Faculty Bibliography

PURPOSE/OBJECTIVE:Estimates of HIV prevalence, and how it changes over time, are needed to inform action (e.g., resource allocation) to improve HIV-related public health. However, creating adequate estimates of (diagnosed and undiagnosed) HIV prevalence is challenging due to biases in samples receiving HIV testing and due to difficulties enumerating key risk populations. To our knowledge, estimates of HIV prevalence among high risk heterosexuals in the United States produced for geographic areas smaller than the entire nation have to date been only for single years and/or for single cities (or other single geographic locations). METHODS:The present study addresses these gaps by using multilevel modeling on multiple data series, in combination with previous estimates of HIV prevalence among heterosexuals from the extant literature, to produce annual estimates of HIV prevalence among high risk heterosexuals for each of 89 metropolitan statistical areas, from 1992 to 2013. It also produces estimates for these MSAs and years by racial/ethnic subgroup to allow for an examination of change over time in racial/ethnic disparities in HIV prevalence among high risk heterosexuals. RESULTS:The resulting estimates suggest that HIV prevalence among high risk heterosexuals has decreased steadily, on average, from 1992 to 2013. Examination of these estimates by racial/ ethnic subgroup suggests that this trend is primarily due to decreases among Black and Hispanic/Latino high risk heterosexuals. HIV prevalence among white high risk heterosexuals remained steady over time at around 1% during the study period. Although HIV prevalence among Black and Hispanic/Latino high risk heterosexuals was much higher (approximately 3.5% and 3.3%, respectively) than that among whites in 1992, over time these differences decreased as HIV prevalence decreased over time among these subgroups. By 2013, HIV prevalence among Hispanic/Latino high risk heterosexuals was estimated to be very similar to that among white high risk heterosexuals (approximately 1%), with prevalence among Black high risk heterosexuals still estimated to be almost twice as high. CONCLUSIONS:It is likely that as HIV incidence has decreased among heterosexuals from 1992 to 2013, mortality due to all causes has remained disparately high among racial/ethnic minorities, thereby outpacing new HIV cases. Future research should aim to empirically examine this by comparing changes over time in estimated HIV incidence among heterosexuals to changes over time in mortality and causes of death among HIV-positive heterosexuals, by racial/ethnic subgroup.

BACKGROUND:Limiting the incidence of opioid-naïve patients who transition to long-term opioid use (i.e., continual use for > 90 days) is a key strategy for reducing opioid-related harms. OBJECTIVE:To identify variables constructed from data routinely collected by prescription drug monitoring programs that are associated with opioid-naïve patients' likelihood of transitioning to long-term use after an initial opioid prescription. DESIGN/METHODS:Statewide cohort study using prescription drug monitoring program data PARTICIPANTS: All opioid-naïve patients in California (no opioid prescriptions within the prior 2 years) age ≥ 12 years prescribed an initial oral opioid analgesic from 2010 to 2017. METHODS AND MAIN MEASURES/UNASSIGNED:Multiple logistic regression models using variables constructed from prescription drug monitoring program data through the day of each patient's initial opioid prescription, and, alternatively, data available up to 30 and 60 days after the initial prescription were constructed to identify probability of transition to long-term use. Model fit was determined by the area under the receiver operating characteristic curve (C-statistic). KEY RESULTS/RESULTS:Among 30,569,125 episodes of patients receiving new opioid prescriptions, 1,809,750 (5.9%) resulted in long-term use. Variables with the highest adjusted odds ratios included concurrent benzodiazepine use, ≥ 2 unique prescribers, and receipt of non-pill, non-liquid formulations. C-statistics for the day 0, day 30, and day 60 models were 0.81, 0.88, and 0.94, respectively. Models assessing opioid dose using the number of pills prescribed had greater discriminative capacity than those using milligram morphine equivalents. CONCLUSIONS:Data routinely collected by prescription drug monitoring programs can be used to identify patients who are likely to develop long-term use. Guidelines for new opioid prescriptions based on pill counts may be simpler and more clinically useful than guidelines based on days' supply or milligram morphine equivalents.

