Faculty Bibliography

BACKGROUND:Treatment for opioid use disorder (OUD) is highly effective, yet it remains dramatically underutilized. Individuals with OUD have disproportionately high rates of hospitalization and low rates of addiction treatment. Hospital-based addiction consult services offer a potential solution by using multidisciplinary teams to evaluate patients, initiate medication for addiction treatment (MAT) in the hospital, and connect patients to post-discharge care. We are studying the effectiveness of an addiction consult model [Consult for Addiction Treatment and Care in Hospitals (CATCH)] as a strategy for engaging patients with OUD in treatment as the program rolls out in the largest municipal hospital system in the US. The primary aim is to evaluate the effectiveness of CATCH in increasing post-discharge initiation and engagement in MAT. Secondary aims are to assess treatment retention, frequency of acute care utilization and overdose deaths and their associated costs, and implementation outcomes. METHODS:A pragmatic trial at six hospitals, conducted in collaboration with the municipal hospital system and department of health, will be implemented to study the CATCH intervention. Guided by the RE-AIM evaluation framework, this hybrid effectiveness-implementation study (Type 1) focuses primarily on effectiveness and also measures implementation outcomes to inform the intervention's adoption and sustainability. A stepped-wedge cluster randomized trial design will determine the impact of CATCH on treatment outcomes in comparison to usual care for a control period, followed by a 12-month intervention period and a 6- to 18-month maintenance period at each hospital. A mixed methods approach will primarily utilize administrative data to measure outcomes, while interviews and focus groups with staff and patients will provide additional information on implementation fidelity and barriers to delivering MAT to patients with OUD. DISCUSSION/CONCLUSIONS:Because of their great potential to reduce the negative health and economic consequences of untreated OUD, addiction consult models are proliferating in response to the opioid epidemic, despite the absence of a strong evidence base. This study will provide the first known rigorous evaluation of an addiction consult model in a large multi-site trial and promises to generate knowledge that can rapidly transform practice and inform the potential for widespread dissemination of these services. TRIAL REGISTRATION/BACKGROUND:NCT03611335.

BACKGROUND:Federal regulations (42 CFR Part 2) provide special privacy protections for persons seeking treatment for substance use disorders. Primary care providers, hospitals, and health care organizations have struggled to balance best practices for medical care with adherence to 42 CFR Part 2, but little formal research has examined this issue. The aim of this study was to explore institutional variability in the interpretation and implementation of 42 CFR Part 2 regulations related to health systems data privacy practices, policies, and information technology architecture. METHODS:This was a cross-sectional qualitative study using purposive sampling to conduct interviews with privacy/legal officers (n = 17) and information technology specialists (n = 10) from 15 integrated healthcare organizations affiliated with three research nodes of the National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network (CTN). Trained staff completed a short survey and digitally recorded semi-structured qualitative interview with each participant. Interviews were transcribed and coded within Atlas.ti. Framework analysis was used to identify and organize key themes across selected codes. RESULTS:Participants voiced concern over balancing patient safety with 42 CFR Part 2 privacy protections. Although similar standards of protection regarding release of information outside of the health system was described, numerous workarounds were used to manage intra-institutional communication and care coordination. To align 42 CFR Part 2 restrictions with electronic health records, health systems used sensitive note designation, "break the glass" technology, limited role-based access for providers, and ad hoc solutions (e.g., provider messaging). CONCLUSIONS:In contemporary integrated care systems, substance-related EHR records (e.g., patient visit history, medication logs) are often accessible internally without specific consent for sharing despite the intent of 42 CFR Part 2. Recent amendments to 42 CFR Part 2 have not addressed information sharing needs within integrated care settings.

