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.

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.

"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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Risks of returning to opioid use at treatment entry and early in opioid use disorder treatment: Role of non-opioid substances

OBJECTIVE

Patients in treatment with medications for opioid use disorder (MOUD) often report use of other substances in addition to opioids. Few studies exist that examine the relationship between use at treatment entry and early non-opioid use in opioid treatment outcome.

METHODOLOGY

We combined and harmonized three randomized, controlled MOUD clinical trials from the National Institutes of Drug Abuse (NIDA) Clinical Trials Network (CTN) (N=2197) and investigated the association of non-opioid substance use at treatment entry and during early treatment with a return to opioid use. The trials compared MOUD treatment (buprenorphine, methadone, extended-release naltrexone) in populations with opioid use disorder (OUD). Non-opioid substances were identified through harmonizing self-reported use. The primary outcomes were markers of return to opioid use by 12 weeks.

RESULTS

When treatment cohorts were adjusted, no association between self-reported treatment entry use of non-opioid substances and week-12 opioid use was detected. During the first month of treatment, higher use of cocaine (OR 1.41 [1.18-1.69]) and amphetamine (OR 1.70 [1.27-2.26]) was found to be associated with higher likelihood of illicit opioid use by week 12. Exploratory analyses of potential treatment cohort-by-predictor interactions showed that those with heavier cocaine use had a lower rate of returning to opioid use in the extended-release naltrexone group than in the methadone group.

CONCLUSION

Substance use other than opioids at treatment entry is not associated with relapse. Use of cocaine or amphetamines during the first few weeks of MOUD treatment may signal a worse outcome, suggesting a need for additional interventions.

Increasing risk of cannabis use disorder among U.S. veterans with chronic pain: 2005-2019

ABSTRACT

In the United States, cannabis is increasingly used to manage chronic pain. Veterans Health Administration (VHA) patients are disproportionately affected by pain and may use cannabis for symptom management. Because cannabis use increases the risk of cannabis use disorders (CUDs), we examined time trends in CUD among VHA patients with and without chronic pain, and whether these trends differed by age. From VHA electronic health records from 2005 to 2019 (∼4.3-5.6 million patients yearly), we extracted diagnoses of CUD and chronic pain conditions ( International Classification of Diseases [ ICD ]- 9-CM , 2005-2014; ICD-10-CM , 2016-2019). Differential trends in CUD prevalence overall and age-stratified (<35, 35-64, or ≥65) were assessed by any chronic pain and number of pain conditions (0, 1, or ≥2). From 2005 to 2014, the prevalence of CUD among patients with any chronic pain increased significantly more (1.11%-2.56%) than those without pain (0.70%-1.26%). Cannabis use disorder prevalence increased significantly more among patients with chronic pain across all age groups and was highest among those with ≥2 pain conditions. From 2016 to 2019, CUD prevalence among patients age ≥65 with chronic pain increased significantly more (0.63%-1.01%) than those without chronic pain (0.28%-0.47%) and was highest among those with ≥2 pain conditions. Over time, CUD prevalence has increased more among VHA patients with chronic pain than other VHA patients, with the highest increase among those age ≥65. Clinicians should monitor symptoms of CUD among VHA patients and others with chronic pain who use cannabis, and consider noncannabis therapies, particularly because the effectiveness of cannabis for chronic pain management remains inconclusive.

Towards shortening the Brief Addiction Monitor-Revised (BAM-R)

Introduction

The Brief Addiction Monitor-Revised (BAM-R) is a widely used, 17-item assessment of substance use, risk, and protective factors associated with recovery from substance use disorders. Despite wide adoption in the U.S. Department of Veterans Affairs (VA) and recommendations for use in measurement-based care (MBC), administration may not be feasible in many MBC settings due to time constraints. The purpose of this study was to derive a shortened version of the BAM-R for use in fast-paced healthcare settings.

Methods

BAM-R data from 32,002 Veterans were obtained through the VA's Corporate Data Warehouse. We used logistic regression models to identify items for removal based on prediction of two clinical outcomes (90-day substance use disorder (SUD) treatment retention and 12-month mortality) and item-level sensitivity to change during substance use treatment.

Results

Although no intake BAM-R items predicted SUD treatment retention or mortality, effect sizes for item-level sensitivity to change during substance use treatment varied from small to large. Seven items were judged as relevant for MBC of SUD. Among all BAM-R items, Heavy Alcohol Use, Self-Help, Drug Use, Craving, and Mood items demonstrated the greatest magnitude of sensitivity to change.

Conclusions

Although additional research is recommended before a shortened BAM-R can be implemented in non-specialty MBC settings, we identified 5 BAM-R items with perceived clinical utility and scores that demonstrated evidence of sensitivity to change. Shortening the BAM-R increases feasibility of use, though more work is needed to optimize measurement for SUD MBC.

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.

Care coordination between rural primary care and telemedicine to expand medication treatment for opioid use disorder: Results from a single-arm, multisite feasibility study

PURPOSE

The use of telemedicine (TM) has accelerated in recent years, yet research on the implementation and effectiveness of TM-delivered medication treatment for opioid use disorder (MOUD) has been limited. This study investigated the feasibility of implementing a care coordination model involving MOUD delivered via an external TM provider for the purpose of expanding access to MOUD for patients in rural settings.

METHODS

The study tested a care coordination model in 6 rural primary care sites by establishing referral and coordination between the clinic and a TM company for MOUD. The intervention spanned approximately 6 months from July/August 2020 to January 2021, coinciding with the peak of the COVID-19 pandemic. Each clinic tracked patients with OUD in a registry during the intervention period. A pre-/post-intervention design (N = 6) was used to assess the clinic-level outcome as patient-days on MOUD based on patient electronic health records.

FINDINGS

All clinics implemented critical components of the intervention, with an overall TM referral rate of 11.7% among patients in the registry. Five of the 6 sites showed an increase in patient-days on MOUD during the intervention period compared to the 6-month period before the intervention (mean increase per 1,000 patients: 132 days, P = .08, Cohen's d = 0.55). The largest increases occurred in clinics that lacked MOUD capacity or had a greater number of patients initiating MOUD during the intervention period.

CONCLUSIONS

To expand access to MOUD in rural settings, the care coordination model is most effective when implemented in clinics that have negligible or limited MOUD capacity.

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.

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.

