Faculty Bibliography

OBJECTIVES/OBJECTIVE:We explored medications for opioid use disorder treatment (MOUD) utilization in six New York City public hospitals that implemented the "Consultation for Addiction Care and Treatment in Hospitals (CATCH)" program. METHODS:CATCH rolled out between October 2018 and February 2020. Data from the electronic health record were analyzed for the first year post-implementation. Eligible cases included adults with an opioid-related diagnosis admitted to inpatient departments served by CATCH, with a stay of ≥1 night. Patients were classified as receiving an MOUD order if there was at least 1 order of buprenorphine, methadone, or naltrexone. Logistic regression modeled the impact of CATCH consults on MOUD orders, controlling for demographic and clinical characteristics with hospital as a random effect. RESULT/RESULTS:Among 2117 eligible patients, 71.4% were male, with a mean age of 51.2 years, and 27.2% identified as Black, 21.2% as White, and 34.5% as Hispanic. MOUD was ordered in 60.9% of admissions, and 41.5% had a completed CATCH consult. Patients identified as Black had lower odds of receiving a MOUD order than those identified as White (OR: 0.52, 95% CI: 0.38-0.71; P < 0.001). Patients with a CATCH consult had higher odds of receiving a MOUD order (OR: 3.22, 95% CI: 2.54-4.07; P < 0.001). CONCLUSION/CONCLUSIONS:Majority of patients in our sample received a MOUD order, with higher odds among those with a CATCH consult. Further research is needed on the drivers of racial disparities in MOUD, and other contextual, organizational, and population-specific barriers and facilitators contributing to receipt of hospital-based addiction consult services and MOUD.

BACKGROUND:In response to the heavy burden of untreated substance use disorders (SUD) in hospital patients, many health systems are implementing addiction consult services staffed by interprofessional teams that diagnose SUD, make recommendations for SUD care in the hospital, and link patients to post-discharge treatment. In 2018, the New York City public hospital system began rolling out the Consult for Addiction Treatment and Care in Hospitals (CATCH) program in six hospitals. CATCH teams are comprised of an addiction-trained medical provider, social worker or addiction counselor, and peer counselor. METHODS:The study conducted qualitative interviews with CATCH staff at all six participating hospitals as part of a pragmatic trial studying the effectiveness and implementation of CATCH. The Consolidated Framework for Implementation Research (CFIR) framework guided interviews conducted from 2018 to 2021 with 26 staff at the start of implementation and with 33 staff 9-12 months post-implementation. The study team created a codebook a priori and further refined it through additional coding of initial interviews. Codes were systematically analyzed using the CFIR. RESULTS:Barriers and facilitators spanned four CFIR domains: inner setting, outer setting, process, and individual characteristics. Barriers identified were primarily related to the outer and inner settings, including patient characteristics and limited resources (e.g. medical comorbidities, homelessness), insurance, CATCH team role confusion, and infrastructure deficits (e.g., availability of physical space). Additional barriers related to process (workload burden), and characteristics of individuals (stigma and lack of comfort treating SUD among medical teams). Facilitators were mostly related to the characteristics of individuals on the CATCH team (advantages and expertise of the CATCH peer counselor, CATCH team communication and cohesiveness) and inner setting (CATCH team relationships with hospital staff, hospital leadership buy-in and support, and infrastructure). Community networks (outer setting) and CATCH training resources (process) were also facilitators of program implementation. CONCLUSION/CONCLUSIONS:Addiction consult services have great potential for improving care for hospital patients with SUD, but as new programs in busy hospital settings they face barriers to implementation that could impact their effectiveness. Barriers may be particularly impactful for programs operating in safety-net hospitals, given limited resources within the health system and the multiple and complex needs of their patients. Understanding the strengths of these programs as well as the barriers to their implementation is critical to utilizing addiction consult services effectively.

BACKGROUND:Despite proliferation of acute-care interventions to initiate medications for opioid use disorder (MOUD), significant challenges remain to supporting care continuity following discharge. Research is needed to inform effective hospital strategies to support patient transitions to ongoing MOUD in the community. OBJECTIVE:To inform a taxonomy of care transition strategies to support MOUD continuity from hospital to community-based settings and assess their perceived impact and feasibility among experts in the field. DESIGN/METHODS:A modified Delphi consensus process through three rounds of electronic surveys. PARTICIPANTS/METHODS:Experts in hospital-based opioid use disorder (OUD) treatment, care transitions, and hospital-based addiction treatment. MAIN MEASURES/METHODS:Delphi participants rated the impact and feasibility of 14 OUD care transition strategies derived from a review of the scientific literature on a scale from 1 to 9 over three survey rounds. Panelists were invited to suggest additional care transition strategies. Agreement level was calculated based on proportion of ratings within three points of the median. KEY RESULTS/RESULTS:Forty-five of 71 invited panelists participated in the survey. Agreement on impact was strong for 12 items and moderate for 10. Agreement on feasibility was strong for 11 items, moderate for 7, and poor for 4. Strategies with highest ratings on impact and feasibility included initiation of MOUD in-hospital and provision of buprenorphine prescriptions or medications before discharge. All original 14 strategies and 8 additional strategies proposed by panelists were considered medium- or high-impact and were incorporated into a final taxonomy of 22 OUD care transition strategies. CONCLUSIONS:Our study established expert consensus on impactful and feasible hospital strategies to support OUD care transitions from the hospital to community-based MOUD treatment, an area with little empirical research thus far. It is the hope that this taxonomy serves as a stepping-stone for future evaluations and clinical practice implementation toward improved MOUD continuity and health outcomes.

