Navigating new norms: Addiction specialists' perspectives on opioid use disorder treatments and policy challenges in the fentanyl era.

BACKGROUND AND OBJECTIVES: Amidst increasing opioid-related overdoses in the USA, opioid use disorder (OUD) treatment has seen few novel treatments emerge. High-potency synthetic opioids (HPSOs) have altered clinical approaches, prompting evaluation of existing medications for opioid use disorder (MOUD) and interest in slow-release oral morphine (SROM) as another therapeutic option. Here we survey addiction specialists on the influence of HPSOs on clinical practice, views on current MOUD regulations, and openness to novel therapies such as SROM. METHODS: Anonymous, online survey conducted at a national conference of addiction specialists (N = 91). Pearson χ2 tests and Fisher's exact tests to compare respondent characteristics. RESULTS: Approximately 89% of respondents (N = 91) acknowledge that HPSOs shifted addiction treatment in recent years, with 86% modifying their MOUD prescribing accordingly. Moreover, 84% report having patients who could benefit from other full opioid agonists beyond methadone for OUD management. Many report off-label prescribing of full agonist opioids other than methadone for withdrawal symptoms or initiating MOUD. Eighty percent reported being in favor of incorporating SROM as a third-line monotherapy for OUD. DISCUSSION AND CONCLUSION: This sample of addiction specialists supports innovative alternatives for MOUD in the USA to combat the challenges posed by fentanyl and related HPSOs. Future work should further addiction specialists' opinions on barriers to OUD treatment and exploration of these international strategies in the USA. SCIENTIFIC SIGNIFICANCE: This appears to be the first study exploring addiction specialists' perspectives on regulatory barriers to OUD treatment and their willingness to uptake internationally adopted strategies such as SROM.

Revisiting Preaddiction.

ABSTRACT: The directors of the National Institute on Drug Abuse and the National Institute on Alcohol Abuse and Alcoholism have proposed new efforts to enable earlier identification and intervention for harmful substance use and its consequences. As editors of The ASAM Principles of Addiction Medicine, we fully support this goal. The word "preaddiction" has been suggested as a diagnostic label to describe individuals who would be targeted for early intervention. In this commentary, we offer that "unhealthy substance use" would be a better descriptor than "preaddiction" and review several potential barriers to be addressed in order to maximize the impact of introducing this new paradigm.

Naltrexone augmented with prazosin for alcohol use disorder: results from a randomized controlled proof-of-concept trial.

AIMS: We conducted a proof-of-concept randomized controlled trial of the mu-opioid receptor antagonist, naltrexone, augmented with the alpha-1 adrenergic receptor antagonist, prazosin, for alcohol use disorder in veterans. We sought a signal that the naltrexone plus prazosin combination regimen would be superior to naltrexone alone. METHODS: Thirty-one actively drinking veterans with alcohol use disorder were randomized 1:1:1:1 to naltrexone plus prazosin (NAL-PRAZ [n = 8]), naltrexone plus placebo (NAL-PLAC [n = 7]), prazosin plus placebo (PRAZ-PLAC [n = 7]), or placebo plus placebo (PLAC-PLAC [n = 9]) for 6 weeks. Prazosin was titrated over 2 weeks to a target dose of 4 mg QAM, 4 mg QPM, and 8 mg QHS. Naltrexone was administered at 50 mg QD. Primary outcomes were the Penn Alcohol Craving Scale (PACS), % drinking days (PDD), and % heavy drinking days (PHDD). RESULTS: In the NAL-PRAZ condition, % reductions from baseline for all three primary outcome measures exceeded 50% and were at least twice as large as % reductions in the NAL-PLAC condition (PACS: 57% vs. 26%; PDD: 51% vs. 22%; PHDD: 69% vs. 15%) and in the other two comparator conditions. Standardized effect sizes between NAL-PRAZ and NAL-PLAC for each primary outcome measure were >0.8. All but one participant assigned to the two prazosin containing conditions achieved the target prazosin dose of 16 mg/day and maintained that dose for the duration of the trial. CONCLUSION: These results suggest that prazosin augmentation of naltrexone enhances naltrexone benefit for alcohol use disorder. These results strengthen rationale for an adequately powered definitive randomized controlled trial.

Collaborating to heal addiction and mental health in primary care (CHAMP): A protocol for a hybrid type 2a trial.