BACKGROUND:Medical comorbidity may influence treatment initiation and engagement for alcohol and other drug (AOD) use disorders. We examined the association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement measures. METHODS:We used electronic health record and insurance claims data from 7 US health care systems to identify patients with AOD use disorders between October 1, 2014, and August 15, 2015 (N = 86,565). Among patients identified with AOD use disorders in outpatient and emergency department (ED) settings, we examined how Charlson/Deyo comorbidity index scores and medical complications of AOD use were associated with treatment initiation. Among those who initiated treatment in inpatient and outpatient/ED settings, we also examined how comorbidity and AOD use-related medical complications were associated with treatment engagement. Analyses were conducted using generalized estimating equation logistic regression modeling. RESULTS:Among patients identified as having an AOD diagnosis in outpatient and ED settings (n = 69,965), Charlson/Deyo comorbidity index scores of 2 or more were independently associated with reduced likelihood of initiation (risk ratio [RR] = 0.80, 95% confidence interval [CI] = 0.74, 0.86; reference score = 0), whereas prior-year diagnoses of cirrhosis (RR = 1.25, 95% CI = 1.12, 1.35) and pancreatic disease (RR = 1.34, 95% CI = 1.15, 1.56) were associated with greater likelihood of initiation. Among those who were identified in outpatient/ED settings and initiated, higher comorbidity scores were associated with lower likelihood of engagement (score 1: RR = 0.85, 95% CI = 0.76, 0.94; score 2+: RR = 0.61, 95% CI = 0.53, 0.71). CONCLUSION/CONCLUSIONS:Medical comorbidity was associated with lower likelihood of initiating or engaging in AOD treatment, but cirrhosis and pancreatic disease were associated with greater likelihood of initiation. Interventions to improve AOD treatment initiation and engagement for patients with comorbidities are needed, such as integrating medical and AOD treatment.

BACKGROUND:Current data suggest that opioid misuse or opioid use disorder (OUD) may be over represented among tobacco users. However, this association remains understudied in primary care settings. A better understanding of the extent of heterogeneity in opioid misuse among primary care patients who use tobacco may have implications for improved primary care-based screening, prevention, and intervention approaches. METHODS:Data were derived from a sample of 2000 adult (aged ≥18) primary care patients across 5 distinct clinics. Among past-year tobacco users (n = 882), we assessed the prevalence of opioid misuse and OUD by sociodemographic characteristics and past-year polysubstance use. Latent class analysis (LCA) was used to identify heterogeneous subgroups of tobacco users according to past-year polysubstance use patterns. Multinomial logistic regression was used to examine variables associated with LCA-defined class membership. RESULTS:Past-year tobacco use was reported by >84% of participants who reported past-year opioid misuse or OUD. Among those reporting past-year tobacco use, the prevalence of past-year opioid misuse and OUD was 14.0% and 9.5%, respectively. The prevalence of opioid misuse or OUD was highest among tobacco users who were male or unemployed. Three LCA-defined classes among tobacco users were identified including a tobacco-minimal drug use group (78.0%), a tobacco-cannabis use group (10.1%), and a tobacco-opioid/polydrug use group (11.9%). Class membership differed by sociodemographic characteristics. CONCLUSIONS:Results from this study support the benefit of more comprehensive assessment of and/or monitoring for opioid misuse among primary care patients who use tobacco, particularly for those who are male, unemployed, or polydrug users.