BACKGROUND:Drug overdoses surged during the COVID-19 pandemic, underscoring the need for expanded and accessible substance use disorder (SUD) treatment. Relatively little is known about the experiences of patients receiving treatment during the pandemic. METHODS:We worked with 21 harm reduction and drug treatment programs in nine states and the District of Columbia from August 2020 to January 2021. Programs distributed study recruitment cards to clients. Clients responded to the survey by calling a study hotline and providing a unique study identification number. Our survey included detailed questions about use of SUD treatment prior to and since the COVID-19 pandemic. We identified settings where individuals received treatment and, for those treated for opioid use disorder, we examined use of medications for opioid use disorder. Individuals also reported whether they had received telehealth treatment and pandemic related treatment changes (e.g., more take-home methadone). We calculated p-values for differences pre and since COVID-19. RESULTS:We interviewed 587 individuals of whom 316 (53.8%) were in drug treatment both before and during the COVID-19 pandemic. Individuals in treatment reported substantial reductions in in-person service use since the start of the pandemic, including a 27 percentage point reduction (p<.001) in group counseling sessions and 28 percentage point reduction in mutual aid group participation (p<.001). By contrast, individuals reported a 21 percentage point increase in receipt of overdose education (p<.001). Most people receiving medications for opioid use disorder reported taking methadone and had high continuity of treatment (86.1% received methadone pre-COVID and 87.1% since-COVID, p=.71). Almost all reported taking advantage of new policy changes such as counseling by video/phone, increased take-home medication, or fewer urine drug screens. Overall, respondents reported relatively high satisfaction with their treatment and with telehealth adaptations (e.g., 80.2% reported "I'm able to get all the treatment that I need"). CONCLUSIONS:Accommodations to treatment made under the federal public health emergency appear to have sustained access to treatment in the early months of the pandemic. Since these changes are set to expire after the official public health emergency declaration, further action is needed to meet the ongoing need.

BACKGROUND:The COVID-19 pandemic has exerted a significant toll on the lives of people who use opioids (PWUOs). At the same time, more flexible regulations around provision of opioid use disorder (OUD) services have led to new opportunities for facilitating access to services for PWUOs. In the current scoping review, we describe new services and service modifications implemented by treatment and harm reduction programs serving PWUO, and discuss implications for policy and practice. METHODS:Literature searches were conducted within PubMed, LitCovid, Embase, and PsycInfo for English-language studies published in 2020 that describe a particular program, service, or intervention aimed at facilitating access to OUD treatment and/or harm reduction services during the COVID-19 pandemic. Abstracts were independently screened by two reviewers. Relevant studies were reviewed in full and those that met inclusion criteria underwent final data extraction and synthesis (n = 25). We used a narrative synthesis approach to identify major themes around key service modifications and innovations implemented across programs serving PWUO. RESULTS:Reviewed OUD treatment and harm reduction services spanned five continents and a range of settings from substance use treatment to street outreach programs. Innovative service modifications to adapt to COVID-19 circumstances primarily involved expanded use of telehealth services (e.g., telemedicine visits for buprenorphine, virtual individual or group therapy sessions, provision of donated or publicly available phones), increased take-home medication allowances for methadone and buprenorphine, expanded uptake of long-acting opioid medications (e.g. extended-release buprenorphine and naltrexone), home delivery of services (e.g. MOUD, naloxone and urine drug screening), outreach and makeshift services for delivering MOUD and naloxone, and provision of a safe supply of opioids. CONCLUSIONS:The COVID-19 pandemic has posed multiple challenges for PWUOs, while simultaneously accelerating innovations in policies, care models, and technologies to lower thresholds for life-saving treatment and harm reduction services. Such innovations highlight novel patient-centered and feasible approaches to mitigating OUD related harms. Further studies are needed to assess the long-term impact of these approaches and inform policies that improve access to care for PWUOs.

BACKGROUND:Hundreds of laws aimed at reducing inappropriate prescription opioid dispensing have been implemented in the United States, yet heterogeneity in provisions and their simultaneous implementation have complicated evaluation of impacts. We apply a hypothesis-generating, multi-stage, machine learning approach to identify salient law provisions and combinations associated with dispensing rates to test in future research. METHODS:Using 162 prescription opioid law provisions capturing prescription drug monitoring program (PDMP) access, reporting and administration features, pain management clinic provisions, and prescription opioid limits, we used regularization approaches and random forest models to identify laws most predictive of county-level and high-dose dispensing. We stratified analyses by overdose epidemic phases-the prescription opioid phase (2006-2009), heroin phase (2010-2012), and fentanyl phase (2013-2016)-to further explore pattern shifts over time. RESULTS:PDMP patient data access provisions most consistently predicted high dispensing and high-dose dispensing counties. Pain management clinic-related provisions did not generally predict dispensing measures in the prescription opioid phase but became more discriminant of high dispensing and high-dose dispensing counties over time, especially in the fentanyl period. Predictive performance across models was poor, suggesting prescription opioid laws alone do not strongly predict dispensing. CONCLUSIONS:Our systematic analysis of 162 law provisions identified patient data access and several pain management clinic provisions as predictive of county prescription opioid dispensing patterns. Future research employing other types of study designs is needed to test these provisions' causal relationships with inappropriate dispensing, and to examine potential interactions between PDMP access and pain management clinic provisions.