Workload, Usability, and Engagement with a Mobile App Supporting Video Observation of Methadone Take-Home Dosing: Usability Study

BACKGROUND

Methadone, a cornerstone of opioid use disorder treatments for many decades, is an essential tool for combatting the opioid epidemic. However, requirements for observing methadone dosing in person through direct observed therapy (DOT) impose significant barriers for many patients. Digital technology can facilitate remote DOT, which could reduce barriers to methadone treatment. Currently, there are limited data on the usability of such technology among patients and counselors in methadone treatment settings.

OBJECTIVE

The primary objective of this study was to assess the workload, usability, and engagement of a video-based DOT mobile app for patients with opioid use disorder receiving methadone treatment. The secondary objective was to assess the workload, usability, and engagement of the provider-facing app portal used by counselors.

METHODS

Patients (n=12) and counselors (n=3) who previously tried video DOT for methadone through a smartphone app in an opioid treatment program participated in usability testing sessions. Participants completed essential tasks for video DOT, then provided ratings of workload (NASA Task Load Index), usability (modified System Usability Scale), and engagement (modified Engagement Scale) with the core features of the video DOT program.

RESULTS

Patients and counselors reported low mental, physical, and temporal demands, successful performance, low effort, and low frustration associated with activities. Patients reported high usability (mean 85, SD 9.5) and engagement (mean 3.8, SD 1.1); counselors reported moderate usability (mean 43.3, SD 17.7) and engagement (mean 2.81, SD 0.63).

CONCLUSIONS

A mobile health app that facilitates video-based DOT for methadone required a low workload for patients and counselors and was highly usable for patients in an opioid treatment program; however, there are opportunities to improve usability and engagement for the counselor-facing portal.

Chronic Pain, Cannabis Legalization and Cannabis Use Disorder in Veterans Health Administration Patients, 2005 to 2019

Background

The risk for cannabis use disorder (CUD) is elevated among U.S. adults with chronic pain, and CUD rates are disproportionately increasing in this group. Little is known about the role of medical cannabis laws (MCL) and recreational cannabis laws (RCL) in these increases. Among U.S. Veterans Health Administration (VHA) patients, we examined whether MCL and RCL effects on CUD prevalence differed between patients with and without chronic pain.

Methods

Patients with ≥1 primary care, emergency, or mental health visit to the VHA and no hospice/palliative care within a given calendar year, 2005-2019 (yearly n=3,234,382 to 4,579,994) were analyzed using VHA electronic health record (EHR) data. To estimate the role of MCL and RCL enactment in the increases in prevalence of diagnosed CUD and whether this differed between patients with and without chronic pain, staggered-adoption difference-in-difference analyses were used, fitting a linear binomial regression model with fixed effects for state, categorical year, time-varying cannabis law status, state-level sociodemographic covariates, a chronic pain indicator, and patient covariates (age group [18-34, 35-64; 65-75], sex, and race and ethnicity). Pain was categorized using an American Pain Society taxonomy of painful medical conditions.

Outcomes

In patients with chronic pain, enacting MCL led to a 0·14% (95% CI=0·12%-0·15%) absolute increase in CUD prevalence, with 8·4% of the total increase in CUD prevalence in MCL-enacting states attributable to MCL. Enacting RCL led to a 0·19% (95%CI: 0·16%, 0·22%) absolute increase in CUD prevalence, with 11·5% of the total increase in CUD prevalence in RCL-enacting states attributable to RCL. In patients without chronic pain, enacting MCL and RCL led to smaller absolute increases in CUD prevalence (MCL: 0·037% [95%CI: 0·03, 0·05]; RCL: 0·042% [95%CI: 0·02, 0·06]), with 5·7% and 6·0% of the increases in CUD prevalence attributable to MCL and RCL. Overall, MCL and RCL effects were significantly greater in patients with than without chronic pain. By age, MCL and RCL effects were negligible in patients age 18-34 with and without pain. In patients age 35-64 with and without pain, MCL and RCL effects were significant (p<0.001) but small. In patients age 65-75 with pain, absolute increases were 0·10% in MCL-only states and 0·22% in MCL/RCL states, with 9·3% of the increase in CUD prevalence in MCL-only states attributable to MCL, and 19.4% of the increase in RCL states attributable to RCL. In patients age 35-64 and 65-75, MCL and RCL effects were significantly greater in patients with pain.

Interpretation

In patients age 35-75, the role of MCL and RCL in the increasing prevalence of CUD was greater in patients with chronic pain than in those without chronic pain, with particularly pronounced effects in patients with chronic pain age 65-75. Although the VHA offers extensive behavioral and non-opioid pharmaceutical treatments for pain, cannabis may seem a more appealing option given media enthusiasm about cannabis, cannabis commercialization activities, and widespread public beliefs about cannabis efficacy. Cannabis does not have the risk/mortality profile of opioids, but CUD is a clinical condition with considerable impairment and comorbidity. Because cannabis legalization in the U.S. is likely to further increase, increasing CUD prevalence among patients with chronic pain following state legalization is a public health concern. The risk of chronic pain increases as individuals age, and the average age of VHA patients and the U.S. general population is increasing. Therefore, clinical monitoring of cannabis use and discussion of the risk of CUD among patients with chronic pain is warranted, especially among older patients.

Research in Context

Evidence before this study: Only three studies have examined the role of state medical cannabis laws (MCL) and/or recreational cannabis laws (RCL) in the increasing prevalence of cannabis use disorder (CUD) in U.S. adults, finding significant MCL and RCL effects but with modest effect sizes. Effects of MCL and RCL may vary across important subgroups of the population, including individuals with chronic pain. PubMed was searched by DH for publications on U.S. time trends in cannabis legalization, cannabis use disorders (CUD) and pain from database inception until March 15, 2023, without language restrictions. The following search terms were used: (medical cannabis laws) AND (pain) AND (cannabis use disorder); (recreational cannabis laws) AND (pain) AND (cannabis use disorder); (cannabis laws) AND (pain) AND (cannabis use disorder). Only one study was found that had CUD as an outcome, and this study used cross-sectional data from a single year, which cannot be used to determine trends over time. Therefore, evidence has been lacking on whether the role of state medical and recreational cannabis legalization in the increasing US adult prevalence of CUD differed by chronic pain status.Added value of this study: To our knowledge, this is the first study to examine whether the effects of state MCL and RCL on the nationally increasing U.S. rates of adult cannabis use disorder differ by whether individuals experience chronic pain or not. Using electronic medical record data from patients in the Veterans Health Administration (VHA) that included extensive information on medical conditions associated with chronic pain, the study showed that the effects of MCL and RCL on the prevalence of CUD were stronger among individuals with chronic pain age 35-64 and 65-75, an effect that was particularly pronounced in older patients ages 65-75.Implications of all the available evidence: MCL and RCL are likely to influence the prevalence of CUD through commercialization that increases availability and portrays cannabis use as 'normal' and safe, thereby decreasing perception of cannabis risk. In patients with pain, the overall U.S. decline in prescribed opioids may also have contributed to MCL and RCL effects, leading to substitution of cannabis use that expanded the pool of individuals vulnerable to CUD. The VHA offers extensive non-opioid pain programs. However, positive media reports on cannabis, positive online "information" that can sometimes be misleading, and increasing popular beliefs that cannabis is a useful prevention and treatment agent may make cannabis seem preferable to the evidence-based treatments that the VHA offers, and also as an easily accessible option among those not connected to a healthcare system, who may face more barriers than VHA patients in accessing non-opioid pain management. When developing cannabis legislation, unintended consequences should be considered, including increased risk of CUD in large vulnerable subgroups of the population.