BACKGROUND: The gold-standard treatment for opioid use disorder (OUD) is medication for OUD (MOUD). However, less than a quarter of people with OUD initiate MOUD. Expanding the Collaborative Care Model (CoCM) to include primary care patients with OUD could improve access to and initiation of MOUD. This paper presents the methods and baseline sample characteristics of a Hybrid Type 2a trial comparing the effectiveness of CoCM for OUD and co-occurring mental health symptoms (MHS) to CoCM for MHS only. METHOD: 42 primary care clinics were cluster randomized and 254 primary care patients with OUD and elevated MHS were enrolled. Recruitment was terminated early by the Data and Safety Monitoring Board for futility. Participants completed research assessments at baseline, 3 months, and 6 months. The multiple primary outcomes were past-month number of days of nonmedical opioid use and SF12 Mental Health Component Summary (MCS) scores. RESULTS: MCS scores were over a standard deviation below the national mean (M = 34.5). Nearly half (47.6 %) of participants had previously overdosed in their lifetimes. Three quarters (76.0 %) were already being prescribed MOUD at baseline, only 30.4 % reported non-medical use of opioids, and only 33.9 % reported being bothered by opioid cravings. CONCLUSION: The unexpectedly high proportion of enrollees already prescribed MOUD at baseline indicates that most patients were in the maintenance rather than acute phase of treatment. Challenges identifying and enrolling patients in the acute phase of OUD treatment implies that intervention effectiveness will depend on its success preventing the discontinuation of MOUD rather than initiating MOUD.

Are we being equitable enough? Lessons learned from sites lost in an implementation trial.

Background: There is a growing interest in practice-based implementation research, yet too often research prioritizes and is most successful in academic settings. During a national implementation trial to evaluate the effectiveness of Collaborative Care for co-occurring opioid use and mental health disorders, we lost three of our 11 participating implementation sites, all representing community sites. Method: To better understand needed supports for implementation trial participation, we conducted exit interviews (n = 5) with key staff at these community sites. Interview transcripts were double-coded and analyzed using Rapid Assessment Process. Qualitative themes were iteratively reviewed by the study team. Results: Three themes emerged characterizing challenges for community sites, including that: (1) research threatens sites' most precious resource-staff; (2) staff lack comfort with and skills for research; and (3) research participation in its current form does not offer a clear return on investment. Conclusions: Learnings from this work illuminate some of the barriers community sites face when trying to participate in multisite implementation research. An undercurrent of participant perspectives was the belief that community sites like theirs are just not set up to successfully participate in clinical trial research, including population-based implementation trials. Future implementation trials should consider strategies that disrupt traditional approaches, increasing the equitable inclusion of diverse practice settings in implementation research.

There is a growing interest in research that reflects community settings. Yet too often, research is most successful in academic settings. During a national implementation trial to evaluate the effectiveness of Collaborative Care for co-occurring opioid use and mental health disorders, we lost three of our 11 participating implementation sites, all representing community sites. To better understand their perspectives, we conducted exit interviews (n = 5) with staff at these community sites. Interview transcripts were double-coded and analyzed using thematic analysis. Analysis identified three themes: (1) research threatens sites' most precious resource­staff; (2) staff lack comfort with and skills for research, and (3) research participation in its current form does not offer a clear return on investment. Community sites face many barriers to participating in implementation research trials. Future trials should consider ways to disrupt traditional approaches and increase the equitable inclusion of community settings in implementation research.

Primary care team perspectives on approaches to engaging patients in treatment for opioid use disorder.

