Exemplar Hospital initiation trial to Enhance Treatment Engagement (EXHIT ENTRE): protocol for CTN-0098B a randomized implementation study to support hospitals in caring for patients with opioid use disorder.

BACKGROUND: Hospitalizations involving opioid use disorder (OUD) are increasing. Medications for opioid use disorder (MOUD) reduce mortality and acute care utilization. Hospitalization is a reachable moment for initiating MOUD and arranging for ongoing MOUD engagement following hospital discharge. Despite existing quality metrics for MOUD initiation and engagement, few hospitals provide hospital based opioid treatment (HBOT). This protocol describes a cluster-randomized hybrid type-2 implementation study comparing low-intensity and high-intensity implementation support strategies to help community hospitals implement HBOT. METHODS: Four state implementation hubs with expertise in initiating HBOT programs will provide implementation support to 24 community hospitals (6 hospitals/hub) interested in starting HBOT. Community hospitals will be randomized to 24-months of either a low-intensity intervention (distribution of an HBOT best-practice manual, a lecture series based on the manual, referral to publicly available resources, and on-demand technical assistance) or a high-intensity intervention (the low-intensity intervention plus funding for a hospital HBOT champion and regular practice facilitation sessions with an expert hub). The primary efficacy outcome, adapted from the National Committee on Quality Assurance, is the proportion of patients engaged in MOUD 34-days following hospital discharge. Secondary and exploratory outcomes include acute care utilization, non-fatal overdose, death, MOUD engagement at various time points, hospital length of stay, and discharges against medical advice. Primary, secondary, and exploratory outcomes will be derived from state Medicaid data. Implementation outcomes, barriers, and facilitators are assessed via longitudinal surveys, qualitative interviews, practice facilitation contact logs, and HBOT sustainability metrics. We hypothesize that the proportion of patients receiving care at hospitals randomized to the high-intensity arm will have greater MOUD engagement following hospital discharge. DISCUSSION: Initiation of MOUD during hospitalization improves MOUD engagement post hospitalization. Few studies, however, have tested different implementation strategies on HBOT uptake, outcome, and sustainability and only one to date has tested implementation of a specific type of HBOT (addiction consultation services). This cluster-randomized study comparing different intensities of HBOT implementation support will inform hospitals and policymakers in identifying effective strategies for promoting HBOT dissemination and adoption in community hospitals. TRIAL REGISTRATION: NCT04921787.

Research Priorities for Expansion of Opioid Use Disorder Treatment in the Community Pharmacy.

In the last decade, the U.S. opioid overdose crisis has magnified, particularly since the introduction of synthetic opioids, including fentanyl. Despite the benefits of medications for opioid use disorder (MOUD), only about a fifth of people with opioid use disorder (OUD) in the U.S. receive MOUD. The ubiquity of pharmacists, along with their extensive education and training, represents great potential for expansion of MOUD services, particularly in community pharmacies. The National Institute on Drug Abuse's National Drug Abuse Treatment Clinical Trials Network (NIDA CTN) convened a working group to develop a research agenda to expand OUD treatment in the community pharmacy sector to support improved access to MOUD and patient outcomes. Identified settings for research include independent and chain pharmacies and co-located pharmacies within primary care settings. Specific topics for research included adaptation of pharmacy infrastructure for clinical service provision, strategies for interprofessional collaboration including health service models, drug policy and regulation, pharmacist education about OUD and OUD treatment, including didactic, experiential, and interprofessional curricula, and educational interventions to reduce stigma towards this patient population. Together, expanding these research areas can bring effective MOUD to where it is most needed.

Potential effect of antidepressants on remission from cocaine use disorder - A nationwide matched retrospective cohort study.