Feasibility, Engagement, and Usability of a Remote, Smartphone-Based Contingency Management Program as a Treatment Add-On for Patients Who Use Methamphetamine: Single-Arm Pilot Study

BACKGROUND

In the United States, methamphetamine-related overdoses have tripled from 2015 to 2020 and continue to rise. However, efficacious treatments such as contingency management (CM) are often unavailable in health systems.

OBJECTIVE

We conducted a single-arm pilot study to evaluate the feasibility, engagement, and usability of a fully remotely delivered mobile health CM program offered to adult outpatients who used methamphetamine and were receiving health care within a large university health system.

METHODS

Participants were referred by primary care or behavioral health clinicians between September 2021 and July 2022. Eligibility criteria screening was conducted by telephone and included self-reported methamphetamine use on ≥5 out of the past 30 days and a goal of reducing or abstaining from methamphetamine use. Eligible participants who agreed to take part then completed an initial welcome phase that included 2 videoconference calls to register for and learn about the CM program and 2 "practice" saliva-based substance tests prompted by a smartphone app. Participants who completed these welcome phase activities could then receive the remotely delivered CM intervention for 12 consecutive weeks. The intervention included approximately 24 randomly scheduled smartphone alerts requesting a video recording of themselves taking a saliva-based substance test to verify recent methamphetamine abstinence, 12 weekly calls with a CM guide, 35 self-paced cognitive behavioral therapy modules, and multiple surveys. Financial incentives were disbursed via reloadable debit cards. An intervention usability questionnaire was completed at the midpoint.

RESULTS

Overall, 37 patients completed telephone screenings, with 28 (76%) meeting the eligibility criteria and consenting to participate. Most participants who completed a baseline questionnaire (21/24, 88%) self-reported symptoms consistent with severe methamphetamine use disorder, and most had other co-occurring non-methamphetamine substance use disorders (22/28, 79%) and co-occurring mental health disorders (25/28, 89%) according to existing electronic health records. Overall, 54% (15/28) of participants successfully completed the welcome phase and were able to receive the CM intervention. Among these participants, engagement with substance testing, calls with CM guides, and cognitive behavioral therapy modules varied. Rates of verified methamphetamine abstinence in substance testing were generally low but varied considerably across participants. Participants reported positive opinions about the intervention's ease of use and satisfaction with the intervention.

CONCLUSIONS

Fully remote CM can be feasibly delivered within health care settings lacking existing CM programs. Although remote delivery may help reduce barriers to treatment access, many patients who use methamphetamine may struggle to engage with initial onboarding. High rates of co-occurring psychiatric conditions in the patient population may also contribute to uptake and engagement challenges. Future efforts could leverage greater human-to-human connection, more streamlined onboarding procedures, larger incentives, longer durations, and the incentivization of non-abstinence-based recovery goals to increase uptake and engagement with fully remote mobile health-based CM.

Clinician Perspectives on Delivering Medication Treatment for Opioid Use Disorder during the COVID-19 Pandemic: A Qualitative Evaluation

OBJECTIVE

The coronavirus disease 2019 (COVID-19) pandemic necessitated changes in opioid use disorder care. Little is known about COVID-19's impact on general healthcare clinicians' experiences providing medication treatment for opioid use disorder (MOUD). This qualitative evaluation assessed clinicians' beliefs about and experiences delivering MOUD in general healthcare clinics during COVID-19.

METHODS

Individual semistructured interviews were conducted May through December 2020 with clinicians participating in a Department of Veterans Affairs initiative to implement MOUD in general healthcare clinics. Participants included 30 clinicians from 21 clinics (9 primary care, 10 pain, and 2 mental health). Interviews were analyzed using thematic analysis.

RESULTS

The following 4 themes were identified: overall impact of the pandemic on MOUD care and patient well-being, features of MOUD care impacted, MOUD care delivery, and continuance of telehealth for MOUD care. Clinicians reported a rapid shift to telehealth care, resulting in few changes to patient assessments, MOUD initiations, and access to and quality of care. Although technological challenges were noted, clinicians highlighted positive experiences, including treatment destigmatization, more timely visits, and insight into patients' environments. Such changes resulted in more relaxed clinical interactions and improved clinic efficiency. Clinicians reported a preference for in-person and telehealth hybrid care models.

CONCLUSIONS

After the quick shift to telehealth-based MOUD delivery, general healthcare clinicians reported few impacts on quality of care and highlighted several benefits that may address common barriers to MOUD care. Evaluations of in-person and telehealth hybrid care models, clinical outcomes, equity, and patient perspectives are needed to inform MOUD services moving forward.

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.

Use of Video Directly Observed Therapy and Characteristics Associated With Use Among Patients Treated With Buprenorphine in an Office-based Setting

OBJECTIVES

Video directly observed therapy (video DOT) is a tool for confirming buprenorphine adherence that could complement the use of urine toxicology; research is needed to characterize the patients who are receptive and able to use this technology. We aimed to describe video DOT utilization and assess participant characteristics associated with use.

METHODS

We performed a secondary analysis of data from a pilot randomized controlled trial of adults who recently initiated sublingual buprenorphine in office-based programs, restricting to intervention arm participants, which consisted of 12 weeks of video DOT via a mobile health technology platform. Participants were instructed to record at least 1 daily video of buprenorphine self-administration. Poisson regression models with robust standard errors were used to measure associations between participant characteristics and frequency of submitted videos.

