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.

"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.

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.

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.

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.

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.

Impact of an intervention to implement provision of opioid use disorder medication among patients with and without co-occurring substance use disorders.

INTRODUCTION: Co-occurring substance use disorders (SUDs) are common among people with opioid use disorder (OUD) and known to hinder receipt of medications for OUD (MOUD). It is important to understand how MOUD care implemented outside of SUD specialty settings impacts access for patients with co-occurring SUDs. The Veterans Health Administration's (VA) Stepped Care for Opioid Use Disorder Train the Trainer (SCOUTT) initiative was implemented in primary care, mental health, and pain clinics in 18 VA facilities, and was found to increase MOUD receipt. This study assessed the SCOUTT initiative's impact among patients with and without co-occurring SUDs. METHODS: This study used a controlled interrupted time series design. We extracted electronic health record data for patients with OUD with visits in SCOUTT intervention or matched comparison clinics during the post-implementation year (9/1/2018-8/31/2019). We examined the monthly proportion of patients who received MOUD in SCOUTT intervention or comparison clinics (primary care, mental health, and pain clinics), or in a VA SUD specialty clinic (where patients may have been referred), during the pre- and post-implementation years. Segmented logistic regression models estimated pre-post changes in outcomes (immediate level change from the final month of the pre-implementation period to the first month of the post-implementation period, change in trend/slope) in intervention vs. comparison facilities, adjusting for patient characteristics and pre-implementation trends. We stratified analyses by the presence of co-occurring SUDs. RESULTS: Among patients without co-occurring SUDs, the pre-post trend/slope change in MOUD received in SCOUTT intervention or comparison clinics was greater in intervention vs. comparison facilities (adjusted odds ratio [aOR]: 1.06, 95% confidence interval [CI]: 1.02-1.10), and the immediate increase in MOUD received in SUD clinics was greater in intervention vs. comparison facilities (aOR: 1.12, 95% CI: 1.02-1.22). These changes did not significantly differ in intervention vs. comparison facilities among patients with co-occurring SUDs. CONCLUSIONS: The SCOUTT initiative may have increased MOUD receipt primarily among patients without co-occurring SUDs. Focusing on increasing MOUD receipt for patients with co-occurring SUDs may improve the overall effectiveness of MOUD implementation efforts.

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.

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.

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.

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.

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.

U.S. veterans' experiences and factors associated with use of a smartphone application to self-manage unhealthy alcohol use.

Unhealthy alcohol use is common among Operations Enduring and Iraqi Freedom (OEF/OIF) veterans, yet barriers discourage treatment-seeking. Mobile applications (apps) that deliver alcohol interventions have potential to address these barriers and increase treatment receipt. Few studies have qualitatively assessed users' experiences with apps to manage alcohol use. We assessed OEF/OIF veterans' experiences with Step Away, an app to reduce alcohol-related risks, to identify factors that may influence engagement. This single-arm pilot study recruited OEF/OIF veterans with positive alcohol screens nationwide using mail/telephone. Veterans aged 18-55 who exceeded drinking guidelines and owned an iPhone were eligible. Twenty-one (16 men, 5 women) of 55 participants completed interviews. Interviews were analyzed using thematic analysis. Participants found Step Away easy to use, although setup was time consuming. Participants reported increased awareness of alcohol use, highlighting daily assessment, weekly feedback, goal setting, and high-risk notification features as helpful and associated awareness with an intent to decrease use. Participants described Step Away as informative, with over half reporting they would use it outside of the study and most recommending it. Suggestions for improvement included greater personalization and control over features. Step Away features appear to influence engagement and increase users' awareness about alcohol consumed and factors associated with drinking, as well as intent to change. Assessment, feedback, and customization features of apps may facilitate app engagement. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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 (<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 <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 <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 <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.

Substance use disorders and COVID-19: An analysis of nation-wide Veterans Health Administration electronic health records.