BACKGROUND: Cocaine use disorder (CUD) is a significant public health issue for which there is no Food and Drug Administration-approved pharmacotherapy. Depressive disorders are common psychiatric comorbidity amongst individuals with CUD. METHODS: A retrospective cohort study was conducted among 161,544 patients diagnosed with CUD and depression to evaluate the effectiveness of 13 antidepressants on CUD remission. For any antidepressant found to be associated with CUD remission that had an additional indication, we conducted an additional analysis to evaluate the effectiveness of the candidate drug in patients with CUD with that indication. We then analyzed publicly genomic and functional databases to identify potential explanatory mechanisms of action of the candidate drug in the treatment of CUD. RESULTS: Among these antidepressants, bupropion was associated with higher rates of CUD remission compared to propensity-score matched patients prescribed other antidepressants: hazard ratio (HR) and 95% confidence interval (CI) 1.57 (95% CI: 1.27-1.94). Bupropion is also approved for smoking cessation. We identified CUD patients with co-occurring nicotine dependence and observed that patients prescribed bupropion displayed a higher rate of CUD remission compared to matched individuals prescribed other drugs for nicotine dependence: 1.38 (95% CI: 1.11-1.71). Genetic and functional analyses revealed that bupropion interacts with four protein-encoding genes (COMT, DRD2, SLC6A3, and SLC6A4) which are also associated with CUD and targets CUD-associated pathways including serotonergic synapses, cocaine addiction, and dopaminergic synapses. CONCLUSIONS: Our findings suggest that bupropion might be considered a treatment for improving CUD remission in patients with CUD and co-occurring depression or nicotine dependence.

Buprenorphine use and courses of care for opioid use disorder treatment within the Veterans Health Administration.

BACKGROUND: Retention of patients in buprenorphine medication treatment for opioid use disorder (B-MOUD) reduces harms associated with opioid use disorder (OUD). We sought to characterize the patients receiving B-MOUD and courses of B-MOUD in a large healthcare system. METHODS: We conducted a retrospective, open cohort study of patients with OUD who either did or did not receive B-MOUD courses within the Veterans Health Administration (VHA) from January 2006 through July 2019, using VHA clinical data. We compared patients receiving or not receiving B-MOUD, characterized B-MOUD courses (e.g., length and doses), and examined persistence, across patient characteristics, over time. We used analyses for normally or non-normally distributed continuous variables, categorical data, and persistence over time (Kaplan-Meier persistence curves). RESULTS: We identified 255,726 Veterans with OUD; 40,431 (15.8%) had received 63,929 B-MOUD courses. Compared to patients with OUD without B-MOUD, patients with B-MOUD were younger, more often of white race, and had more co-morbidities. The frequency of new B-MOUD starts and prevalent B-MOUD patients ranged from 1550 and 1989 in 2007 to 8146 and 16,505 in 2018, respectively. The median duration of B-MOUD was 157 (IQR: 37-537) days for all courses and 33.8% patients had more than one course. The average proportion days covered was 90% (SD: 0.15), and the average prescribed daily dose was 13.44 (SD: 6.5). CONCLUSIONS: Within a VHA B-MOUD cohort, courses increased more than 10-fold from 2006 to 2016 with nearly half of patients experiencing multiple courses. Patient demographics seem to dictate the length of courses.

Surmounting Withdrawal to Initiate Fast Treatment with Naltrexone (SWIFT): A stepped wedge hybrid type 1 effectiveness-implementation study.

BACKGROUND: Extended-release injectable naltrexone (XR-NTX) is an effective treatment for opioid use disorder (OUD), but initiation remains a barrier to implementation. Standard practice requires a 10- to 15-day inpatient admission prior to XR-NTX initiation and involves a methadone or buprenorphine taper followed by a 7- to 10-day washout, as recommended in the Prescribing Information for XR-NTX. A 5- to 7-day rapid induction approach was developed that utilizes low-dose oral naltrexone and non-opioid medications. METHODS: The CTN-0097 Surmounting Withdrawal to Initiate Fast Treatment with Naltrexone (SWIFT) study was a hybrid type I effectiveness-implementation trial that compared the effectiveness of the standard procedure (SP) to the rapid procedure (RP) for XR-NTX initiation across six community inpatient addiction treatment units, and evaluated the implementation process. Sites were randomized to RP every 14 weeks in an optimized stepped wedge design. Participants (target recruitment = 450) received the procedure (SP or RP) that the site was implementing at time of admission. The hypothesis was RP will be non-inferior to SP on proportion of inpatients who receive XR-NTX, with a shorter admission time for RP. Superiority testing of RP was planned if the null hypothesis of inferiority of RP to SP was rejected. DISCUSSION: If RP for XR-NTX initiation is shown to be effective, the shorter inpatient stay could make XR-NTX more feasible and have an important public health impact expanding access to OUD pharmacotherapy. Further, a better understanding of facilitators and barriers to RP implementation can help with future translatability and uptake to other community programs. TRIAL REGISTRATION: NCT04762537 Registered February 21, 2021.

Repurposing ketamine to treat cocaine use disorder: integration of artificial intelligence-based prediction, expert evaluation, clinical corroboration and mechanism of action analyses.