The Centers for Disease Control and Prevention's 2016 Guideline for Prescribing Opioids for Chronic Pain aimed to reduce unsafe opioid prescribing. It is unknown whether the guideline influenced prescribing in the target population: patients with chronic, noncancer pain, who may be at particular risk for opioid-related harms. To study this question, we used 2014-18 data from a commercial claims database to examine associations between the release of the guideline and opioid dispensing in a national cohort of more than 450,000 patients with four common chronic pain diagnoses. We also examined whether any reductions associated with the guideline were larger for diagnoses for which there existed stronger expert consensus against opioid prescribing. Overall, the guideline was associated with substantial reductions in dispensing opioids, including a reduction in patients' rate of receiving at least one opioid prescription by approximately 20 percentage points by December 2018 compared with the counterfactual, no-guideline scenario. However, the reductions in dispensing did not vary by the strength of expert consensus against opioid prescribing. These findings suggest that although voluntary guidelines can drive changes in prescribing, questions remain about how clinicians are tailoring opioid reductions to best benefit patients.

BACKGROUND:The endocannabinoid system has been implicated in physiological processes fundamental to pain, giving plausibility to the hypothesis that cannabis may be used as a substitute or complement to prescription opioids in the management of chronic pain. We examined the association of medical cannabis licensure with likelihood of prescription opioid receipt using administrative records. METHODS:This study linked registry information for medical cannabis licensure with records from the prescription drug monitoring program from April 1, 2016 to March 31, 2019 to create a population-based, retrospective cohort in Rhode Island. We examined within-person changes in receipt of any opioid prescription and receipt of an opioid prescription with a morphine equivalent dose of 50 mg or more, and of 90 mg or more. RESULTS:The sample included 5,296 participants with medical cannabis license. Medical cannabis licensure was not associated with the odds of filling any opioid prescription (OR: 0.99; 95% CI: 0.94-0.1.05) or the odds of filling a prescription with a morphine equivalent dose of 50 mg or more (OR: 0.93; 95% CI: 0.84-1.04) and 90 mg or more (OR: 0.99; 95% CI: 0.86-1.15). CONCLUSION/CONCLUSIONS:Medical cannabis licensure was not associated with subsequent cessation and reduction in prescription opioid use. Re-scheduling of cannabis will allow for the conduct of randomized controlled trials to determine the efficacy of medical cannabis as an alternative to prescription opioid use or a complement to the use of lower doses of prescription opioids in patients with chronic pain.

BACKGROUND:Variation in drug policies, norms, and substance use over time and across countries may affect the normative sequences of adolescent substance use initiation. We estimated relative and absolute time-varying associations between prior alcohol and tobacco use and adolescent marijuana initiation in Argentina and Chile. Relative measures quantify the magnitude of the associations, whereas absolute measures quantify excess risk. METHODS:We analyzed repeated, cross-sectional survey data from the National Surveys on Drug Use Among Secondary School Students in Argentina (2001-2014) and Chile (2001-2017). Participants included 8th, 10th, and 12th grade students (N = 680,156). Linear regression models described trends over time in the average age of first use of alcohol, tobacco, and marijuana. Logistic regression models were used to estimate time-varying risk ratios and risk differences of the associations between prior alcohol and tobacco use and current-year marijuana initiation. RESULTS:Average age of marijuana initiation increased and then decreased in Argentina and declined in Chile. In both countries, the relative associations between prior tobacco use and marijuana initiation weakened amid declining rates of tobacco use; e.g., in Argentina, the risk ratio was 19.9 (95% CI: 9.0-30.8) in 2001 and 11.6 (95% CI: 9.0-13.2) in 2014. The relative association between prior alcohol use and marijuana initiation weakened Chile, but not in Argentina. On the contrary, risk differences (RD) increased substantially across both relationships and countries, e.g., in Argentina, the RD for tobacco was 3% (95% CI: 0.02-0.03) in 2001 and 12% (95% CI: 0.11-0.13) in 2014. CONCLUSION/CONCLUSIONS:Diverging trends in risk ratios and risk differences highlight the utility of examining multiple measures of association. Variation in the strength of the associations over time and place suggests the influence of environmental factors. Increasing risk differences indicate alcohol and tobacco use may be important targets for interventions to reduce adolescent marijuana use.