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.

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.

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.

"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.

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.

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.

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.

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.

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.

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.

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.

Mental and Physical Health Conditions Among U.S. Veterans with Cannabis Use and Cannabis Use Disorders.

Purpose of Review: Veterans are a large population that is disproportionately affected by various physical and mental health conditions. The primary aim of this review is to provide a concise overview of recent literature on the prevalence of cannabis use and cannabis use disorder (CUD) among US Veterans, and associations with mental and physical health conditions. We also addressed gaps in the literature by investigating associations between CUD and mental and physical health conditions in 2019 data from the Veterans Health Administration (VHA; N=5,657,277). Recent Findings: In total, 25 studies were reviewed. In 2019, the prevalence of Veteran cannabis use ranged from 11.9%-18.7%. Cannabis use and CUD were associated with bipolar disorders, psychotic disorders, suicidality, pain conditions, and other substance use, but less consistently associated with depressive disorders, anxiety disorders, and posttraumatic stress disorder. Analyses of 2019 VHA data indicated that CUD was strongly associated with a broad array of physical and mental health conditions and mortality. Summary: Cannabis use and CUD are prevalent and highly comorbid with other conditions among US Veterans. Harm reduction methods tailored to these populations are needed.

Association of Cannabis Legalization with Cannabis Positive Drug Screening in US Veterans.

Background: Although cannabis legalization is associated with increases in self-report cannabis use, biological measures of cannabis use are needed to address potential bias introduced by improved self-reporting of cannabis use in states enacting medical cannabis laws (MCL) and recreational cannabis laws (RCL). Objective: Quantify the role of MCL and RCL enactment in cannabis positive urine drug screen (UDS) prevalence among Veterans Health Administration (VHA) emergency department (ED) patients from 2008 to 2019. Design: Staggered-adoption difference-in-difference analysis were used to estimate the role of MCL and RCL in cannabis positive UDS data, fitting adjusted linear binomial regression models to estimate the association between MCL and RCL enactment and prevalence of cannabis positive UDS. Participants: VHA enrolled veterans aged 18-75 years with ≥1 ED visit in a given year from 2008 to 2019. Main Measures: Receipt of ≥1 cannabis positive UDS during an ED visit were analyzed. Key Results: From 2008 to 2019, adjusted cannabis positive UDS prevalences increased from 16.4% to 25.6% in states with no cannabis law, 16.6% to 27.6% in MCL-only enacting states, and 18.2% to 33.8% in RCL-enacting states. MCL-only and MCL/RCL enactment was associated with a 0.8% (95% CI, 0.4-1.0) and 2.9% (95% CI, 2.5-3.3) absolute increase in cannabis positive UDS, respectively. Significant effect sizes were found for MCL and RCL, such that 7.0% and 18.5% of the total increase in cannabis positive UDS prevalence in MCL-only and RCL states could be attributed to MCLs and RCLs. Conclusions: In this study of VHA ED patients, MCL and RCL enactment played a significant role in the overall increases in cannabis positive UDS. The increase in a biological measure of cannabis use reduces concerns that previously documented increases in self-reported cannabis use from surveys are due to changes in patient willingness to report use as it becomes more legal.

Trends in Cannabis-positive Urine Toxicology Test Results: US Veterans Health Administration Emergency Department Patients, 2008 to 2019.

OBJECTIVES: This study aimed to examine trends in cannabis-positive urine drug screens (UDSs) among emergency department (ED) patients from 2008 to 2019 using data from the Veterans Health Administration (VHA) health care system, and whether these trends differed by age group (18-34, 35-64, and 65-75 years), sex, and race, and ethnicity. METHOD: VHA electronic health records from 2008 to 2019 were used to identify the percentage of unique VHA patients seen each year at an ED, received a UDS, and screened positive for cannabis. Trends in cannabis-positive UDS were examined by age, race and ethnicity, and sex within age groups. RESULTS: Of the VHA ED patients with a UDS, the annual prevalence positive for cannabis increased from 16.42% in 2008 to 27.2% in 2019. The largest increases in cannabis-positive UDS were observed in the younger age groups. Male and female ED patients tested positive for cannabis at similar levels. Although the prevalence of cannabis-positive UDS was consistently highest among non-Hispanic Black patients, cannabis-positive UDS increased in all race and ethnicity groups. DISCUSSION: The increasing prevalence of cannabis-positive UDS supports the validity of previously observed population-level increases in cannabis use and cannabis use disorder from survey and administrative records. Time trends via UDS results provide additional support that previously documented increases in self-reported cannabis use and disorder from surveys and claims data are not spuriously due to changes in patient willingness to report use as it becomes more legalized, or due to greater clinical attention over time.

Nurse Care Management for Opioid Use Disorder Treatment: The PROUD Cluster Randomized Clinical Trial.

