year/past-month cannabis use or with multi-year changes in any risky and frequent cannabis use among young people.

BACKGROUND:Substance use disorders (SUD) elevate the risk for COVID-19 hospitalization, but studies are inconsistent on the relationship of SUD to COVID-19 mortality. METHODS:Veterans Health Administration (VHA) patients treated in 2019 and evaluated in 2020 for COVID-19 (n=5,556,315), of whom 62,303 (1.1%) tested positive for COVID-19 (COVID-19+). Outcomes were COVID-19+ by 11/01/20, hospitalization, ICU admission, or death within 60 days of a positive test. Main predictors were any ICD-10-CM SUDs, with substance-specific SUDs (cannabis, cocaine, opioid, stimulant, sedative) explored individually. Logistic regression produced unadjusted and covariate-adjusted odds ratios (OR; aOR). RESULTS:Among COVID-19+ patients, 19.25% were hospitalized, 7.71% admitted to ICU, and 5.84% died. In unadjusted models, any SUD and all substance-specific SUDs except cannabis use disorder were associated with COVID-19+(ORs=1.06-1.85); adjusted models produced similar results. Any SUD and all substance-specific SUDs were associated with hospitalization (aORs: 1.24-1.91). Any SUD, cocaine and opioid disorder were associated with ICU admission in unadjusted but not adjusted models. Any SUD, cannabis, cocaine, and stimulant disorders were inversely associated with mortality in unadjusted models (OR=0.27-0.46). After adjustment, associations with mortality were no longer significant. In ad hoc analyses, adjusted odds of mortality were lower among the 49.9% of COVID-19+ patients with SUD who had SUD treatment in 2019, but not among those without such treatment. CONCLUSIONS:In VHA patients, SUDs are associated with COVID-19 hospitalization but not COVID-19 mortality. SUD treatment may provide closer monitoring of care, ensuring that these patients received needed medical attention, enabling them to ultimately survive serious illness.

BACKGROUND:Opioid treatment programs (OTPs) serve as daily essential services for people with opioid use disorder. This study seeks to identify modifications to operations and adoption of safety measures at Pennsylvania OTPs during the COVID-19 pandemic. METHODS:A 25-min online survey to clinical and administrative directors at all 103 state-licensed OTPs in Pennsylvania was fielded from September to November 2020. Survey domains included: 1) changes to services, client volume, hours and staffing during the COVID-19 pandemic 2) types of services modifications 3) safety protocols to reduce COVID-19 transmission 4) challenges to operations during the pandemic. RESULTS:Forty-seven directors responded, for a response rate of 45%. Almost all respondents reported making some service modification (96%, n = 43). Almost half (47%, n = 21) of respondents reported reductions in the number of clients served. OTPs were more likely to adopt safety protocols that did not require significant funding, such as limiting the number of people entering the site (100%, n = 44), posting COVID-safety information (100%, n = 44), enforcing social distancing (98%, n = 43), and increasing sanitation (100%, n = 44). Only 34% (n = 14) of OTPS provided N95 masks to most or all staff. Respondents reported that staff's stress and negative mental health (86%, n = 38) and staff caregiving responsibilities (84%, n = 37) during the pandemic were challenges to maintaining OTP operations. CONCLUSION/CONCLUSIONS:OTPs faced numerous challenges to operations and adoption of safety measures during the COVID-19 pandemic. Funding mechanisms and interventions to improve adoption of safety protocols, staff mental health as well as research on patient experiences and preferences can inform further OTP adaptation to the COVID-19 pandemic and future emergency planning.

In the United States, combined stimulant/opioid overdose mortality has risen dramatically over the last decade. These increases may particularly affect non-Hispanic Black and Hispanic populations. We used death certificate data from the US National Center for Health Statistics (2007-2019) to compare state-level trends in overdose mortality due to opioids in combination with 1) cocaine and 2) methamphetamine and other stimulants (MOS) across racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Asian American/Pacific Islander). To avoid unstable estimates from small samples, we employed principles of small area estimation and a Bayesian hierarchical model, enabling information-sharing across groups. Black Americans experienced severe and worsening mortality due to opioids in combination with both cocaine and MOS, particularly in eastern states. Cocaine/opioid mortality increased 575% among Black people versus 184% in White people (Black, 0.60 to 4.05 per 100,000; White, 0.49 to 1.39 per 100,000). MOS/opioid mortality rose 16,200% in Black people versus 3,200% in White people (Black, 0.01 to 1.63 per 100,000; White, 0.09 to 2.97 per 100,000). Cocaine/opioid overdose mortality rose sharply among Hispanic and Asian Americans. State-group heterogeneity highlighted the importance of data disaggregation and methods to address small sample sizes. Research to understand the drivers of these trends and expanded efforts to address them are needed, particularly in minoritized groups.