INTRODUCTION: Engagement is a critical component of successful treatment for opioid use disorder (OUD). However, rates of patient engagement in OUD treatment, especially in outpatient settings, are variable and often low. Little is known about the specific strategies members of primary care teams use to initiate and encourage ongoing participation in OUD treatment. In a national cohort of primary care clinics in the U.S., we explored the perspectives of primary care team members on the meaning of and approaches to OUD treatment engagement. METHODS: We conducted semi-structured interviews with 35 providers from multidisciplinary primary care teams in an existing national cohort of 13 clinics across seven states. Teams were delivering OUD treatment via the Collaborative Care Model, a model that combines primary care providers (PCP), behavioral health care managers (BHCM) and consulting psychiatric providers (CPP) in a structured way to provide patient-centered, team-based, and measurement-based care. Interview participants included 14 PCPs, 13 BHCMs, and 8 CPPs. Interviews asked open-ended questions about provider experiences and practices that aided or hindered patient engagement in OUD treatment. Interview transcripts were double-coded by trained qualitative researchers and analyzed using a combination of deductive and inductive approaches to identify themes. RESULTS: Two themes emerged that describe provider perspectives on the meaning of engagement: 1) qualifying engagement by the volume of contact with patients, and 2) the need for more multidimensional measures of engagement. Six themes emerged that characterized provider engagement practices: 1) creating an environment of disclosure, 2) normalizing OUD treatment, 3) offering gentle but persistent outreach, 4) providing human connection and encouragement, 5) tailoring treatment to patient needs, and 6) avoiding stigmatizing responses. Analysis identified multiple replicable strategies that providers used to support these engagement practices. CONCLUSIONS: Providers consistently apply a range of strategies when trying to engage patients in OUD treatment. Specific engagement strategies used embodied compassion and pragmatism, hallmarks of patient-centered care. Further research is needed to understand the impact of scaling engagement approaches across all care settings.

Optimizing Patient Engagement in Treatment for Opioid Use Disorder: Primary Care Team Perspectives on Influencing Factors.

BACKGROUND: Opioid use disorder (OUD) care engagement rates in primary care (PC) settings are often low. Little is known about PC team experiences when delivering OUD treatment and potential factors that influence their capacity to engage patients in treatment. Exploring PC team experiences may inform needed supports that can optimize OUD care delivery and improve outcomes for patients with OUD. OBJECTIVE: We explored multidisciplinary PC team perspectives on barriers and facilitators to engaging patients in OUD treatment. DESIGN: Qualitative study using in-depth interviews. PARTICIPANTS: Primary care clinical teams. APPROACH: We conducted semi-structured interviews (n = 35) with PC team members involved in OUD care delivery, recruited using a combination of criterion and maximal variation sampling. Data collection and analysis were informed by existing theoretical literature about patient engagement, specifically that patient engagement is influenced by factors across individual (patient, provider), interpersonal (patient-provider), and health system domains. Interviews were professionally transcribed and doubled-coded using a coding schema based on the interview guide while allowing for emergent codes. Coding was iteratively reviewed using a constant comparison approach to identify themes and verified with participants and the full study team. KEY RESULTS: Analysis identified five themes that impact PC team ability to engage patients effectively, including limited patient contact (e.g., phone, text) in between visits, varying levels of provider confidence to navigate OUD treatment discussions, structural factors (e.g., schedules, productivity goals) that limited provider time, the role of team-based approaches in lessening discouragement and feelings of burnout, and lack of shared organizational vision for reducing harms from OUD. CONCLUSIONS: While the capacity of PC teams to engage patients in OUD care is influenced across multiple levels, some of the most promising opportunities may involve addressing system-level factors that limit PC team time and collaboration and promoting organizational alignment on goals for OUD treatment.

Offering nurse care management for opioid use disorder in primary care: Impact on emergency and hospital utilization in a cluster-randomized implementation trial.

BACKGROUND: Patients with opioid use disorder (OUD) have increased emergency and hospital utilization. The PROUD trial showed that implementation of office-based addiction treatment (OBAT) increased OUD medication treatment compared to usual care, but did not decrease acute care utilization in patients with OUD documented pre-randomization (clinicaltrials.gov/study/NCT03407638). This paper reports secondary emergency and hospital utilization outcomes in patients with documented OUD in the PROUD trial. METHODS: This cluster-randomized implementation trial was conducted in 12 clinics from 6 diverse health systems (March 2015-February 2020). Patients who visited trial clinics and had an OUD diagnosis within 3 years pre-randomization were included in primary analyses; secondary analyses added patients with OUD who were new to the clinic or with newly-documented OUD post-randomization. Outcomes included days of emergency care and hospital utilization over 2 years post-randomization. Explanatory outcomes included measures of OUD treatment. Patient-level analyses used mixed-effect regression with clinic-specific random intercepts. RESULTS: Among 1988 patients with documented OUD seen pre-randomization (mean age 49, 53 % female), days of emergency care or hospitalization did not differ between intervention and usual care; OUD treatment also did not differ. In secondary analyses among 1347 patients with OUD post-randomization, there remained no difference in emergency or hospital utilization despite intervention patients receiving 32.2 (95 % CI 4.7, 59.7) more days of OUD treatment relative to usual care. CONCLUSIONS: Implementation of OBAT did not reduce emergency or hospital utilization among patients with OUD, even in the sample with OUD first documented post-randomization in whom the intervention increased treatment.