INTRODUCTION/BACKGROUND:Six hospitals within the New York City public hospital system implemented the Consult for Addiction Treatment and Care in Hospitals (CATCH) program, an interprofessional addiction consult service. A stepped-wedge cluster randomized controlled trial tested the effectiveness of CATCH for increasing initiation and engagement in post-discharge medication for opioid use disorder (MOUD) treatment among hospital patients with opioid use disorder (OUD). The objective of this study was to identify facility characteristics that were associated with stronger performance of CATCH. METHODS:This study used a mixed methods multiple-case study design. The six hospitals in the CATCH evaluation were each assigned a case rating according to intervention reach. Reach was considered high if ≥50 % of hospitalized OUD patients received an MOUD order. Cross-case rating comparison identified attributes of high-performing hospitals and inductive and deductive approaches were used to identify themes. RESULTS:Higher-performing hospitals exhibited attributes that were generally absent in lower-performing hospitals, including (1) complete medical provider staffing; (2) designated office space and resources for CATCH; (3) existing integrated OUD treatment resources; and (4) limited overlap between the implementation period and COVID-19 pandemic. CONCLUSIONS:Hospitals with attributes indicative of awareness and integration of OUD services into general care were generally higher performing than hospitals that had siloed OUD treatment programs. Future implementations of addiction consult services may benefit from an increased focus on hospital- and community-level buy-in and efforts to integrate MOUD treatment into general care.

BACKGROUND:Evidence maps are emerging data visualization of a systematic review. There are no published evidence maps summarizing opioid use disorder (OUD) interventions. AIM/OBJECTIVE:Our aim was to publish an interactive summary of all peer-reviewed interventional and observational trials assessing the treatment of OUD and common clinical outcomes. METHODS:PubMed, Embase, PsycInfo, Cochrane Central Register of Clinical Trials, and Web of Science were queried using multiple OUD-related MESH terms, without date limitations, for English-language publications. Inclusions were human subjects, treatment of OUD, OUD patient or community-level outcomes, and systematic reviews of OUD interventions. Exclusions were laboratory studies, reviews, and case reports. Two reviewers independently scanned abstracts for inclusion before coding eligible full-text articles by pre-specified filters: research design, study population, study setting, intervention, outcomes, sample size, study duration, geographical region, and funding sources. RESULTS:The OUD Evidence Map (https://med.nyu.edu/research/lee-lab/research/opioid-use-disorder-treatment-evidence-map) identified and assessed 12,933 relevant abstracts through 2020. We excluded 9455 abstracts and full text reviewed 2839 manuscripts; 888 were excluded, 1591 were included in the final evidence map. The most studied OUD interventions were methadone (n = 754 studies), buprenorphine (n = 499), and naltrexone (n = 134). The most common outcomes were heroin/opioid use (n = 708), treatment retention (n = 557), and non-opioid drug use (n = 368). Clear gaps included a wider array of opioid agonists for treatment, digital behavioral interventions, studies of OUD treatments in criminal justice settings, and overdose as a clinical outcome. CONCLUSION/CONCLUSIONS:This OUD Evidence Map highlights the importance of pharmacologic interventions for OUD and reductions in opioid use. Future iterations will update results annually and scan policy-level interventions.

The United States is experiencing an unprecedented opioid crisis, with a record of about 93,000 opioid-involved overdose deaths in 2020, which requires rapid and substantial scaling up of access to effective treatment for opioid use disorder. Only 18% of individuals with opioid use disorder receive evidence-based treatment, and strategies to increase access are hindered by a lack of treatment providers. Using a case study from the largest municipal hospital system in the United States, the authors describe the effects of a workforce shortage on health system responses to the opioid crisis. This national problem demands a multipronged approach, including federal programs to grow and diversify the pipeline of addiction providers, medical education initiatives, and enhanced training and mentorship to increase the capacity of allied clinicians to treat patients who have an opioid use disorder. Workforce development should be combined with structural reforms for integrating addiction treatment into mainstream medical care and with new treatment models, including telehealth, which can lower patient barriers to accessing treatment.