BACKGROUND AND AIMS: Cocaine use disorder (CUD) is a significant public health issue for which there is no Food and Drug Administration (FDA) approved medication. Drug repurposing looks for new cost-effective uses of approved drugs. This study presents an integrated strategy to identify repurposed FDA-approved drugs for CUD treatment. DESIGN: Our drug repurposing strategy combines artificial intelligence (AI)-based drug prediction, expert panel review, clinical corroboration and mechanisms of action analysis being implemented in the National Drug Abuse Treatment Clinical Trials Network (CTN). Based on AI-based prediction and expert knowledge, ketamine was ranked as the top candidate for clinical corroboration via electronic health record (EHR) evaluation of CUD patient cohorts prescribed ketamine for anesthesia or depression compared with matched controls who received non-ketamine anesthesia or antidepressants/midazolam. Genetic and pathway enrichment analyses were performed to understand ketamine's potential mechanisms of action in the context of CUD. SETTING: The study utilized TriNetX to access EHRs from more than 90 million patients world-wide. Genetic- and functional-level analyses used DisGeNet, Search Tool for Interactions of Chemicals and Kyoto Encyclopedia of Genes and Genomes databases. PARTICIPANTS: A total of 7742 CUD patients who received anesthesia (3871 ketamine-exposed and 3871 anesthetic-controlled) and 7910 CUD patients with depression (3955 ketamine-exposed and 3955 antidepressant-controlled) were identified after propensity score-matching. MEASUREMENTS: EHR analysis outcome was a CUD remission diagnosis within 1 year of drug prescription. FINDINGS: Patients with CUD prescribed ketamine for anesthesia displayed a significantly higher rate of CUD remission compared with matched individuals prescribed other anesthetics [hazard ratio (HR) = 1.98, 95% confidence interval (CI) = 1.42-2.78]. Similarly, CUD patients prescribed ketamine for depression evidenced a significantly higher CUD remission ratio compared with matched patients prescribed antidepressants or midazolam (HR = 4.39, 95% CI = 2.89-6.68). The mechanism of action analysis revealed that ketamine directly targets multiple CUD-associated genes (BDNF, CNR1, DRD2, GABRA2, GABRB3, GAD1, OPRK1, OPRM1, SLC6A3, SLC6A4) and pathways implicated in neuroactive ligand-receptor interaction, cAMP signaling and cocaine abuse/dependence. CONCLUSIONS: Ketamine appears to be a potential repurposed drug for treatment of cocaine use disorder.

Comparison of Medical Cannabis Use Reported on a Confidential Survey vs Documented in the Electronic Health Record Among Primary Care Patients.

Importance: Patients who use cannabis for medical reasons may benefit from discussions with clinicians about health risks of cannabis and evidence-based treatment alternatives. However, little is known about the prevalence of medical cannabis use in primary care and how often it is documented in patient electronic health records (EHR). Objective: To estimate the primary care prevalence of medical cannabis use according to confidential patient survey and to compare the prevalence of medical cannabis use documented in the EHR with patient report. Design, Setting, and Participants: This study is a cross-sectional survey performed in a large health system that conducts routine cannabis screening in Washington state where medical and nonmedical cannabis use are legal. Among 108 950 patients who completed routine cannabis screening (between March 28, 2019, and September 12, 2019), 5000 were randomly selected for a confidential survey about cannabis use, using stratified random sampling for frequency of past-year use and patient race and ethnicity. Data were analyzed from November 2020 to December 2021. Exposures: Survey measures of patient-reported past-year cannabis use, medical cannabis use (ie, explicit medical use), and any health reason(s) for use (ie, implicit medical use). Main Outcomes and Measures: Survey data were linked to EHR data in the year before screening. EHR measures included documentation of explicit and/or implicit medical cannabis use. Analyses estimated the primary care prevalence of cannabis use and compared EHR-documented with patient-reported medical cannabis use, accounting for stratified sampling and nonresponse. Results: Overall, 1688 patients responded to the survey (34% response rate; mean [SD] age, 50.7 [17.5] years; 861 female [56%], 1184 White [74%], 1514 non-Hispanic [97%], and 1059 commercially insured [65%]). The primary care prevalence of any past-year patient-reported cannabis use on the survey was 38.8% (95% CI, 31.9%-46.1%), whereas the prevalence of explicit and implicit medical use were 26.5% (95% CI, 21.6%-31.3%) and 35.1% (95% CI, 29.3%-40.8%), respectively. The prevalence of EHR-documented medical cannabis use was 4.8% (95% CI, 3.45%-6.2%). Compared with patient-reported explicit medical use, the sensitivity and specificity of EHR-documented medical cannabis use were 10.0% (95% CI, 4.4%-15.6%) and 97.1% (95% CI, 94.4%-99.8%), respectively. Conclusions and Relevance: These findings suggest that medical cannabis use is common among primary care patients in a state with legal use, and most use is not documented in the EHR. Patient report of health reasons for cannabis use identifies more medical use compared with explicit questions about medical use.