RESULTS

The sample included 39 participants. Of 3276 possible videos, 1002 (31%) were submitted. Age ≥40 years (relative risk [RR], 2.54 [95% confidence interval {CI}, 1.31-4.91]) and once-daily buprenorphine dosing (RR, 3.10 [95% CI, 1.76-5.48]) were positively associated with video submissions. Non-White race (RR, 0.43 [95% CI, 0.19-0.97]), less than high school education (RR, 0.27 [95% CI, 0.10-0.74]), history of previous buprenorphine treatment (RR, 0.50 [95% CI, 0.25-0.97]), and ≥3 previous treatment attempts (RR, 0.16 [95% CI, 0.07-0.37]) were negatively associated.

CONCLUSIONS

Video DOT utilization resulted in about a third of expected videos, although there were differences in use according to age, race, buprenorphine treatment factors, and educational status. Such differences underscore that mobile-health interventions such as video DOT may not be equally used by all patients.Trial Registration : ClinicalTrails.gov , NCT03779997 , registered on December 19, 2018.

State Cannabis Legalization and Cannabis Use Disorder in the US Veterans Health Administration, 2005 to 2019

Importance

Cannabis use disorder (CUD) is increasing among US adults. Few national studies have addressed the role of medical cannabis laws (MCLs) and recreational cannabis laws (RCLs) in these increases, particularly in patient populations with high rates of CUD risk factors.

Objective

To quantify the role of MCL and RCL enactment in the increases in diagnosed CUD prevalence among Veterans Health Administration (VHA) patients from 2005 to 2019.

Design, Setting, and Participants

Staggered-adoption difference-in-difference analyses were used to estimate the role of MCL and RCL in the increases in prevalence of CUD diagnoses, fitting a linear binomial regression model with fixed effects for state, categorical year, time-varying cannabis law status, state-level sociodemographic covariates, and patient age group, sex, and race and ethnicity. Patients aged 18 to 75 years with 1 or more VHA primary care, emergency department, or mental health visit and no hospice/palliative care within a given calendar year were included. Time-varying yearly state control covariates were state/year rates from American Community Survey data: percentage male, Black, Hispanic, White, 18 years or older, unemployed, income below poverty threshold, and yearly median household income. Analysis took place between February to December 2022.

Main Outcomes and Measures

As preplanned, International Classification of Diseases, Clinical Modification, ninth and tenth revisions, CUD diagnoses from electronic health records were analyzed.

Results

The number of individuals analyzed ranged from 3 234 382 in 2005 to 4 579 994 in 2019. Patients were largely male (94.1% in 2005 and 89.0% in 2019) and White (75.0% in 2005 and 66.6% in 2019), with a mean (SD) age of 57.0 [14.4] years. From 2005 to 2019, adjusted CUD prevalences increased from 1.38% to 2.25% in states with no cannabis laws (no CLs), 1.38% to 2.54% in MCL-only enacting states, and 1.39% to 2.56% in RCL-enacting states. Difference-in-difference results indicated that MCL-only enactment was associated with a 0.05% (0.05-0.06) absolute increase in CUD prevalence, ie, that 4.7% of the total increase in CUD prevalence in MCL-only enacting states could be attributed to MCLs, while RCL enactment was associated with a 1.12% (95% CI, 0.10-0.13) absolute increase in CUD prevalence, ie, that 9.8% of the total increase in CUD prevalence in RCL-enacting states could be attributed to RCLs. The role of RCL in the increases in CUD prevalence was greatest in patients aged 65 to 75 years, with an absolute increase of 0.15% (95% CI, 0.13-0.17) in CUD prevalence associated with RCLs, ie, 18.6% of the total increase in CUD prevalence in that age group.

Conclusions and Relevance

In this study of VHA patients, MCL and RCL enactment played a significant role in the overall increases in CUD prevalence, particularly in older patients. However, consistent with general population studies, effect sizes were relatively small, suggesting that cumulatively, laws affected cannabis attitudes diffusely across the country or that other factors played a larger role in the overall increases in adult CUD. Results underscore the need to screen for cannabis use and CUD and to treat CUD when it is present.

Integrating Routine Screening for Opioid Use Disorder into Primary Care Settings: Experiences from a National Cohort of Clinics

BACKGROUND

The U.S. Preventive Services Task Force recommends routine population-based screening for drug use, yet screening for opioid use disorder (OUD) in primary care occurs rarely, and little is known about barriers primary care teams face.

OBJECTIVE

As part of a multisite randomized trial to provide OUD and behavioral health treatment using the Collaborative Care Model, we supported 10 primary care clinics in implementing routine OUD screening and conducted formative evaluation to characterize early implementation experiences.

DESIGN

Qualitative formative evaluation.

APPROACH

Formative evaluation included taking detailed observation notes at implementation meetings with individual clinics and debriefings with external facilitators. Observation notes were analyzed weekly using a Rapid Assessment Process guided by the Consolidated Framework for Implementation Research, with iterative feedback from the study team. After clinics launched OUD screening, we conducted structured fidelity assessments via group interviews with each site to evaluate clinic experiences with routine OUD screening. Data from observation and structured fidelity assessments were combined into a matrix to compare across clinics and identify cross-cutting barriers and promising implementation strategies.

KEY RESULTS

While all clinics had the goal of implementing population-based OUD screening, barriers were experienced across intervention, individual, and clinic setting domains, with compounding effects for telehealth visits. Seven themes emerged characterizing barriers, including (1) challenges identifying who to screen, (2) complexity of the screening tool, (3) staff discomfort and/or hesitancies, (4) workflow barriers that decreased screening follow-up, (5) staffing shortages and turnover, (6) discouragement from low screening yield, and (7) stigma. Promising implementation strategies included utilizing a more universal screening approach, health information technology (HIT), audit and feedback, and repeated staff trainings.

CONCLUSIONS

Integrating population-based OUD screening in primary care is challenging but may be made feasible via implementation strategies and tailored practice facilitation that standardize workflows via HIT, decrease stigma, and increase staff confidence regarding OUD.

Baseline representativeness of patients in clinics enrolled in the PRimary care Opioid Use Disorders treatment (PROUD) trial: comparison of trial and non-trial clinics in the same health systems

BACKGROUND

Pragmatic primary care trials aim to test interventions in "real world" health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial.

METHODS

This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16-90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization ("baseline"). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD).

RESULTS

Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics' patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: - 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42).

CONCLUSIONS

trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials.