BACKGROUND:Alcohol and drug use are leading causes of morbidity and mortality that frequently go unidentified in medical settings. As part of a multi-phase study to implement electronic health record-integrated substance use screening in primary care clinics, we interviewed key clinical stakeholders to identify current substance use screening practices, barriers to screening, and recommendations for its implementation. METHODS:Focus groups and individual interviews were conducted with 67 stakeholders, including patients, primary care providers (faculty and resident physicians), nurses, and medical assistants, in two urban academic health systems. Themes were identified using an inductive approach, revised through an iterative process, and mapped to the Knowledge to Action (KTA) framework, which guides the implementation of new clinical practices (Graham et al. in J Contin Educ Health Prof 26(1):13-24, 2006). RESULTS:Factors affecting implementation based on KTA elements were identified from participant narratives. Identifying the problem: Participants consistently agreed that having knowledge of a patient's substance use is important because of its impacts on health and medical care, that substance use is not properly identified in medical settings currently, and that universal screening is the best approach. Assessing barriers: Patients expressed concerns about consequences of disclosing substance use, confidentiality, and the individual's own reluctance to acknowledge a substance use problem. Barriers identified by providers included individual-level factors such as lack of clinical knowledge and training, as well as systems-level factors including time pressure, resources, lack of space, and difficulty accessing addiction treatment. Adapting to the local context: Most patients and providers stated that the primary care provider should play a key role in substance use screening and interventions. Opinions diverged regarding the optimal approach to delivering screening, although most preferred a patient self-administered approach. Many providers reported that taking effective action once unhealthy substance use is identified is crucial. CONCLUSIONS:Participants expressed support for substance use screening as a valuable part of medical care, and identified individual-level as well as systems-level barriers to its implementation. These findings suggest that screening programs should clearly communicate the goals of screening to patients and proactively counteract stigma, address staff concerns regarding time and workflow, and provide education as well as treatment resources to primary care providers.

The prevalence of urine tampering within office-based opioid treatment (OBOT) is not currently known. This study was a cross-sectional analysis of an OBOT practice in New York City that experienced both a change in provider and a change in electronic medical record software. At that time, every patient in the practice received a urine drug test for "quantitative buprenorphine metabolites." METHODS: Outcomes of the first three urine drug tests were tabulated and analyzed with specific attention to the frequency of buprenorphine-positive (bup+), norbuprenorphine-negative (norbup-) samples, a pattern consistent with urine tampering. RESULTS: On the first sample 6/33 (18%) of patients submitted bup+/norbup- samples, and an additional 3 patients submitted bup+/norbup- samples on subsequent urine tests. Retention to the end of the study period among patients with bup+/norbup- samples was 33%, while in those with bup+/norbup+samples it was 96%. A scatter plot of norbuprenorphine vs. buprenorphine levels estimated that a ratio of <0.2 indicated tampering. CONCLUSION: Testing for buprenorphine metabolites yields valuable clinical information. The prevalence of a result pattern consistent with tampering by "urine spiking," the addition of unconsumed buprenorphine into the urine sample, may be higher than previous estimates. Previous lower cutoffs of the norbuprenorphine:buprenorphine metabolic ratio may miss a substantial proportion of these likely tampered samples.

BACKGROUND: There are limited data about the extent of DSM-5 substance use disorders (SUDs) among primary care patients. METHODS: This study analyzed data from a multisite validation study of a substance use screening instrument conducted in a diverse sample of 2000 adults aged >/=18 years recruited from five primary care practices in four states. Prevalence and correlates of 12-month DSM-5 SUDs were examined. RESULTS: Overall, 75.5% of the sample used any substance, including alcohol (62.0%), tobacco (44.1%), or illicit drugs/nonmedical medications (27.9%) in the past 12 months (marijuana 20.8%, cocaine 7.3%, opioids 4.8%, sedatives 4.1%, heroin 3.9%). The prevalence of any 12-month SUD was 36.0% (mild disorder 14.2%, moderate/severe disorder 21.8%): tobacco 25.3% (mild 11.5%, moderate/severe 13.8%); alcohol 13.9% (mild 6.9%, moderate/severe 7.0%); and any illicit/nonmedical drug 14.0% (mild 4.0%, moderate/severe 10.0%). Among past 12-month users, a high proportion of tobacco or drug users met criteria for a disorder: tobacco use disorder 57.4% (26.1% mild, 31.3% moderate/severe) and any drug use disorder 50.2% (14.3% mild, 35.8% moderate/severe); a lower proportion of alcohol users (22.4%) met criteria for alcohol use disorder (11.1% mild, 11.3% moderate/severe). Over 80% of adults with opioid/heroin use disorder met criteria for a moderate/severe disorder. Younger ages, male sex, and low education were associated with increased odds of having SUD. CONCLUSION: These findings reveal the high prevalence of SUDs in primary care and underscore the need to identify and address them.