Pain Severity and Interference and Substance Use Among Community Pharmacy Patients Prescribed Opioids: A Secondary Analysis of the PHARMSCREEN Study.

This secondary analysis examined relationships between pain severity and interference and substance use among patients filling opioid prescriptions in Indiana and Ohio community pharmacies (n = 1,461). We likewise sought to explore the moderating role of gender in pain-substance use relations. We used patient-reported data from a cross-sectional health survey linked with controlled substance dispensing data from statewide prescription drug monitoring programs. Multivariable logistic regression estimated associations between pain severity and interference and various indices of risky prescription opioid use and non-opioid substance use. Exploratory analyses examined whether gender moderated associations. Increased pain severity was associated with increased odds of moderate- to high-risk opioid use (OR: 1.23; 95% CI: 1.16-1.31) and opioid-benzodiazepine co-use (OR: 1.20; 95% CI: 1.03-1.40). Increased pain interference was associated with greater odds of receiving opioids from multiple pharmacies or providers (OR: 1.15; 95% CI: 1.01-1.31). Increased pain severity and interference were associated with higher odds of any tobacco use (severity: OR: 1.13; 95% CI: 1.06-1.21; interference: OR: 1.07; 95% CI: 1.01-1.12) and weekly to daily sedative use (severity: OR: 1.13; 95% CI: 1.03-1.25; interference: OR: 1.13; 95% CI: 1.04-1.22). Increased pain severity was associated with decreased odds of any alcohol use (OR: 0.93; 95% CI: 0.88-0.99). Gender was a significant effect modifier in associations between pain and alcohol, tobacco, and cannabis use. The study was registered in the database of clinicaltrials.gov (register number NCT03936985). Perspective: This study suggests that pain severity and interference are associated with increased use of non-medical prescription opioids, sedatives, and tobacco and decreased use of alcohol, in ways that are different between women and men. Findings may guide the development of gender-sensitive evidence-based strategies to ameliorate or prevent substance misuse among patients living with pain.

Clinical documentation of patient-reported medical cannabis use in primary care: Toward scalable extraction using natural language processing methods.

Background: Most states have legalized medical cannabis, yet little is known about how medical cannabis use is documented in patients' electronic health records (EHRs). We used natural language processing (NLP) to calculate the prevalence of clinician-documented medical cannabis use among adults in an integrated health system in Washington State where medical and recreational use are legal. Methods: We analyzed EHRs of patients ≥18 years old screened for past-year cannabis use (November 1, 2017-October 31, 2018), to identify clinician-documented medical cannabis use. We defined medical use as any documentation of cannabis that was recommended by a clinician or described by the clinician or patient as intended to manage health conditions or symptoms. We developed and applied an NLP system that included NLP-assisted manual review to identify such documentation in encounter notes. Results: Medical cannabis use was documented for 16,684 (5.6%) of 299,597 outpatient encounters with routine screening for cannabis use among 203,489 patients seeing 1,274 clinicians. The validated NLP system identified 54% of documentation and NLP-assisted manual review the remainder. Language documenting reasons for cannabis use included 125 terms indicating medical use, 28 terms indicating non-medical use and 41 ambiguous terms. Implicit documentation of medical use (e.g., "edible THC nightly for lumbar pain") was more common than explicit (e.g., "continues medical cannabis use"). Conclusions: Clinicians use diverse and often ambiguous language to document patients' reasons for cannabis use. Automating extraction of documentation about patients' cannabis use could facilitate clinical decision support and epidemiological investigation but will require large amounts of gold standard training data.

Validation and threshold identification of a prescription drug monitoring program clinical opioid risk metric with the WHO alcohol, smoking, and substance involvement screening test.