Medication-based treatment among rural, primary care patients diagnosed with opioid use disorder and alcohol use disorder.

INTRODUCTION: Opioid and alcohol use disorders are increasingly being addressed in primary care, yet how medications to treat these disorders are prescribed in rural regions is unknown. METHODS: We determined prevalence, types, and duration of medication prescription for opioid and/or alcohol use disorder among adult patients in rural primary clinics. The sample included 1874 adult patients who visited one of six rural primary care sites in the Northeastern and Northwestern United States at least once from October 2019 to January 2021 and had a diagnosis code for opioid use disorder (OUD), alcohol use disorder (AUD), or co-occurring opioid and alcohol use disorder (OUD + AUD) during that time. RESULTS: Patients with OUD + AUD were more likely to be prescribed medication for at least one of these disorders (85.3 %) than patients with OUD only (63.7 %) or AUD only (10.3 %). Further, the OUD + AUD group had the highest number of days on medication (M = 264.7), followed by OUD only (M = 220.5), then the AUD only group (M = 62.5). Only 8.8 % of patients with OUD + AUD were prescribed naltrexone or medication for OUD + AUD to treat both substance use disorders. CONCLUSIONS: Medications for treating AUD as well as OUD are available, but few patients with OUD + AUD and even fewer with AUD received pharmacological treatment for AUD. The current work highlights the need for rural clinicians to consider medications for AUD as an important treatment method for patients with AUD only or OUD + AUD.

Tools to implement measurement-based care (MBC) in the treatment of opioid use disorder (OUD): toward a consensus.

BACKGROUND: The prevalence and associated overdose death rates from opioid use disorder (OUD) have dramatically increased in the last decade. Despite more available treatments than 20 years ago, treatment access and high discontinuation rates are challenges, as are personalized medication dosing and making timely treatment changes when treatments fail. In other fields such as depression, brief measures to address these tasks combined with an action plan-so-called measurement-based care (MBC)-have been associated with better outcomes. This workgroup aimed to determine whether brief measures can be identified for using MBC for optimizing dosing or informing treatment decisions in OUD. METHODS: The National Institute on Drug Abuse Center for the Clinical Trials Network (NIDA CCTN) in 2022 convened a small workgroup to develop consensus about clinically usable measures to improve the quality of treatment delivery with MBC methods for OUD. Two clinical tasks were addressed: (1) to identify the optimal dose of medications for OUD for each patient and (2) to estimate the effectiveness of a treatment for a particular patient once implemented, in a more granular fashion than the binary categories of early or sustained remission or no remission found in The Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5). DISCUSSION: Five parameters were recommended to personalize medication dose adjustment: withdrawal symptoms, opioid use, magnitude (severity and duration) of the subjective effects when opioids are used, craving, and side effects. A brief rating of each OUD-specific parameter to adjust dosing and a global assessment or verbal question for side-effects was viewed as sufficient. Whether these ratings produce better outcomes (e.g., treatment engagement and retention) in practice deserves study. There was consensus that core signs and symptoms of OUD based on some of the 5 DSM-5 domains (e.g., craving, withdrawal) should be the basis for assessing treatment outcome. No existing brief measure was found to meet all the consensus recommendations. Next steps would be to select, adapt or develop de novo items/brief scales to inform clinical decision-making about dose and treatment effectiveness. Psychometric testing, assessment of acceptability and whether the use of such scales produces better symptom control, quality of life (QoL), daily function or better prognosis as compared to treatment as usual deserves investigation.

Internal Medicine Resident Addiction Training at the Veteran's Health Administration: A Qualitative Evaluation of Site Directors' Response to the 2022 ACGME Requirements.