Comparing mental and physical health of U.S. veterans by VA healthcare use: implications for generalizability of research in the VA electronic health records

OBJECTIVE

The Department of Veterans Affairs' (VA) electronic health records (EHR) offer a rich source of big data to study medical and health care questions, but patient eligibility and preferences may limit generalizability of findings. We therefore examined the representativeness of VA veterans by comparing veterans using VA healthcare services to those who do not.

METHODS

We analyzed data on 3051 veteran participants age ≥ 18 years in the 2019 National Health Interview Survey. Weighted logistic regression was used to model participant characteristics, health conditions, pain, and self-reported health by past year VA healthcare use and generate predicted marginal prevalences, which were used to calculate Cohen's d of group differences in absolute risk by past-year VA healthcare use.

RESULTS

Among veterans, 30.4% had past-year VA healthcare use. Veterans with lower income and members of racial/ethnic minority groups were more likely to report past-year VA healthcare use. Health conditions overrepresented in past-year VA healthcare users included chronic medical conditions (80.6% vs. 69.4%, d = 0.36), pain (78.9% vs. 65.9%; d = 0.35), mental distress (11.6% vs. 5.9%; d = 0.47), anxiety (10.8% vs. 4.1%; d = 0.67), and fair/poor self-reported health (27.9% vs. 18.0%; d = 0.40).

CONCLUSIONS

Heterogeneity in veteran sociodemographic and health characteristics was observed by past-year VA healthcare use. Researchers working with VA EHR data should consider how the patient selection process may relate to the exposures and outcomes under study. Statistical reweighting may be needed to generalize risk estimates from the VA EHR data to the overall veteran population.

Sex Differences in Comorbid Mental and Substance Use Disorders Among Primary Care Patients With Opioid Use Disorder

OBJECTIVE

The authors sought to characterize the 3-year prevalence of mental disorders and nonnicotine substance use disorders among male and female primary care patients with documented opioid use disorder across large U.S. health systems.

METHODS

This retrospective study used 2014-2016 data from patients ages ≥16 years in six health systems. Diagnoses were obtained from electronic health records or claims data; opioid use disorder treatment with buprenorphine or injectable extended-release naltrexone was determined through prescription and procedure data. Adjusted prevalence of comorbid conditions among patients with opioid use disorder (with or without treatment), stratified by sex, was estimated by fitting logistic regression models for each condition and applying marginal standardization.

RESULTS

Females (53.2%, N=7,431) and males (46.8%, N=6,548) had a similar prevalence of opioid use disorder. Comorbid mental disorders among those with opioid use disorder were more prevalent among females (86.4% vs. 74.3%, respectively), whereas comorbid other substance use disorders (excluding nicotine) were more common among males (51.9% vs. 60.9%, respectively). These differences held for those receiving medication treatment for opioid use disorder, with mental disorders being more common among treated females (83% vs. 71%) and other substance use disorders more common among treated males (68% vs. 63%). Among patients with a single mental health condition comorbid with opioid use disorder, females were less likely than males to receive medication treatment for opioid use disorder (15% vs. 20%, respectively).

CONCLUSIONS

The high rate of comorbid conditions among patients with opioid use disorder indicates a strong need to supply primary care providers with adequate resources for integrated opioid use disorder treatment.

Acceptability, feasibility, and outcomes of a clinical pilot program for video observation of methadone take-home dosing during the COVID-19 pandemic

BACKGROUND

Methadone is one of the most utilized treatments for opioid use disorder. However, requirements for observing methadone dosing can impose barriers to patients and increase risk for respiratory illness transmission (e.g., COVID-19). Video observation of methadone dosing at home could allow opioid treatment programs (OTPs) to offer more take-home doses while ensuring patient safety through remote observation of ingestion.

METHODS

Between April and August 2020, a clinical pilot program of video observation of methadone take-home dosing via smartphone was conducted within a multisite OTP agency. Participating patients completed a COVID-19 symptom screener and submitted video recordings of themselves ingesting all methadone take-home doses. Patients who followed these procedures for a two-week trial period could continue participating in the full pilot program and potentially receive more take-home doses. This retrospective observational study characterizes patient engagement and compares clinical outcomes with matched controls.

RESULTS

Of 44 patients who initiated the two-week trial, 33 (75 %) were successful and continued participating in the full pilot program. Twenty full pilot participants (61 %) received increased take-home doses. Full pilot participants had more days with observed dosing over a 60-day period than matched controls (mean = 53.2 vs. 16.6 days, respectively). Clinical outcomes were similar between pilot participants and matched controls.

CONCLUSIONS

Video observation of methadone take-home dosing implemented during the COVID-19 pandemic was feasible. This model has the potential to enhance safety by increasing rates of observed methadone dosing and reducing infection risks and barriers associated with relying solely on face-to-face observation of methadone dosing.

Specific polysubstance use patterns predict relapse among patients entering opioid use disorder treatment

Introduction

While polysubstance use has consistently been associated with higher rates of relapse, few studies have examined subgroups with specific combinations and time course of polysubstance use (i.e., polysubstance use patterns). This study aimed to classify and compare polysubstance use patterns, and their associations with relapse to regular opioid use in 2637 participants in three large opioid use disorder (OUD) treatment trials.

Methods

We explored the daily patterns of self-reported substance use in the 28 days prior to treatment entry. Market basket analysis (MBA) and repeated measure latent class analysis (RMLCA) were used to examine the subgroups of polysubstance use patterns, and multiple logistic regression was used to examine associations between identified classes and relapse.

Results

MBA and RMLCA identified 34 "associations rules " and 6 classes, respectively. Specific combinations of polysubstance use and time course (high baseline use and rapid decrease of use prior to initiation) predicts a worse relapse outcome. MBA showed individuals who co-used cocaine, heroin, prescription opioids, and cannabis had a higher risk for relapse (OR = 2.82, 95%CI = 1.13, 7.03). In RMLCA, higher risk of relapse was observed in individuals who presented with high baseline prescription opioid (OR = 1.9, 95% CI = 1.3, 2.76) or heroin use (OR = 3.54, 95%CI = 1.86, 6.72), although use decreased in both cases prior to treatment initiation.

Conclusions

Our analyses identified subgroups with distinct patterns of polysubstance use. Different patterns of polysubstance use differentially predict relapse outcomes. Interventions tailored to these individuals with specific polysubstance use patterns prior to treatment initiation may increase the effectiveness of relapse prevention.