BACKGROUND AND AIM/OBJECTIVE:In Uruguay, residents age 18 and older seeking legal cannabis must register with the government and choose one of three supply mechanisms: self-cultivation, non-profit cannabis clubs or pharmacies. This is the first paper to measure the association between type of legal cannabis supply mechanism and traffic crashes involving injuries. DESIGN/METHODS:Ecological study using ordinary least squares regression to examine how department-level variation in registrations (overall and by type) is associated with traffic crashes involving injuries. SETTING/METHODS:Uruguay. CASES/METHODS:532 department-quarters. MEASUREMENTS/METHODS:Quarterly cannabis registration counts at the department level and incident-level traffic crash data were obtained from government agencies. The analyses controlled for department-level economic and demographic characteristics and, as a robustness check, we included traffic violations involving alcohol for departments reporting this information. Department-level data on crashes, registrations and alcohol violations were denominated by the number of residents ages 18 and older. FINDINGS/RESULTS:From 2013 to 2019, the average number of registrations at the department-quarter level per 10 000 residents age 18 and older for self-cultivation, club membership and pharmacy purchasing were 17.7 (SD = 16.8), 3.6 (SD = 8.6), and 25.1 (SD = 50.4), respectively. In our multivariate regression analyses, we did not find a statistically significant association between the total number of registrations and traffic crashes with injuries (β = -0.007; P = 0.398; 95% CI = -0.023, 0.01). Analyses focused on the specific supply mechanisms found a consistent, positive and statistically significant association between the number of individuals registered as self-cultivators and the number of traffic crashes with injuries (β = 0.194; P = 0.008; 95% CI = 0.058, 0.329). Associations for other supply mechanisms were inconsistent across the various model specifications. CONCLUSIONS:In Uruguay, the number of people allowed to self-cultivate cannabis is positively associated with traffic crashes involving injuries. Individual-level analyses are needed to assess better the factors underlying this association.

Predictors of opioid overdose death in neighborhoods are important to identify, both to understand characteristics of high-risk areas and to prioritize limited prevention and intervention resources. Machine learning methods could serve as a valuable tool for identifying neighborhood-level predictors. We examined statewide data on opioid overdose death from Rhode Island (log-transformed rates for 2016-2019) and 203 covariates from the American Community Survey for 742 US Census block groups. The analysis included a least absolute shrinkage and selection operator (LASSO) algorithm followed by variable importance rankings from a random forest algorithm. We employed double cross-validation, with 10 folds in the inner loop to train the model and 4 outer folds to assess predictive performance. The ranked variables included a range of dimensions of socioeconomic status, including education, income and wealth, residential stability, race/ethnicity, social isolation, and occupational status. The R2 value of the model on testing data was 0.17. While many predictors of overdose death were in established domains (education, income, occupation), we also identified novel domains (residential stability, racial/ethnic distribution, and social isolation). Predictive modeling with machine learning can identify new neighborhood-level predictors of overdose in the continually evolving opioid epidemic and anticipate the neighborhoods at high risk of overdose mortality.

OBJECTIVE:Despite their effectiveness in preventing the transmission of HIV among people who inject drugs (PWID), syringe services programs (SSPs) in many settings are hampered by social and political opposition. We aimed to estimate the impact of closure and temporary interruption of SSP on the HIV epidemic in a rural US setting. METHODS:Using an agent-based model calibrated to observed surveillance data, we simulated HIV risk behaviors and transmission in adult populations who inject and do not inject drugs in Scott County, Indiana. We projected HIV incidence and prevalence between 2020-2025 for scenarios with permanent closure, delayed closure (one additional renewal for 24 months before closure), and temporary closure (lasting 12 months) of an SSP in comparison to persistent SSP operation. RESULTS:With sustained SSP operation, we projected an incidence rate of 0.15 per 100 person-years among the overall population [95% simulation interval: 0.06-0.28]. Permanently closing the SSP would cause an average of 58.4% increase in the overall incidence rate during 2021-2025, resulting in a higher prevalence of 60.8% [50.9%-70.6%] (18.7% increase) among PWID by 2025. A delayed closure would increase the incidence rate by 38.9%. A temporary closure would cause 12 (35.3%) more infections during 2020-2021. CONCLUSIONS:Our analysis suggests that temporary interruption and permanent closure of existing SSPs operating in rural US may lead to "rebound" HIV outbreaks among PWID. To reach and sustain HIV epidemic control, it will be necessary to maintain existing and implement new SSPs in combination with other prevention interventions.