BACKGROUND: Substance use disorders (SUDs) are prevalent in the USA yet remain dramatically undertreated. To address this care gap, the Accreditation Council for Graduate Medical Education (ACGME) approved revisions to the Program Requirements for Graduate Medical Education (GME) in Internal Medicine, effective July 1, 2022, requiring addiction medicine training for all internal medicine (IM) residents. The Veterans Health Administration (VHA) is a clinical training site for many academic institutions that sponsor IM residencies. This focus group project evaluated VHA IM residency site directors' perspectives about providing addiction medical education within VHA IM training sites. OBJECTIVE: To better understand the current state, barriers to, and facilitators of IM resident addiction medicine training at VHA sites. DESIGN: This was a qualitative evaluation based on semi-structured video-based focus groups. PARTICIPANTS: Participants were VHA IM site directors based at a VHA hospital or clinic throughout the USA. APPROACH: Focus groups were conducted using a semi-structured group interview guide. Two investigators coded each focus group independently, then met to create a final adjudicated coding scheme. Thematic analysis was used to identify key themes. KEY RESULTS: Forty-three participants from 38 VHA sites participated in four focus groups (average size: 11 participants). Six themes were identified within four pre-defined categories. Current state of training: most VHA sites offered no formal training in addiction medicine for IM residents. Barriers: addiction experts are often located outside of IM settings, and ACGME requirements were non-specific. Facilitators: clinical champions help support addiction training. Desired next steps: participants desired incentives to train or hire local champions and a pre-packaged didactic curriculum. CONCLUSIONS: Developing competent clinical champions and leveraging VHA addiction specialists from non-IM settings would create more addiction training opportunities for IM trainees at VHA sites. These insights can likely be applied to IM training at non-VHA sites.

"The Only Reason I Am Willing to Do It at All": Evaluation of VA's SUpporting Primary care Providers in Opioid Risk reduction and Treatment (SUPPORT) Center.

OBJECTIVES: Medication treatment for opioid use disorder (MOUD) is effective and recommended for outpatient settings. We implemented and evaluated the SUpporting Primary care Providers in Opioid Risk reduction and Treatment (SUPPORT) Center-a quality improvement partnership to implement stepped care for MOUD in 2 Veterans Health Administration (VA) primary care (PC) clinics. METHODS: SUPPORT provided a dedicated clinical team (nurse practitioner prescriber and social worker) and stepped care ([1] identification, assessment, referral; [2] MOUD induction; [3] stabilization; and [4] maintenance supporting PC providers [PCPs] to initiate and/or sustain treatment) coupled with ongoing internal facilitation (consultation, trainings, informatics support). Qualitative interviews with stakeholders (PCPs and patients) and meeting notes identified barriers and facilitators to implementation. Electronic health record and patient tracking data measured reach, adoption, and implementation outcomes descriptively. RESULTS: SUPPORT's implementation barriers included the need for an X-waiver, VA's opioid tapering policies, patient and PCP knowledge gaps and PCP discomfort, and logistical compatibility and sustainability challenges for clinics. SUPPORT's dedicated clinical staff, ongoing internal facilitation, and high patient and PCP satisfaction were key facilitators. SUPPORT (January 2019 to September 2021) trained 218 providers; 63 received X-waivers, and 23 provided MOUD (10.5% of those trained). SUPPORT provided care to 167 patients, initiated MOUD for 33, and provided education and naloxone to 72 (all = 0 in year before launch). CONCLUSIONS: SUPPORT reached many PCPs and patients and resulted in small increases in MOUD prescribing and high levels of stakeholder satisfaction. Dedicated clinical staff was key to observed successes. Although resource-intensive, SUPPORT offers a potential model for outpatient MOUD provision.

Buprenorphine Receipt and Retention for Opioid Use Disorder Following an Initiative to Increase Access in Primary Care.