Criminal justice involved individuals have a high rate of opioid overdose death following release. In March 2020, New York City jails released over 1000 inmates due to concern of COVID-19 outbreaks in county jails. The closure of addiction treatment clinics further complicated efforts to expand access to medications for opioid use disorder among criminal justice involved adults. The New York City Health + Hospitals Virtual Buprenorphine Clinic established in March 2020 offered low-threshold telemedicine-based opioid treatment with buprenorphine-naloxone, specifically for criminal justice involved adults post-release. We describe a case report of the novel role of tele-conferencing for the provision of buprenorphine-naloxone for jail-released adults with opioid use disorder experiencing homelessness during the COVID-19 pandemic. The patient is a 49-year-old male with severe opioid use disorder released from New York City jail as part of its early release program. He then started using diverted buprenorphine-naloxone, and 1 month later a harm-reduction specialist at his temporary housing at a hotel referred him to an affiliated buprenorphine provider and then eventually to the New York City Health + Hospitals Virtual Buprenorphine Clinic, where he was continued on buprenorphine-naloxone, and was followed biweekly thereafter until being referred to an office-based opioid treatment program. For this patient, telemedicine-based opioid treatment offered a safe and feasible approach to accessing medication for opioid use disorder during the COVID-19 pandemic and following incarceration.

OBJECTIVES/OBJECTIVE:The purpose of this study was to assess the feasibility and clinical impact of telemedicine-based opioid treatment with buprenorphine-naloxone following the Coronavirus disease 2019 pandemic. METHODS:Participants included in this retrospective analysis consisted of adult New York City residents with opioid use disorder eligible for enrollment in the NYC Health+Hospitals Virtual Buprenorphine Clinic between March and May 2020 (n = 78). Follow-up data were comprised of rates of retention in treatment at 2 months, referrals to community treatment, and induction-related events. RESULTS:During the initial 9 weeks of clinic operations, the clinic inducted 78 patients on to buprenorphine-naloxone and completed 252 visits. Patient referrals included non-NYC Health + Hospitals (n = 22, 28.2%) and NYC Health + Hospitals healthcare providers (n = 17, 21.8%), homeless shelter staff (n = 13, 16.7%), and the NYC Health + Hospitals jail reentry program in Rikers Island (n = 11, 14.1%). At 8 weeks, 42 patients remained in care (53.8%), 21 were referred to a community treatment program (26.9%), and 15 were lost to follow-up (19.2%). No patients were terminated from care due to disruptive behavior or suspicions of diversion or misuse of Buprenorphine. Adverse clinical outcomes were uncommon and included persistent withdrawal symptoms (n = 8, 4.3%) and one nonfatal opioid overdose (0.5%). CONCLUSIONS:Telemedicine-based opioid treatment and unobserved home induction on buprenorphine-naloxone offers a safe and feasible approach to expand the reach of opioid use disorder treatment, primary care, and behavioral health for a highly vulnerable urban population during an unprecedented natural disaster.

CONTEXT/BACKGROUND:Use of electronic cigarettes (e-cigarettes) has rapidly increased despite unclear longitudinal health effects. Once thought to be a safer alternative to tobacco smoke, it is possible that e-cigarettes expose the user to similar carcinogenic byproducts during the vaping process. These toxicants are metabolized and excreted in the urine, and may have oncogenic implications for bladder urothelium. OBJECTIVE:To characterize and summarize known urinary carcinogenic biomarkers in e-cigarette users as they relate to the risk of developing bladder cancer. EVIDENCE ACQUISITION/METHODS:A systematic literature search was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and included PubMed, Embase, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL). Relevant articles published in peer-reviewed journals, through January 2019, that reported on urinary biomarkers in e-cigarettes users were included. Parent compounds and urinary biomarkers were classified according to the International Agency for Research on Cancer Monographs on the Evaluation of Carcinogenic Risks to Humans and cross referenced using the Collaborative on Health and the Environment, Toxicant and Disease Database to determine a link to bladder cancer, grouped by strength of evidence. EVIDENCE SYNTHESIS/RESULTS:Our initial search identified 1385 articles, 22 of which met final inclusion criteria and were included for analysis. In summation, these studies described 40 different parent compounds and four metals found in the urine of e-cigarette users. Since each parent compound can be metabolized several different ways, 63 unique toxicant or carcinogenic metabolite biomarkers were identified. Compared with nonuser controls, e-cigarette users had higher concentrations of urinary biomarkers of several carcinogenic compounds linked to bladder cancer. The majority of studies were limited by heterogeneous reporting and a dearth of control individuals who had never smoked. CONCLUSIONS:Biomarkers of carcinogens, several with a strong link to bladder cancer, are present in the urine of e-cigarette users. Long-term implications of urothelial exposure to these toxicants are unknown but concerning, given the similarities to tobacco smoke and its established relationship with bladder cancer. Further study on the urological safety of e-cigarettes is necessary. PATIENT SUMMARY/UNASSIGNED:Our review shows that several carcinogens that have a known link to bladder cancer are present in the urine of electronic cigarette (e-cigarette) users. Further study on the urological safety of e-cigarettes is necessary.