Importance: Few primary care (PC) practices treat patients with medications for opioid use disorder (OUD) despite availability of effective treatments. Objective: To assess whether implementation of the Massachusetts model of nurse care management for OUD in PC increases OUD treatment with buprenorphine or extended-release injectable naltrexone and secondarily decreases acute care utilization. Design, Setting, and Participants: The Primary Care Opioid Use Disorders Treatment (PROUD) trial was a mixed-methods, implementation-effectiveness cluster randomized clinical trial conducted in 6 diverse health systems across 5 US states (New York, Florida, Michigan, Texas, and Washington). Two PC clinics in each system were randomized to intervention or usual care (UC) stratified by system (5 systems were notified on February 28, 2018, and 1 system with delayed data use agreement on August 31, 2018). Data were obtained from electronic health records and insurance claims. An implementation monitoring team collected qualitative data. Primary care patients were included if they were 16 to 90 years old and visited a participating clinic from up to 3 years before a system's randomization date through 2 years after. Intervention: The PROUD intervention included 3 components: (1) salary for a full-time OUD nurse care manager; (2) training and technical assistance for nurse care managers; and (3) 3 or more PC clinicians agreeing to prescribe buprenorphine. Main Outcomes and Measures: The primary outcome was a clinic-level measure of patient-years of OUD treatment (buprenorphine or extended-release injectable naltrexone) per 10 000 PC patients during the 2 years postrandomization (follow-up). The secondary outcome, among patients with OUD prerandomization, was a patient-level measure of the number of days of acute care utilization during follow-up. Results: During the baseline period, a total of 130 623 patients were seen in intervention clinics (mean [SD] age, 48.6 [17.7] years; 59.7% female), and 159 459 patients were seen in UC clinics (mean [SD] age, 47.2 [17.5] years; 63.0% female). Intervention clinics provided 8.2 (95% CI, 5.4-∞) more patient-years of OUD treatment per 10 000 PC patients compared with UC clinics (P = .002). Most of the benefit accrued in 2 health systems and in patients new to clinics (5.8 [95% CI, 1.3-∞] more patient-years) or newly treated for OUD postrandomization (8.3 [95% CI, 4.3-∞] more patient-years). Qualitative data indicated that keys to successful implementation included broad commitment to treat OUD in PC from system leaders and PC teams, full financial coverage for OUD treatment, and straightforward pathways for patients to access nurse care managers. Acute care utilization did not differ between intervention and UC clinics (relative rate, 1.16; 95% CI, 0.47-2.92; P = .70). Conclusions and Relevance: The PROUD cluster randomized clinical trial intervention meaningfully increased PC OUD treatment, albeit unevenly across health systems; however, it did not decrease acute care utilization among patients with OUD. Trial Registration: ClinicalTrials.gov Identifier: NCT03407638.

Chronic pain, cannabis legalisation, and cannabis use disorder among patients in the US Veterans Health Administration system, 2005 to 2019: a repeated, cross-sectional study.

BACKGROUND: Cannabis use disorder is associated with considerable comorbidity and impairment in functioning, and prevalence is increasing among adults with chronic pain. We aimed to assess the effect of introduction of medical cannabis laws (MCL) and recreational cannabis laws (RCL) on the increase in cannabis use disorder among patients in the US Veterans Health Administration (VHA). METHODS: Data from patients with one or more primary care, emergency, or mental health visit to the VHA in 2005-19 were analysed using 15 repeated cross-sectional VHA electronic health record datasets (ie, one dataset per year). Patients in hospice or palliative care were excluded. Patients were stratified as having chronic pain or not using an American Pain Society taxonomy of painful medical conditions. We used staggered-adoption difference-in-difference analyses to estimate the role of MCL and RCL enactment in the increases in prevalence of diagnosed cannabis use disorder and associations with presence of chronic pain, accounting for the year that state laws were enacted. We did this by fitting a linear binomial regression model stratified by pain, with time-varying cannabis law status, fixed effects for state, categorical year, time-varying state-level sociodemographic covariates, and patient covariates (age group [18-34 years, 35-64 years, and 65-75 years], sex, and race and ethnicity). FINDINGS: Between 2005 and 2019, 3 234 382-4 579 994 patients were included per year. Among patients without pain in 2005, 5·1% were female, mean age was 58·3 (SD 12·6) years, and 75·7%, 15·6%, and 3·6% were White, Black, and Hispanic or Latino, respectively. In 2019, 9·3% were female, mean age was 56·7 (SD 15·2) years, and 68·1%, 18·2%, and 6·5% were White, Black, and Hispanic or Latino, respectively. Among patients with pain in 2005, 7·1% were female, mean age was 57·2 (SD 11·4) years, and 74·0%, 17·8%, and 3·9% were White, Black, and Hispanic or Latino, respectively. In 2019, 12·4% were female, mean age was 57·2 (SD 13·8) years, and 65·3%, 21·9%, and 7·0% were White, Black, and Hispanic or Latino, respectively. Among patients with chronic pain, enacting MCL led to a 0·135% (95% CI 0·118-0·153) absolute increase in cannabis use disorder prevalence, with 8·4% of the total increase in MCL-enacting states attributable to MCL. Enacting RCL led to a 0·188% (0·160-0·217) absolute increase in cannabis use disorder prevalence, with 11·5% of the total increase in RCL-enacting states attributable to RCL. In patients without chronic pain, enacting MCL and RCL led to smaller absolute increases in cannabis use disorder prevalence (MCL: 0·037% [0·027-0·048], 5·7% attributable to MCL; RCL: 0·042% [0·023-0·060], 6·0% attributable to RCL). Overall, associations of MCL and RCL with cannabis use disorder were greater in patients with chronic pain than in patients without chronic pain. INTERPRETATION: Increasing cannabis use disorder prevalence among patients with chronic pain following state legalisation is a public health concern, especially among older age groups. Given cannabis commercialisation and widespread public beliefs about its efficacy, clinical monitoring of cannabis use and discussion of the risk of cannabis use disorder among patients with chronic pain is warranted. FUNDING: NIDA grant R01DA048860, New York State Psychiatric Institute, and the VA Centers of Excellence in Substance Addiction Treatment and Education.