OBJECTIVES: Buprenorphine, a medication for opioid use disorder (OUD), is underutilized in general medical settings. Further, it is inequitably received by racialized groups and persons with comorbidities. The Veterans Health Administration launched an initiative to increase buprenorphine receipt in primary care. The project's objective was to identify patient-related factors associated with buprenorphine receipt and retention in primary care clinics (n = 18) participating in the initiative. METHODS: Retrospective cohort quality improvement evaluation of patients 18 years or older with 2 or more primary care visits in a 1-year period and an OUD diagnosis in the year before the first primary care visit (index date). Buprenorphine receipt was the proportion of patients with OUD who received 1 or more buprenorphine prescriptions from primary care providers during the post-index year and retention the proportion who received buprenorphine for 180 days or longer. RESULTS: Of 2880 patients with OUD seen in primary care, 11.7% (95% confidence interval [CI], 10.6%-12.9%) received buprenorphine in primary care, 58.2% (95% CI, 52.8%-63.3%) of whom were retained on buprenorphine for 180 days or longer. Patients with alcohol use disorder (adjusted odds ratio [AOR], 0.39; 95% CI, 0.27-0.57), nonopioid drug use disorder (AOR, 0.64; 95% CI, 0.45-0.93), and serious mental illness (AOR, 0.60; 95% CI, 0.37-0.97) had lower buprenorphine receipt. Those with an anxiety disorder had higher buprenorphine receipt (AOR, 1.42; 95% CI, 1.04-1.95). Buprenorphine receipt (AOR, 0.55; 95% CI, 0.35-0.87) and 180-day retention (AOR, 0.40; 95% CI, 0.19-0.84) were less likely among non-Hispanic Black patients. CONCLUSIONS: Further integration of addiction services in primary care may be needed to enhance buprenorphine receipt for patients with comorbid substance use disorders, and interventions are needed to address disparities in receipt and retention among non-Hispanic Black patients.

Medication treatment for opioid use disorder among rural primary care patients.

PURPOSE: To investigate the prevalence of opioid use disorder (OUD) and medication treatment for OUD (MOUD) receipt in rural primary care settings and identify characteristics associated with MOUD among patients with OUD. METHODS: Secondary analyses based on electronic health records of all adult patients who visited 1 of the 6 rural primary care clinic sites from October 2019 to January 2021. Mixed effects logistic regression was conducted to assess MOUD receipt (Y/N) in relation to patient characteristics (eg, demographics, other substance use disorders [SUDs], mental health disorders, and chronic pain) and the number of MOUD prescribers per clinic. FINDINGS: The prevalence of OUD varied from 0.7% to 8.2% (Mean [SD] = 3.3% [95% CI: 0.4, 6.1]) among 36,762 primary care patients across 6 clinic sites. Among 1,164 patients with OUD, on average 50.1% received MOUD (95% CI: 28.0, 72.3). Patients in clinics with more than 3 MOUD prescribers had more than 3 times the odds of receiving MOUD (OR = 3.42; 95% CI, 1.22-9.62) as those in clinics with fewer than 3 prescribers. MOUD was positively associated with younger age (18-30 [OR = 6.97; 95% CI, 3.37-14.42], 31-64 [OR = 5.03; 95% CI, 2.64-9.57], relative to those 65 and older), having other co-occurring SUDs (OR = 3.77; 95% CI, 2.57-5.52), being male (OR = 1.50; 95% CI, 1.12-2.01), and negatively associated with having chronic pain disorders (OR = 0.69; 95% CI, 0.50-0.94). CONCLUSIONS: The prevalence of OUD and MOUD are high but vary considerably across rural primary care clinics; primary care MOUD prescribers play a key role on MOUD access in rural settings.

Individual-Level Risk Prediction of Return to Use During Opioid Use Disorder Treatment.

Importance: No existing model allows clinicians to predict whether patients might return to opioid use in the early stages of treatment for opioid use disorder. Objective: To develop an individual-level prediction tool for risk of return to use in opioid use disorder. Design, Setting, and Participants: This decision analytical model used predictive modeling with individual-level data harmonized in June 1, 2019, to October 1, 2022, from 3 multicenter, pragmatic, randomized clinical trials of at least 12 weeks' duration within the National Institute on Drug Abuse Clinical Trials Network (CTN) performed between 2006 and 2016. The clinical trials covered a variety of treatment settings, including federally licensed treatment sites, physician practices, and inpatient treatment facilities. All 3 trials enrolled adult participants older than 18 years, with broad pragmatic inclusion and few exclusion criteria except for major medical and unstable psychiatric comorbidities. Intervention: All participants received 1 of 3 medications for opioid use disorder: methadone, buprenorphine, or extended-release naltrexone. Main Outcomes and Measures: Predictive models were developed for return to use, which was defined as 4 consecutive weeks of urine drug screen (UDS) results either missing or positive for nonprescribed opioids by week 12 of treatment. Results: The overall sample included 2199 trial participants (mean [SD] age, 35.3 [10.7] years; 728 women [33.1%] and 1471 men [66.9%]). The final model based on 4 predictors at treatment entry (heroin use days, morphine- and cocaine-positive UDS results, and heroin injection in the past 30 days) yielded an area under the receiver operating characteristic curve (AUROC) of 0.67 (95% CI, 0.62-0.71). Adding UDS in the first 3 treatment weeks improved model performance (AUROC, 0.82; 95% CI, 0.78-0.85). A simplified score (CTN-0094 OUD Return-to-Use Risk Score) provided good clinical risk stratification wherein patients with weekly opioid-negative UDS results in the 3 weeks after treatment initiation had a 13% risk of return to use compared with 85% for those with 3 weeks of opioid-positive or missing UDS results (AUROC, 0.80; 95% CI, 0.76-0.84). Conclusions and Relevance: The prediction model described in this study may be a universal risk measure for return to opioid use by treatment week 3. Interventions to prevent return to regular use should focus on this critical early treatment period.