BACKGROUND: Prescription drug monitoring programs (PDMPs) are critical for pharmacists to identify risky opioid medication use. We performed an independent evaluation of the PDMP-based Narcotic Score (NS) metric. METHODS: This study was a one-time, cross-sectional health assessment within 19 pharmacies from a national chain among adults picking-up opioid medications. The NS metric is a 3-digit composite indicator. The WHO Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) was the gold-standard to which the NS metric was compared. Machine learning determined optimal risk thresholds; Receiver Operating Characteristic curves and Spearman (P) and Kappa (K) coefficients analyzed concurrent validity. Regression analyses evaluated participant characteristics associated with misclassification. RESULTS: The NS metric showed fair concurrent validity (area under the curve≥0.70; K=0.35; P = 0.37, p < 0.001). The ASSIST and NS metric categorized 37% of participants as low-risk (i.e., not needing screening/intervention) and 32.3% as moderate/high-risk (i.e., needing screening/intervention). Further, 17.2% were categorized as low ASSIST risk but moderate/high NS metric risk, termed false positives. These reported disability (OR=3.12), poor general health (OR=0.66), and/or greater pain severity/interference (OR=1.12/1.09; all p < 0.05; i.e., needing unmanaged-pain screening/intervention). A total of 13.4% were categorized as moderate/high ASSIST risk but low NS metric risk, termed false negatives. These reported greater overdose history (OR=1.24) and/or substance use (OR=1.81-12.66; all p < 0.05). CONCLUSIONS: The NS metric could serve as a useful initial universal prescription opioid-risk screener given its: 1) low-burden (i.e., no direct assessment); 2) high accuracy (86.5%) of actionable data identifying low-risk patients and those needing opioid use/unmanaged pain screening/intervention; and 3) broad availability.

An Examination of the Feasibility of Detecting Cocaine Use Using Smartwatches.

As digital technology increasingly informs clinical trials, novel ways to collect study data in the natural field setting have the potential to enhance the richness of research data. Cocaine use in clinical trials is usually collected via self-report and/or urine drug screen results, both of which have limitations. This article examines the feasibility of developing a wrist-worn device that can detect sufficient physiological data (i.e., heart rate and heart rate variability) to detect cocaine use. This study aimed to develop a wrist-worn device that can be used in the natural field setting among people who use cocaine to collect reliable data (determined by data yield, device wearability, and data quality) that is less obtrusive than chest-based devices used in prior research. The study also aimed to further develop a cocaine use detection algorithm used in previous research with an electrocardiogram on a chestband by adapting it to a photoplethysmography sensor on the wrist-worn device which is more prone to motion artifacts. Results indicate that wrist-based heart rate data collection is feasible and can provide higher data yield than chest-based sensors, as wrist-based devices were also more comfortable and affected participants' daily lives less often than chest-based sensors. When properly worn, wrist-based sensors produced similar quality of heart rate and heart rate variability features to chest-based sensors and matched their performance in automated detection of cocaine use events. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02915341.

Prevalence of Medical Cannabis Use and Associated Health Conditions Documented in Electronic Health Records Among Primary Care Patients in Washington State.

Importance: Many people use cannabis for medical reasons despite limited evidence of therapeutic benefit and potential risks. Little is known about medical practitioners' documentation of medical cannabis use or clinical characteristics of patients with documented medical cannabis use. Objectives: To estimate the prevalence of past-year medical cannabis use documented in electronic health records (EHRs) and to describe patients with EHR-documented medical cannabis use, EHR-documented cannabis use without evidence of medical use (other cannabis use), and no EHR-documented cannabis use. Design, Setting, and Participants: This cross-sectional study assessed adult primary care patients who completed a cannabis screen during a visit between November 1, 2017, and October 31, 2018, at a large health system that conducts routine cannabis screening in a US state with legal medical and recreational cannabis use. Exposures: Three mutually exclusive categories of EHR-documented cannabis use (medical, other, and no use) based on practitioner documentation of medical cannabis use in the EHR and patient report of past-year cannabis use at screening. Main Outcomes and Measures: Health conditions for which cannabis use has potential benefits or risks were defined based on National Academies of Sciences, Engineering, and Medicine's review. The adjusted prevalence of conditions diagnosed in the prior year were estimated across 3 categories of EHR-documented cannabis use with logistic regression. Results: A total of 185 565 patients (mean [SD] age, 52.0 [18.1] years; 59% female, 73% White, 94% non-Hispanic, and 61% commercially insured) were screened for cannabis use in a primary care visit during the study period. Among these patients, 3551 (2%) had EHR-documented medical cannabis use, 36 599 (20%) had EHR-documented other cannabis use, and 145 415 (78%) had no documented cannabis use. Patients with medical cannabis use had a higher prevalence of health conditions for which cannabis has potential benefits (49.8%; 95% CI, 48.3%-51.3%) compared with patients with other cannabis use (39.9%; 95% CI, 39.4%-40.3%) or no cannabis use (40.0%; 95% CI, 39.8%-40.2%). In addition, patients with medical cannabis use had a higher prevalence of health conditions for which cannabis has potential risks (60.7%; 95% CI, 59.0%-62.3%) compared with patients with other cannabis use (50.5%; 95% CI, 50.0%-51.0%) or no cannabis use (42.7%; 95% CI, 42.4%-42.9%). Conclusions and Relevance: In this cross-sectional study, primary care patients with documented medical cannabis use had a high prevalence of health conditions for which cannabis use has potential benefits, yet a higher prevalence of conditions with potential risks from cannabis use. These findings suggest that practitioners should be prepared to discuss potential risks and benefits of cannabis use with patients.