Methamphetamine use and illicit opioid use during buprenorphine treatment.

Introduction: Although methamphetamine use is rising in the United States, its impacts on patient outcomes among persons undergoing treatment for opioid use disorder (OUD) remain unclear. This study aims to assess the association between baseline methamphetamine/amphetamine (MA/A) use and subsequent illicit opioid use among patients with OUD initiating buprenorphine in an office-based setting. Methods: We conducted a secondary analysis of a pilot randomized controlled trial of a behavioral mobile health intervention for buprenorphine adherence conducted over a 12-week study period at two clinic sites. The study defined baseline MA/A use by a positive urine drug test (UDT) and/or self-report of use within the past 30-days. Separate Poisson regression models with robust standard errors evaluated associations between MA/A and: i) illicit opioid use measured by weekly UDT (primary) and ii) self-reported past 30-day use at end of study (secondary). Other secondary outcomes included buprenorphine positive UDTs throughout the study and retention in OUD treatment at both weeks 12 and 24 post-randomization. Results: At baseline, 28 (36%) of the 78 participants had MA/A use and use was associated with a statistically significant increase in risk of testing positive for illicit opioids on UDT during the study follow-up period (adjusted relative risk (aRR)=1.54; 95% CI=1.09-2.17; p=0.015), as well as an increased risk for reported past 30-day illicit opioid use at week 12 (aRR=3.86; 95% CI=1.47-10.18; P=0.006). The study found no significant associations between MA/A use and buprenorphine positive UDT or retention in OUD treatment. Conclusions: In this sample of patients initiating buprenorphine, methamphetamine/amphetamine use at baseline was associated with illicit opioid use over a 12-week period. These findings demonstrate how co-use of methamphetamine can impede attainment of ideal OUD treatment outcomes.

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.

Integrating Opioid Use Disorder Treatment Into Primary Care Settings.

Importance: Medication for opioid use disorder (MOUD) (eg, buprenorphine and naltrexone) can be offered in primary care, but barriers to implementation exist. Objective: To evaluate an implementation intervention over 2 years to explore experiences and perspectives of multidisciplinary primary care (PC) teams initiating or expanding MOUD. Design, Setting, and Participants: This survey-based and ethnographic qualitative study was conducted at 12 geographically and structurally diverse primary care clinics that enrolled in a hybrid effectiveness-implementation study from July 2020 to July 2022 and included PC teams (prescribing clinicians, nonprescribing behavioral health care managers, and consulting psychiatrists). Survey data analysis was conducted from February to April 2022. Exposure: Implementation intervention (external practice facilitation) to integrate OUD treatment alongside existing collaborative care for mental health services. Measures: Data included (1) quantitative surveys of primary care teams that were analyzed descriptively and triangulated with qualitative results and (2) qualitative field notes from ethnographic observation of clinic implementation meetings analyzed using rapid assessment methods. Results: Sixty-two primary care team members completed the survey (41 female individuals [66%]; 1 [2%] American Indian or Alaskan Native, 4 [7%] Asian, 5 [8%] Black or African American, 5 [8%] Hispanic or Latino, 1 [2%] Native Hawaiian or Other Pacific Islander, and 46 [4%] White individuals), of whom 37 (60%) were between age 25 and 44 years. An analysis of implementation meetings (n = 362) and survey data identified 4 themes describing multilevel factors associated with PC team provision of MOUD during implementation, with variation in their experience across clinics. Themes characterized challenges with clinical administrative logistics that limited the capacity to provide rapid access to care and patient engagement as well as clinician confidence to discuss aspects of MOUD care with patients. These challenges were associated with conflicting attitudes among PC teams toward expanding MOUD care. Conclusions and Relevance: The results of this survey and qualitative study of PC team perspectives suggest that PC teams need flexibility in appointment scheduling and the capacity to effectively engage patients with OUD as well as ongoing training to maintain clinician confidence in the face of evolving opioid-related clinical issues. Future work should address structural challenges associated with workload burden and limited schedule flexibility that hinder MOUD expansion in PC settings.