Faculty Bibliography

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.

OBJECTIVE:To characterize the prevalence of tobacco, alcohol, and drug use and the acceptability of screening in university health centers. PARTICIPANTS/METHODS:Five hundred and two consecutively recruited students presenting for primary care visits in February and August, 2015, in two health centers. METHODS:Participants completed anonymous substance use questionnaires in the waiting area, and had the option of sharing results with their medical provider. We examined screening rates, prevalence, and predictors of sharing results. RESULTS:Past-year use was 31.5% for tobacco, 67.1% for alcohol (>4 drinks/day), 38.6% for illicit drugs, and 9.2% for prescription drugs (nonmedical use). A minority (43.8%) shared screening results. Sharing was lowest among those with moderate-high risk use of tobacco (OR =0.37, 95% CI 0.20-0.69), alcohol (OR =0.48, 95% CI 0.25-0.90), or illicit drugs (OR =0.38, 95% CI 0.20-0.73). CONCLUSIONS:Screening can be integrated into university health services, but students with active substance use may be uncomfortable discussing it with medical providers.

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.

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.

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.

BACKGROUND: Alcohol and drug use is a leading cause of morbidity and mortality that frequently goes unidentified in medical settings. As part of a multi-phase study to implement the NIDA Common Data Elements for collecting substance use screening information in electronic health records (EHRs), we interviewed key clinical stakeholders with a goal of identifying barriers and facilitators affecting the implementation of substance use screening in primary care clinics. METHODS: Focus groups and individual qualitative interviews were conducted with 67 stakeholders, including primary care patients, medical providers (faculty and resident physicians, nurses), and medical assistants, in two urban academic health systems. Themes were identified, discussed, and revised through an iterative process, and mapped to the Knowledge to Action (KTA) framework (Graham, 2006), which guides the selection and implementation of new clinical practices. RESULTS: Factors affecting implementation based on KTA elements were identified from participant narratives. Identifying the problem: Participants unanimously agreed that having knowledge of a patient's substance use is important because of its impacts on health andmedical care, that substance use is not properly identified in medical settings, and that universal screening is the best approach. Adapting knowledge: The majority of patients and providers stated that the primary care provider should play a key role in substance use screening and interventions. There was discrepancy of opinion regarding the optimal approach to delivering screening. Some felt that patients should self-administer questionnaires, while others thought that patients would be more comfortable having face-to-face discussions with their primary care provider - though not with other members of the care team. Many providers reported that being able to take effective action once unhealthy substance use is identified is crucial. Assessing barriers: Patients expressed concerns about confidentiality, 'denial', and providers' lack of empathy. Barriers identified by providers included individual-level factors such as lack of knowledge and training, and systems-level factors including lack of time, resources, and space, disjointed communication between members of the medical team, and difficulty accessing addiction treatment. CONCLUSIONS: Based on these findings, we designed and are testing an implementation strategy utilizing universal screening, patient self-administered questionnaires, and EHR-integrated clinical decision support to assist providers in conducting brief motivational counseling and linking patients to behavioral health services, to address unhealthy substance use in primary care clinics

BACKGROUND: There is a need for a rapid substance use screening instrument to detect unhealthy tobacco, alcohol, and other drug use among primary care patients. The Tobacco, Alcohol, Prescription Medications, and other Substances Tool (TAPS Tool) is a combined 2-part screening and brief assessment developed for adult primary care patients. Its screening component (TAPS-1) consists of 4 items asking about past 12-month use of four substance categories (any tobacco, 5 or more drinks/day for men [4 for women] of alcohol, any illicit drug use, and any non-medical use of prescription drugs. Categorical response options are: never, less than monthly, monthly, weekly, and daily or almost daily. The objective of this preplanned secondary analysis was to validate the TAPS-1 against the DSM-5 substance use disorder (SUD) criteria. METHODS: This was a multi-site study evaluating the concurrent validity of the TAPS-1 compared to SUD criteria conducted among 2,000 adult primary care patients in 5 clinics located in 4 Eastern US states. Participants completed the TAPS Tool in a self- administered version on a tablet computer and in an interviewer-administered format, in random order. They were then administered a modified version of the Composite International Diagnostic Interview (CIDI) to determine DSM-5 criteria. Optimal cut points for identifying SUDs were obtained using receiver operating characteristics (ROC) analysis to obtain sensitivity (sens), specificity (spec), positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC). RESULTS: The optimal cut-point on the interviewer-administered TAPS-1 for identifying SUDs was '> monthly use' for tobacco (sens = .95, spec = .80, PPV= .62, NPV = .98, AUC = .88) and for alcohol (sens = .68, spec = .87, PPV = .45, NPV = .94, AUC = .77). In contrast, 'any use' was the optimal cut-point for illicit drugs (sens = .93, spec = .86, PPV = .50, NPV = .99, AUC = .89) and for nonmedical use of prescription drugs (sens = .90, spec = .95, PPV = .41, NPV = 1.0, AUC= .93). The self-administered format had similar performance. CONCLUSIONS: The TAPS-1 was able to rapidly screen adult primary care patients for SUDs. Thus, the TAPS-1 could assist health care providers in determining which patients might need a focused, in-depth substance use assessment