Bupropion and Naltrexone in Methamphetamine Use Disorder.

BACKGROUND: The use of naltrexone plus bupropion to treat methamphetamine use disorder has not been well studied. METHODS: We conducted this multisite, double-blind, two-stage, placebo-controlled trial with the use of a sequential parallel comparison design to evaluate the efficacy and safety of extended-release injectable naltrexone (380 mg every 3 weeks) plus oral extended-release bupropion (450 mg per day) in adults with moderate or severe methamphetamine use disorder. In the first stage of the trial, participants were randomly assigned in a 0.26:0.74 ratio to receive naltrexone-bupropion or matching injectable and oral placebo for 6 weeks. Those in the placebo group who did not have a response in stage 1 underwent rerandomization in stage 2 and were assigned in a 1:1 ratio to receive naltrexone-bupropion or placebo for an additional 6 weeks. Urine samples were obtained from participants twice weekly. The primary outcome was a response, defined as at least three methamphetamine-negative urine samples out of four samples obtained at the end of stage 1 or stage 2, and the weighted average of the responses in the two stages is reported. The treatment effect was defined as the between-group difference in the overall weighted responses. RESULTS: A total of 403 participants were enrolled in stage 1, and 225 in stage 2. In the first stage, 18 of 109 participants (16.5%) in the naltrexone-bupropion group and 10 of 294 (3.4%) in the placebo group had a response. In the second stage, 13 of 114 (11.4%) in the naltrexone-bupropion group and 2 of 111 (1.8%) in the placebo group had a response. The weighted average response across the two stages was 13.6% with naltrexone-bupropion and 2.5% with placebo, for an overall treatment effect of 11.1 percentage points (Wald z-test statistic, 4.53; P<0.001). Adverse events with naltrexone-bupropion included gastrointestinal disorders, tremor, malaise, hyperhidrosis, and anorexia. Serious adverse events occurred in 8 of 223 participants (3.6%) who received naltrexone-bupropion during the trial. CONCLUSIONS: Among adults with methamphetamine use disorder, the response over a period of 12 weeks among participants who received extended-release injectable naltrexone plus oral extended-release bupropion was low but was higher than that among participants who received placebo. (Funded by the National Institute on Drug Abuse and others; ADAPT-2 ClinicalTrials.gov number, NCT03078075.).

Buprenorphine physician-pharmacist collaboration in the management of patients with opioid use disorder: results from a multisite study of the National Drug Abuse Treatment Clinical Trials Network.

BACKGROUND AND AIMS: Physician and pharmacist collaboration may help address the shortage of buprenorphine-waivered physicians and improve care for patients with opioid use disorder (OUD). This study investigated the feasibility and acceptability of a new collaborative care model involving buprenorphine-waivered physicians and community pharmacists. DESIGN: Nonrandomized, single-arm, open-label feasibility trial. SETTING: Three office-based buprenorphine treatment (OBBT) clinics and three community pharmacies in the United States. PARTICIPANTS: Six physicians, six pharmacists, and 71 patients aged ≥18 years with Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) OUD on buprenorphine maintenance. INTERVENTION: After screening, eligible patients' buprenorphine care was transferred from their OBBT physician to a community pharmacist for 6 months. MEASUREMENTS: Primary outcomes included recruitment, treatment retention and adherence, and opioid use. Secondary outcomes were intervention fidelity, pharmacists' use of prescription drug monitoring program (PDMP), participant safety, and satisfaction with treatment delivery. FINDINGS: A high proportion (93.4%, 71/76) of eligible participants enrolled into the study. There were high rates of treatment retention (88.7%) and adherence (95.3%) at the end of the study. The proportion of opioid-positive urine drug screens (UDSs) among complete cases (i.e. those with all six UDSs collected during 6 months) at month 6 was (4.9%, 3/61). Intervention fidelity was excellent. Pharmacists used PDMP at 96.8% of visits. There were no opioid-related safety events. Over 90% of patients endorsed that they were "very satisfied with their experience and the quality of treatment offered," that "treatment transfer from physician's office to the pharmacy was not difficult at all," and that "holding buprenorphine visits at the same place the medication is dispensed was very or extremely useful/convenient." Similarly, positive ratings of satisfaction were found among physicians/pharmacists. CONCLUSIONS: A collaborative care model for people with opioid use disorder that involves buprenorphine-waivered physicians and community pharmacists appears to be feasible to operate in the United States and have high acceptability to patients.