Trends in Cannabis Use Disorder Diagnoses in the U.S. Veterans Health Administration, 2005-2019

OBJECTIVE

In the United States, adult cannabis use has increased over time, but less information is available on time trends in cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine change over time in cannabis use disorder diagnoses among veterans, an important population subgroup, and whether such trends differ by age group (&lt;35 years, 35-64 years, ≥65 years), sex, or race/ethnicity.

METHODS

VHA electronic health records from 2005 to 2019 (range of Ns per year, 4,403,027-5,797,240) were used to identify the percentage of VHA patients seen each year with a cannabis use disorder diagnosis (ICD-9-CM, January 1, 2005-September 30, 2015; ICD-10-CM, October 1, 2015-December 31, 2019). Trends in cannabis use disorder diagnoses were examined by age and by race/ethnicity and sex within age groups. Given the transition in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM).

RESULTS

In 2005, the percentages of VHA patients diagnosed with cannabis use disorder in the &lt;35, 35-64, and ≥65 year age groups were 1.70%, 1.59%, and 0.03%, respectively; by 2019, the percentages had increased to 4.84%, 2.86%, and 0.74%, respectively. Although the prevalence of cannabis use disorder was consistently higher among males than females, between 2016 and 2019, the prevalence increased more among females than males in the &lt;35 year group. Black patients had a consistently higher prevalence of cannabis use disorder than other racial/ethnic groups, and increases were greater among Black than White patients in the &lt;35 year group in both periods.

CONCLUSIONS

Since 2005, diagnoses of cannabis use disorder have increased substantially among VHA patients, as they have in the general population and other patient populations. Possible explanations warranting investigation include decreasing perception of risk, changing laws, increasing cannabis potency, stressors related to growing socioeconomic inequality, and use of cannabis to self-treat pain. Clinicians and the public should be educated about the increases in cannabis use disorder in general in the United States, including among patients treated at the VHA.

Trends in Prescriptions for Non-opioid Pain Medications Among U.S. Adults With Moderate or Severe Pain, 2014-2018

As opioid prescribing has declined, it is unclear how the landscape of prescription pain treatment across the U.S. has changed. We used nationally-representative data from the Medical Expenditure Health Survey, 2014 to 2018 to examine trends in prescriptions for opioid and non-opioid pain medications, including acetaminophen, non-steroidal anti-inflammatory drugs, gabapentinoids, and antidepressants among U.S. adults with self-reported pain. Overall, from 2014 to 2018, the percentage of participants receiving a prescription for opioids declined, (38.8% vs 32.8%), remained stable for non-steroidal anti-inflammatory drugs (26.8% vs 27.7%), and increased for acetaminophen (1.6% vs 2.3%), antidepressants (9.6% vs 12.0%) and gabapentinoids (13.2% vs 19.0%). In this period, the adjusted odds of receiving an opioid prescription decreased (aOR = .93, 95% CI = .90-.96), while the adjusted odds of receiving antidepressant, gabapentinoid and acetaminophen prescriptions increased (antidepressants: aOR = 1.08, 95% CI = 1.03-1.13 gabapentinoids: aOR = 1.11, 95% CI = 1.06-1.17; acetaminophen: aOR = 1.10, 95% CI: 1.02-1.20). Secondary analyses stratifiying within the 2014 to 2016 and 2016 to 2018 periods revealed particular increases in prescriptions for gabapentinoids (aOR = 1.13, 95% CI = 1.05-1.21) and antidepressants (aOR = 1.23, 95% CI = 1.12-1.35) since 2016. PERSPECTIVE: These data demonstrate that physicians are increasingly turning to CDC-recommended non-opioid medications for pain management, particularly antidepressants and gabapentinoids. However, evidence for these medications' efficacy in treating numerous common pain conditions, including low back pain, remains limited.

Buprenorphine in safety-sensitive positions

The permissibility of buprenorphine in safety-sensitive positions is a controversial topic. As an opioid medication, concerns have arisen regarding the potential for impairment and any effects that this would have on an employee's ability to safely perform job duties. While there are no definitive guidelines on the use of buprenorphine for those employed in safety-sensitive lines of work, most employers do not permit its use under any circumstance due to the potential risk of harm to the public. In addition to overlooking the fact that buprenorphine is a well-established and life-saving treatment for opioid use disorder (OUD), there are many flaws in making this determination. For one, buprenorphine is a partial mu opioid agonist which makes it inherently unique in comparison to other opioids. Most studies on impairment have examined acute use of full agonist opioids instead of chronic dosing of buprenorphine. Furthermore, assessments of impairment are not tailored to the tasks required of specific positions. Importantly, policies banning buprenorphine may contribute to treatment discontinuation and stigma, which can lead to relapse and overdose. Considering the morbidity and mortality associated with OUD, along with the surge in overdose deaths during the COVID19 pandemic, buprenorphine policies should be considered carefully. Given the lack of evidence showing definitive and specific impairments as a result of chronic buprenorphine use, coupled with the consequences of universal bans on its use, determinations on the permissibility of buprenorphine treatment for safety-sensitive positions should be made on a case-by-case basis.

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.

Moderation of buprenorphine therapy for cocaine dependence efficacy by variation of the Prodynorphin gene

PURPOSE

The aim of this secondary analysis was to identify prodynorphin (PDYN) genetic markers moderating the therapeutic response to treatment of cocaine dependence with buprenorphine/naloxone (Suboxone®; BUP).

METHODS

Cocaine-dependent participants (N = 302) were randomly assigned to a platform of injectable, extended-release naltrexone (XR-NTX) and one of three daily medication arms: 4 mg BUP (BUP4), 16 mg BUP (BUP16), or placebo (PLB) for 8 weeks (Parent Trial Registration: Protocol ID: NIDA-CTN-0048, Clinical Trials.gov ID: NCT01402492). DNA was obtained from 277 participants. Treatment response was determined from weeks 3 to 7 over each 1-week period by the number of cocaine-positive urines per total possible urines.

RESULTS

In the cross-ancestry group, the PLB group had more cocaine-positive urines than the BUP16 group (P = 0.0021). The interactions of genetic variant × treatment were observed in the rs1022563 A-allele carrier group where the BUP16 group (N = 35) had fewer cocaine-positive urines (P = 0.0006) than did the PLB group (N = 26) and in the rs1997794 A-allele carrier group where the BUP16 group (N = 49) had fewer cocaine-positive urines (P = 0.0003) than did the PLB group (N = 58). No difference was observed in the rs1022563 GG or rs1997794 GG genotype groups between the BUP16 and PLB groups. In the African American-ancestry subgroup, only the rs1022563 A-allele carrier group was associated with treatment response.