BACKGROUND: The Tobacco, Alcohol, Prescription Medication, and Other Substance use (TAPS) tool is a combined two-part screening and brief assessment developed for adult primary care patients. The tool's first-stage screening component (TAPS-1) consists of four items asking about past 12-month use for four substance categories, with response options of never, less than monthly, monthly, weekly, and daily or almost daily. OBJECTIVE: To validate the TAPS-1 in primary care patients. DESIGN: Participants completed the TAPS tool in self- and interviewer-administered formats, in random order. In this secondary analysis, the TAPS-1 was evaluated against DSM-5 substance use disorder (SUD) criteria to determine optimal cut-points for identifying unhealthy substance use at three severity levels (problem use, mild SUD, and moderate-to-severe SUD). PARTICIPANTS: Two thousand adult patients at five primary care sites. MAIN MEASURES: DSM-5 SUD criteria were determined via the modified Composite International Diagnostic Interview. Oral fluid was used as a biomarker of recent drug use. KEY RESULTS: Optimal frequency-of-use cut-points on the self-administered TAPS-1 for identifying SUDs were >/= monthly use for tobacco and alcohol (sensitivity = 0.92 and 0.71, specificity = 0.80 and 0.85, AUC = 0.86 and 0.78, respectively) and any reported use for illicit drugs and prescription medication misuse (sensitivity = 0.93 and 0.89, specificity = 0.85 and 0.91, AUC = 0.89 and 0.90, respectively). The performance of the interviewer-administered format was similar. When administered first, the self-administered format yielded higher disclosure rates for past 12-month alcohol use, illicit drug use, and prescription medication misuse. Frequency of use alone did not provide sufficient information to discriminate between gradations of substance use problem severity. Among those who denied drug use on the TAPS-1, less than 4% had a drug-positive biomarker. CONCLUSIONS: The TAPS-1 can identify unhealthy substance use in primary care patients with a high level of accuracy, and may have utility in primary care for rapid triage.

Hospitalized patients have high rates of unhealthy substance use, which has important impacts on health both during and after hospitalization, but is infrequently identified in the absence of screening. The Substance Use Brief Screen (SUBS) was developed as a brief, self-administered instrument to identify use of tobacco, alcohol, illicit drugs, and non-medical use of prescription drugs, and was previously validated in primary care patients. This study assessed the diagnostic accuracy of the SUBS in comparison to longer screening instruments to identify unhealthy and high-risk alcohol and drug use in hospitalized current smokers. Participants were 439 patients, aged 18 and older, who were admitted to either two urban safety-net hospitals in New York City and enrolled in a smoking cessation trial. We measured the performance of the SUBS for identifying illicit drug and non-medical use of prescription drugs in comparison to a modified Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) and its performance for identifying excessive alcohol use in comparison to the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C). At the standard cutoff (response other than 'never' indicates a positive screen), the SUBS had a sensitivity of 98% (95% CI 95-100%) and specificity of 61% (95% CI 55-67%) for unhealthy alcohol use, a sensitivity of 85% (95% CI 80-90%) and specificity of 75% (95% CI 78-87%) for illicit drug use, and a sensitivity of 73% (95% CI 61-83%) and specificity of 83% (95% CI 78-87%) for prescription drug non-medical use. For identifying high-risk use, a higher cutoff (response of '3 or more days' of use indicates a positive screen), the SUBS retained high sensitivity (77-90%), and specificity was 62-88%. The SUBS can be considered as an alternative to longer screening instruments, which may fit more easily into busy inpatient settings. Further study is needed to evaluate its validity using gold standard measures in hospitalized populations.