Towards detecting cocaine use using smartwatches in the NIDA clinical trials network: Design, rationale, and methodology.

Cocaine use in clinical trials is often measured via self-report, which can be inaccurate, or urine drug screens, which can be intrusive and burdensome. Devices that can automatically detect cocaine use and can be worn conveniently in daily life may provide several benefits. AutoSense is a wearable, physiological-monitoring suite that can detect cocaine use, but it may be limited as a method for monitoring cocaine use because it requires wearing a chestband with electrodes. This paper describes the design, rationale, and methodology of a project that seeks to build upon and extend previous work in the development of methods to detect cocaine use via wearable, unobtrusive mobile sensor technologies. To this end, a wrist-worn sensor suite (i.e., MotionSense HRV) will be developed and evaluated. Participants who use cocaine (N = 25) will be asked to wear MotionSense HRV and AutoSense for two weeks during waking hours. Drug use will be assessed via thrice-weekly urine drug screens and self-reports, and will be used to isolate periods of cocaine use that will be differentiated from other drug use. The present study will provide information on the feasibility and acceptability of using a wrist-worn device to detect cocaine use.

Multicomorbidity of chronic diseases and substance use disorders and their association with hospitalization: Results from electronic health records data.

BACKGROUND: Chronic diseases are prevalent and the leading causes of mortality. Comorbidity of substance use disorders (SUDs) and chronic diseases is understudied to inform behavioral healthcare integration. OBJECTIVES: This study leveraged electronic health record (EHR) data of 211,880 adults from a large health system to examine prevalence and correlates of comorbidity of SUDs and nine chronic disease groups and to determine their association with hospitalization. METHODS: Logistic regression analyses were conducted to estimate associations between chronic diseases and SUDs. To control for severity of diagnosis, analyses of associations between SUD and hospitalization were stratified by the number of chronic conditions. RESULTS: In the sample, 48.3% had ≥1 chronic condition (hypertension 33.7%, arthritis 16.2%, diabetes 13.7%, chronic kidney disease 9.9%, asthma 9.1%, chronic obstructive pulmonary disease 8.9%, ischemic heart disease 8.3%, cancer 4.6%, and hepatitis 1.3%). Prevalence of SUD (overall 13.3%) among patients increased with multiple chronic conditions (14.3% having SUD among patients with one condition; 21.2% having SUD among patients with two to three conditions; and 32.5% having SUD among patients with 4-9 conditions). Chronic conditions were associated with increased odds of SUDs. For all SUD groups, hospitalization was more prevalent among patients with SUD than those without it; prevalence of hospitalization increased with the number of comorbid chronic conditions. CONCLUSIONS: Findings reveal a striking pattern of multicomorbidity of SUD and chronic diseases and its positive association with hospitalization. Behavioral healthcare integration should consider efforts to assess and treat comorbid SUD and chronic diseases, especially among adults with multiple chronic conditions.

Tobacco use during cannabis cessation: Use patterns and impact on abstinence in a National Drug Abuse Treatment Clinical Trials Network study.