Identifying patients with opioid use disorder using International Classification of Diseases (ICD) codes: Challenges and opportunities.

BACKGROUND AND AIMS: International Classification of Diseases (ICD) diagnosis codes are often used in research to identify patients with opioid use disorder (OUD), but their accuracy for this purpose is not fully evaluated. This study describes application of ICD-10 diagnosis codes for opioid use, dependence and abuse from an electronic health record (EHR) data extraction using data from the clinics' OUD patient registries and clinician/staff EHR entries. DESIGN: Cross-sectional observational study. SETTING: Four rural primary care clinics in Washington and Idaho, USA. PARTICIPANTS: 307 patients. MEASUREMENTS: This study used three data sources from each clinic: (1) a limited dataset extracted from the EHR, (2) a clinic-based registry of patients with OUD and (3) the clinician/staff interface of the EHR (e.g. progress notes, problem list). Data source one included records with six commonly applied ICD-10 codes for opioid use, dependence and abuse: F11.10 (opioid abuse, uncomplicated), F11.20 (opioid dependence, uncomplicated), F11.21 (opioid dependence, in remission), F11.23 (opioid dependence with withdrawal), F11.90 (opioid use, unspecified, uncomplicated) and F11.99 (opioid use, unspecified with unspecified opioid-induced disorder). Care coordinators used data sources two and three to categorize each patient identified in data source one: (1) confirmed OUD diagnosis, (2) may have OUD but no confirmed OUD diagnosis, (3) chronic pain with no evidence of OUD and (4) no evidence for OUD or chronic pain. FINDINGS: F11.10, F11.21 and F11.99 were applied most frequently to patients who had clinical diagnoses of OUD (64%, 89% and 79%, respectively). F11.20, F11.23 and F11.90 were applied to patients who had a diagnostic mix of OUD and chronic pain without OUD. The four clinics applied codes inconsistently. CONCLUSIONS: Lack of uniform application of ICD diagnosis codes make it challenging to use diagnosis code data from EHR to identify a research population of persons with opioid use disorder.

Trends in Prevalence of Cannabis Use Disorder Among U.S. Veterans With and Without Psychiatric Disorders Between 2005 and 2019.

OBJECTIVE: Cannabis use disorder diagnoses are increasing among U.S. adults and are more prevalent among people with comorbid psychiatric disorders. Recent changes in cannabis laws, increasing cannabis availability, and higher-potency cannabis may have placed people with cannabis use and psychiatric disorders at disproportionately increasing risk for cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine whether trends in cannabis use disorder prevalence among VHA patients differ by whether they have psychiatric disorders. METHODS: VHA electronic health records from 2005 to 2019 (N range, 4,332,165-5,657,277) were used to identify overall and age-group-specific (<35, 35-64, and ≥65 years) trends in prevalence of cannabis use disorder diagnoses among patients with depressive, anxiety, posttraumatic stress, bipolar, or psychotic spectrum disorders and to compare these to corresponding trends among patients without any of these disorders. Given transitions in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM). RESULTS: Greater increases in prevalence of cannabis use disorder diagnoses were observed among patients with psychiatric disorders compared to those without (difference in prevalence change, 2005-2014: 1.91%, 95% CI=1.87-1.96; 2016-2019: 0.34%, 95% CI=0.29-0.38). Disproportionate increases in cannabis use disorder prevalence among patients with psychiatric disorders were greatest among those under age 35 between 2005 and 2014, and among those age 65 or older between 2016 and 2019. Among patients with psychiatric disorders, the greatest increases in cannabis use disorder prevalences were observed among those with bipolar and psychotic spectrum disorders. CONCLUSIONS: The findings highlight disproportionately increasing disparities in risk of cannabis use disorder among VHA patients with common psychiatric disorders. Greater public health and clinical efforts are needed to monitor, prevent, and treat cannabis use disorder in this population.