CONCLUSION

These results suggest that PDYN variants may identify patients who are best suited to treatment with XR-NTX plus buprenorphine for cocaine use disorder pharmacotherapy.

Pain, cannabis use, and physical and mental health indicators among veterans and nonveterans: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III

ABSTRACT

Chronic pain is associated with mental and physical health difficulties and is prevalent among veterans. Cannabis has been put forth as a treatment for chronic pain, and changes in laws, attitudes, and use patterns have occurred over the past 2 decades. Differences in prevalence of nonmedical cannabis use and cannabis use disorder (CUD) were examined across 2 groups: veterans or nonveterans and those reporting or not reporting recent pain. Data from the National Epidemiologic Survey on Alcohol and Related Conditions-III (2012-2013; n = 36,309) were analyzed using logistic regression. Prevalence differences (PDs) for 3 cannabis outcomes (1) past-year nonmedical cannabis use, (2) frequent (≥3 times a week) nonmedical use, and (3) DSM-5 CUD were estimated for those reporting recent moderate to severe pain (veterans or nonveterans) and veterans reporting or not reporting recent pain. Difference in differences was calculated to investigate PDs on outcomes associated with residence in a state with medical cannabis laws (MCLs). Associations between physical and mental health and cannabis variables were tested. The results indicated that the prevalence of recent pain was greater among veterans (PD = 7.25%, 95% confidence interval (CI) [4.90-9.60]). Among veterans, the prevalence of frequent cannabis use was greater among those with pain (PD = 1.92%, 98% CI [0.21-3.63]), and among veterans residing in a state with MCLs, the prevalence of CUD was greater among those reporting recent pain (PD = 3.88%, 98% CI [0.36-7.39]). Findings failed to support the hypothesis that cannabis use improves mental or physical health for veterans with pain. Providers treating veterans with pain in MCL states should monitor such patients closely for CUD.

Rationale, design and methods of VA-BRAVE: a randomized comparative effectiveness trial of two formulations of buprenorphine for treatment of opioid use disorder in veterans

Background

To address the US opioid epidemic, there is an urgent clinical need to provide persons with opioid use disorder (OUD) with effective medication treatments for OUD (MOUD). Formulations of sublingual buprenorphine/naloxone (SL-BUP/NLX) are considered the standard of care for OUD including within the Veterans Healthcare Administration (VHA). However, poor retention on MOUD undermines its effectiveness. Long-acting injectable monthly buprenorphine (INJ-BUP) (e.g., Sublocade®) has the potential to improve retention and therefore reduce opioid use and overdose. Designing and conducting studies for OUD pose unique challenges. The strategies and solutions to some of these considerations in designing Cooperative Studies Program (CSP) 2014, Buprenorphine for Treating Opioid Use Disorder in Veterans (VA-BRAVE), a randomized, 20-site, clinical effectiveness trial comparing INJ-BUP to SL-BUP/NLX conducted within the VHA may provide valuable guidance for others confronted with similar investigation challenges.

Methods

This 52-week, parallel group, open-label, randomized controlled trial (RCT) evaluates the comparative effectiveness of two current FDA-approved formulations of buprenorphine: (1) daily SL-BUP/NLX vs. (2) monthly (28-day) INJ-BUP for Veterans with moderate to severe OUD (n = 952). The primary outcomes are (1) retention in MOUD and (2) opioid abstinence. Secondary outcomes include measures of other drug use, psychiatric symptoms, medical outcomes including prevalence rates of HIV, hepatitis B and C as well as social outcomes (housing instability, criminal justice involvement), service utilization and cost-effectiveness. Special considerations in conducting a comparative effectiveness trial with this population and during COVID-19 pandemic were also included.

Discussion

The evaluation of the extended-release formulation of buprenorphine compared to the standard sublingual formulation in real-world VHA settings is of paramount importance in addressing the opioid epidemic. The extent to which this new treatment facilitates retention, decreases opioid use, and prevents severe sequelae of OUD has not been studied in any long-term trial to date. Positive findings in this trial could lead to widespread adoption of MOUD, and, if proven superior INJ-BUP, by clinicians throughout the VHA and beyond. This treatment has the potential to reduce opioid use among Veterans, improve medical, psychological, and social outcomes, and save lives at justifiable cost.

Trial registration Registered at Clinicaltrials.gov NCT04375033

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.

Long-term follow-up assessment of opioid use outcomes among individuals with comorbid mental disorders and opioid use disorder treated with buprenorphine or methadone in a randomized clinical trial

AIMS

To investigate whether reduction in opioid use differs when treated by either buprenorphine-naloxone (BUP) or methadone (MET) among adults with comorbid opioid use disorder (OUD) and mental disorders.

DESIGN, SETTING AND PARTICIPANTS

In a randomized controlled trial, adults with OUD were randomized to 24 weeks of either BUP or MET treatment and were followed up in 3-yearly assessments. The present secondary analyses were based on 597 participants who completed all assessments.

MEASUREMENTS

The outcome measure was the number of days of using opioids per month during the follow-up period. The Mini-International Neuropsychiatric Interview (MINI) was used to classify participants into three groups: life-time mood disorder (n = 302), life-time mental disorder other than mood disorder (n = 114) and no mental disorder (n = 181). Medication treatment (BUP, MET, no treatment) during the follow-up period was a time-varying predictor.

FINDINGS

Based on zero-inflated Poisson (ZIP) mixed regression analysis, it was found that relative to no treatment, opioid use during the follow-up was significantly reduced by BUP [odds ratio (OR) = 0.12, 95% confidence interval (CI) = 0.07-0.21 for any use; risk ratio (RR) = 0.77, 95% CI =0.66-0.89 for days of use] and by MET [OR = 0.33, 95% CI = 0.25-0.45 for any use; RR = 0.78, 95% CI = 0.72-0.84 for days of use]. Relative to MET, BUP was associated with a lower likelihood of any opioid use among participants with mood disorders (OR = 0.52, 95% CI = 0.36-0.74) and for participants without mental disorder (OR = 0.37, 95% CI = 0.21-0.66) and fewer number of days using opioids (RR = 0.37, 95% CI = 0.25-0.56) among participants with other mental disorders.

CONCLUSIONS

Among adults with comorbid opioid use disorder and mental disorders, treatment with buprenorphine-naloxone produced greater reductions in opioid use than treatment with methadone.