BACKGROUND: It is common for cannabis users to also use tobacco. While data suggest that tobacco users have more difficulty achieving cannabis cessation, secondary analyses of clinical trial data sets may provide insight into the moderating variables contributing to this relationship, as well as changes in tobacco use during cannabis treatment. Those were the aims of this secondary analysis. METHODS: The parent study was a multi-site trial of N-acetylcysteine for cannabis dependence conducted within the National Drug Abuse Treatment Clinical Trials Network. Participants were treatment-seeking adults (ages 18-50) who met criteria for cannabis dependence (N = 302). For cigarette smokers (n = 117), tobacco use was assessed via timeline follow-back and nicotine dependence was assessed via the Fagerström Test for Nicotine Dependence (FTND). Outcome measures included: 1) changes in tobacco use based on treatment assignment, nicotine dependence, and concurrent cannabis reduction/abstinence, and 2) independent associations between nicotine dependence and cannabis abstinence. RESULTS: Cigarette smokers accounted for 39% of the sample (117/302), with a median FTND score of 3.0 (10-point scale). Among those with lower baseline nicotine dependence scores, cigarette smoking was reduced in the active treatment group compared to placebo. Those with moderate/high levels of nicotine dependence showed slight increases in smoking following active treatment. Nicotine dependence did not affect cannabis cessation. CONCLUSIONS: Cigarette smoking during cannabis treatment was affected, but depended on baseline nicotine dependence severity, though dependence levels did not impact cannabis abstinence. Interventions that address both tobacco and cannabis are needed, especially due to an increasing prevalence of cannabis use.

Using ecological momentary assessment to examine the relationship between craving and affect with opioid use in a clinical trial of clonidine as an adjunct medication to buprenorphine treatment.

BACKGROUND: In a recent clinical trial (NCT00295308), we demonstrated that clonidine decreased the association between opioid craving and moderate levels of stress and affect in patients receiving buprenorphine-based opioid agonist therapy. OBJECTIVES: To examine the relationship between illicit opioid use and craving and affect during the evaluation of clonidine as an adjunct medication in buprenorphine treatment for opioid use disorder. Secondarily, to examine whether those relationships are driven by within- or between-participant factors. METHODS: This was a secondary data analysis from our original trial. Participants (N = 108, female: n = 23, male n = 85) receiving buprenorphine were randomized to receive adjunct clonidine or placebo. Participants used portable electronic devices to rate stress, mood, and craving via ecological momentary assessment (EMA) four times randomly each day. To associate the EMA data with illicit opioid use, each EMA report was linked to participants' next urine drug screen (thrice weekly). We used generalized linear mixed models to examine the interaction between treatment group and illicit opioid use, as well as to decompose the analysis into within- and between-participant effects. RESULTS: Craving for opioids and cocaine was increased when participants were using illicit opioids; this effect was greater in the clonidine group. For affect, mood was poorer during periods preceding opioid-positive urines than opioid-negative urines for clonidine-treated participants, whereas there was no difference for placebo participants. CONCLUSION: This secondary analysis provides evidence that for participants maintained on opioid agonist therapy, clonidine minimized the behavioral impact of moderate levels of negative affect and craving.

Substance use disorders and medical comorbidities among high-need, high-risk patients with diabetes.

BACKGROUND: The majority of the U.S. healthcare resources are utilized by a small population characterized as high-risk, high-need persons with complex care needs (e.g., adults with multiple chronic conditions). Substance use disorders (SUDs) and mental health disorders (MHDs) are a driver of poor health and additional healthcare costs, but they are understudied among high-need patients. OBJECTIVE: We examine the prevalence and correlates of SUDs and MHDs among adults with high-risk diabetes, who are patients at the top 10% risk score for developing poor outcomes (hospital admission or death). METHODS: A risk algorithm developed from Duke University Health System electronic health records (EHRs) data was used to identify patients with high-risk diabetes for targeting home-based primary care. The EHR data of the 263 patients with high-risk diabetes were analyzed to understand patterns of SUDs and MHDs to inform care-coordinating efforts. RESULTS: Both SUDs (any SUD 48.3%, alcohol 12.5%, tobacco 38.8%, drug 23.2%) and MHDs (any MHD 74.9%, mood 53.2%, sleep 37.3%, anxiety 32.7%, schizophrenia/psychotics/delusional 14.8%, dementia/delirium/amnestic/cognitive 14.4%, adjustment 9.1%) were prevalent. Overall, 81.7% of the sample had SUD or MHD. Elevated odds of SUD were noted among men (tobacco, alcohol) and those who were never-married (alcohol, cannabis). African-American race (vs. other race/ethnicity) was associated with lower odds of anxiety disorders. CONCLUSION: While data are limited to one large academic health system, they provide clinical evidence revealing that 82% of patients with high-risk diabetes had SUD and/or MHD recorded in their EHRs, highlighting a need for developing service models to optimize high-risk care.