Stakeholder perspectives on a telemedicine referral and coordination model to expand medication treatment for opioid use disorder in rural primary care clinics.

INTRODUCTION: Opioid overdose deaths are increasing rapidly in the United States. Medications for opioid use disorder (MOUD) are effective and can be delivered in primary care, but uptake has been limited in rural communities. Referral to and coordination with an external telemedicine (TM) vendor by rural primary care clinics for MOUD (TM-MOUD) may increase MOUD access for rural patients, but we know little about perspectives on this model among key stakeholders. As part of a TM-MOUD feasibility study, we explored TM-MOUD acceptability and feasibility among personnel and patients from seven rural primary care clinics and a TM-MOUD vendor. METHODS: We conducted virtual interviews or focus groups with clinic administrators (n = 7 interviews), clinic primary care and behavioral health providers (8 groups, n = 30), other clinic staff (9 groups, n = 37), patients receiving MOUD (n = 16 interviews), TM-MOUD vendor staff (n = 4 interviews), and vendor-affiliated behavioral health and prescribing providers (n = 17 interviews). We asked about experiences with and acceptability of MOUD (primarily buprenorphine) and telemedicine (TM) and a TM-MOUD referral and coordination model. We conducted content analysis to identify themes and participants quantitatively rated acceptability of TM-MOUD elements on a 4-item scale. RESULTS: Perceived benefits of vendor-based TM-MOUD included reduced logistical barriers, more privacy and less stigma, and access to services not available locally (e.g., counseling, pain management). Barriers included lack of internet or poor connectivity in patients' homes, limited communication and trust between TM-MOUD and clinic providers, and questions about the value to the clinic of TM-MOUD referral to external vendor. Acceptability ratings for TM-MOUD were generally high; they were lowest among frontline staff. CONCLUSIONS: Rural primary care clinic personnel, TM-MOUD vendor personnel, and patients generally perceived referral from primary care to a TM-MOUD vendor to hold potential for increasing access to MOUD in rural communities. Increasing TM-MOUD uptake requires buy-in and understanding among staff of the TM-MOUD workflow, TM services offered, requirements for patients, advantages over clinic-based or TM services from clinic providers, and identification of appropriate patients. Poverty, along with patient hesitation to initiate treatment, creates substantial barriers to MOUD treatment generally; insufficient internet availability creates a substantial barrier to TM-MOUD.

Co-occurring substance use disorders among patients with opioid use disorder in rural primary care clinics.

BACKGROUND: Co-occurring substance use disorders (SUDs) among individuals with opioid use disorder (OUD) are associated with additional impairment, overdose, and death. This study examined characteristics of patients who have OUD with and without co-occurring SUDs in rural primary care clinics. METHODS: Secondary analysis used electronic health record (EHR) data from six rural primary care clinics, including demographics, diagnoses, encounters, and prescriptions of medication for OUD (MOUD), as well as EHR data from an external telemedicine vendor that provided MOUD to some clinic patients. The study population included all adult patients who had a visit to the participating clinics from October 2019 to January 2021. RESULTS: We identified 1164 patients with OUD; 72.6 % had OUD only, 11.5 % had OUD and stimulant use disorder (OUD + StUD), and 15.9 % had OUD and other non-stimulant substance use disorder (OUD + Other). The OUD + StUD group had the highest rates of hepatitis C virus (25.4 % for OUD + StUD, 17.8 % for OUD + Other, and 7.5 % for OUD Only; p < 0.001) and the highest rates of mental health disorders (78.4 %, 69.7 %, and 59.9 %, respectively; p < 0.001). Compared to the OUD Only group, patients in the OUD + StUD and OUD + Other groups were more likely to receive telehealth services provided by clinic staff, in-clinic behavioral health services, and in-clinic MOUD. The OUD + StUD group had the highest proportion of referrals to the external telemedicine vendor. CONCLUSIONS: More than 27 % of patients with OUD in rural primary care clinics had other co-occurring SUDs, and these patients received more healthcare services than those with OUD only. Future studies should examine variations in outcomes associated with these other services among patients with OUD and co-occurring SUDs.