Prevalence and Correlates of Cannabis Use and Cannabis Use Disorder Among U.S. Veterans: Results From the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III)

OBJECTIVE

The authors sought to estimate the prevalence of past-12-month and lifetime cannabis use and cannabis use disorder among U.S. veterans; to describe demographic, substance use disorder, and psychiatric disorder correlates of nonmedical cannabis use and cannabis use disorder; and to explore differences in cannabis use and cannabis use disorder prevalence among veterans in states with and without medical marijuana laws.

METHODS

Participants were 3,119 respondents in the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) who identified as U.S. veterans. Weighted prevalences were calculated. Logistic regression analyses tested associations of nonmedical cannabis use and cannabis use disorder with demographic and clinical correlates and examined whether prevalence differed by state legalization status.

RESULTS

The prevalences of any past-12-month cannabis use and cannabis use disorder were 7.3% and 1.8%, respectively. Lifetime prevalences were 32.5% and 5.7%, respectively. Past-12-month and lifetime cannabis use disorder prevalence estimates among nonmedical cannabis users were 24.4% and 17.4%, respectively. Sociodemographic correlates of nonmedical cannabis use and use disorder included younger age, male gender, being unmarried, lower income, and residing in a state with medical marijuana laws. Nonmedical cannabis use and use disorder were associated with most psychiatric and substance use disorders examined.

CONCLUSIONS

Among veterans, the odds of nonmedical cannabis use and use disorder were elevated among vulnerable subgroups, including those with lower income or psychiatric disorders and among survey participants residing in states with medical marijuana laws. The study findings highlight the need for clinical attention (e.g., screening, assessment) and ongoing monitoring among veterans in the context of increasing legalization of cannabis.

Accessibility to Medication for Opioid Use Disorder After Interventions to Improve Prescribing Among Nonaddiction Clinics in the US Veterans Health Care System

IMPORTANCE

With increasing rates of opioid use disorder (OUD) and overdose deaths in the US, increased access to medications for OUD (MOUD) is paramount. Rigorous effectiveness evaluations of large-scale implementation initiatives using quasi-experimental designs are needed to inform expansion efforts.

OBJECTIVE

To evaluate a US Department of Veterans Affairs (VA) initiative to increase MOUD use in nonaddiction clinics.

DESIGN, SETTING, AND PARTICIPANTS

This quality improvement initiative used interrupted time series design to compare trends in MOUD receipt. Primary care, pain, and mental health clinics in the VA health care system (n = 35) located at 18 intervention facilities and nonintervention comparison clinics (n = 35) were matched on preimplementation MOUD prescribing trends, clinic size, and facility complexity. The cohort of patients with OUD who received care in intervention or comparison clinics in the year after September 1, 2018, were evaluated. The preimplementation period extended from September 1, 2017, through August 31, 2018, and the postimplementation period from September 1, 2018, through August 31, 2019.

EXPOSURES

The multifaceted implementation intervention included education, external facilitation, and quarterly reports.

MAIN OUTCOMES AND MEASURES

The main outcomes were the proportion of patients receiving MOUD and the number of patients per clinician prescribing MOUD. Segmented logistic regression evaluated monthly proportions of MOUD receipt 1 year before and after initiative launch, adjusting for demographic and clinical covariates. Poisson regression models examined yearly changes in clinician prescribing over the same time frame.

RESULTS

Overall, 7488 patients were seen in intervention clinics (mean [SD] age, 53.3 [14.2] years; 6858 [91.6%] male; 1476 [19.7%] Black, 417 [5.6%] Hispanic; 5162 [68.9%] White; 239 [3.2%] other race [including American Indian or Alaska Native, Asian, Native Hawaiian or other Pacific Islander, and multiple races]; and 194 [2.6%] unknown) and 7558 in comparison clinics (mean [SD] age, 53.4 [14.0] years; 6943 [91.9%] male; 1463 [19.4%] Black; 405 [5.4%] Hispanic; 5196 [68.9%] White; 244 [3.2%] other race; 250 [3.3%] unknown). During the preimplementation year, the proportion of patients receiving MOUD in intervention clinics increased monthly by 5.0% (adjusted odds ratio [AOR], 1.05; 95% CI, 1.03-1.07). Accounting for this preimplementation trend, the proportion of patients receiving MOUD increased monthly by an additional 2.3% (AOR, 1.02; 95% CI, 1.00-1.04) during the implementation year. Comparison clinics increased by 2.6% monthly before implementation (AOR, 1.03; 95% CI, 1.01-1.04), with no changes detected after implementation. Although preimplementation-year trends in monthly MOUD receipt were similar in intervention and comparison clinics, greater increases were seen in intervention clinics after implementation (AOR, 1.04; 95% CI, 1.01-1.08). Patients treated with MOUD per clinician in intervention clinics saw greater increases from before to after implementation compared with comparison clinics (incidence rate ratio, 1.50; 95% CI, 1.28-1.77).

CONCLUSIONS AND RELEVANCE

A multifaceted implementation initiative in nonaddiction clinics was associated with increased MOUD prescribing. Findings suggest that engagement of clinicians in general clinical settings may increase MOUD access.

Elevated customary alcohol consumption attenuates opioid effects

BACKGROUND

Regular alcohol consumption is on the rise among older adults and has the potential of altering the subjective experience of pain and response to pain medications. This study examined the cognitive, analgesic and side effect response to oxycodone in middle age and older adults with elevated levels of customary alcohol consumption in a human laboratory setting.

METHODS

After refraining from alcohol for one day, eligible participants underwent baseline assessment cognition and side effects by means of questionnaires that were repeated at three time points (90 min, 5 and 8 h) following administration of a 10 mg oral dose of oxycodone. Response to pain stimulus (Cold Pressor Test (CPT)), pupil size, and plasma oxycodone were also measured.

RESULTS

One hundred twenty-eight adults (age 35-85) completed the study day. Compared to those with lower customary alcohol consumption, participants with elevated alcohol consumption showed attenuated opioid-induced pupil constriction and cognitive decline on objective measures of working memory, sustained attention, inhibitory control, coordination on a simulated driving task, and subjective dysphoric effects with enhanced subjective euphoric effects. Oxycodone pharmacokinetics, pain tolerance to CPT, and Berg balance were impacted comparably between alcohol consumption groups. Women endorsed greater negative drug effects, whereas men endorsed positive drug effects.

CONCLUSION

Independent of subject's age, elevated customary alcohol consumption attenuates opioid central effects (i.e., pupil miosis, impaired cognition) and gender influences subjective drug effects. Clinicians should consider alcohol consumption and gender when prescribing opioid medications.