BACKGROUND: Substance use disorders (SUD) elevate the risk for COVID-19 hospitalization, but studies are inconsistent on the relationship of SUD to COVID-19 mortality. METHODS: Veterans Health Administration (VHA) patients treated in 2019 and evaluated in 2020 for COVID-19 (n=5,556,315), of whom 62,303 (1.1%) tested positive for COVID-19 (COVID-19+). Outcomes were COVID-19+ by 11/01/20, hospitalization, ICU admission, or death within 60 days of a positive test. Main predictors were any ICD-10-CM SUDs, with substance-specific SUDs (cannabis, cocaine, opioid, stimulant, sedative) explored individually. Logistic regression produced unadjusted and covariate-adjusted odds ratios (OR; aOR). RESULTS: Among COVID-19+ patients, 19.25% were hospitalized, 7.71% admitted to ICU, and 5.84% died. In unadjusted models, any SUD and all substance-specific SUDs except cannabis use disorder were associated with COVID-19+(ORs=1.06-1.85); adjusted models produced similar results. Any SUD and all substance-specific SUDs were associated with hospitalization (aORs: 1.24-1.91). Any SUD, cocaine and opioid disorder were associated with ICU admission in unadjusted but not adjusted models. Any SUD, cannabis, cocaine, and stimulant disorders were inversely associated with mortality in unadjusted models (OR=0.27-0.46). After adjustment, associations with mortality were no longer significant. In ad hoc analyses, adjusted odds of mortality were lower among the 49.9% of COVID-19+ patients with SUD who had SUD treatment in 2019, but not among those without such treatment. CONCLUSIONS: In VHA patients, SUDs are associated with COVID-19 hospitalization but not COVID-19 mortality. SUD treatment may provide closer monitoring of care, ensuring that these patients received needed medical attention, enabling them to ultimately survive serious illness.

Benzodiazepine Treatment and Hospital Course of Medical Inpatients With Alcohol Withdrawal Syndrome in the Veterans Health Administration.

OBJECTIVE: To describe initial benzodiazepine dosing strategies and factors associated with variation in benzodiazepine dosing in a national cohort of hospitalized patients with alcohol withdrawal syndrome (AWS). PATIENTS AND METHODS: This cross-sectional study included adult patients with AWS admitted to medical services and treated with benzodiazepines at 93 Veterans Health Administration hospitals in 2013. Treatment was categorized by initial benzodiazepine dosing strategy-fixed-dose, symptom-triggered, or front-loading. Associations with patient characteristics, facility, and cumulative benzodiazepine exposure, intensive care, and intubation were evaluated. RESULTS: Among 6938 medical inpatients with AWS, 2909 (41.9%), 2829 (40.8%), and 1200 (17.3%) received treatment with symptom-triggered, fixed-dose, and front-loading benzodiazepines, respectively. The magnitude of differences in initial treatment associated with patient characteristics was small compared with differences associated with the predominant practice at a facility. Compared with fixed-dose therapy, symptom-triggered therapy was associated with higher cumulative benzodiazepine exposure (mean, 208-mg vs 182-mg diazepam equivalents) and higher probability of intensive care and intubation (28.2% vs 21.3% and 4.8% vs 3.5%, respectively). CONCLUSION: This study revealed that real-world AWS treatment of medical inpatients was often inconsistent with published guidelines recommending symptom-triggered long-acting benzodiazepines for AWS. The facility where a patient was hospitalized was associated with marked treatment variation. In contrast to prior randomized controlled trials conducted in specialized detoxification units, hospitalized patients who received symptom-triggered therapy in this study had greater cumulative benzodiazepine exposure and higher probability of intensive care and intubation than those receiving fixed-dose therapy.

Prevalence of medical and nonmedical cannabis use among veterans in primary care.

OBJECTIVE: This study examined past-year cannabis use prevalence and sociodemographic and clinical correlates of cannabis use among Veterans Health Administration (VHA) primary care patients in a state with legalized medical cannabis. METHOD: Participants were 1,072 predominantly white, male, VHA primary care patients enrolled in a drug screening validation study (2012-2014). Sociodemographic and clinical correlates were examined by past-year cannabis use status. Multivariate regression models, adjusted for demographics, estimated cannabis use prevalence and clinical correlates among recreational, medical, and both medical and recreational users. RESULTS: Nearly one in five (18.7%) veterans endorsed past-year cannabis use, with 14.1% of the total sample reporting any recreational use and 7.0% reporting any medical use. Correlates of any past-year use included younger age, period of service, being unmarried, lower education, lower income, other substance use, meeting criteria for an alcohol or drug use disorder or posttraumatic stress disorder, higher pain rating, and lower self-reported well-being. Compared to veterans endorsing only recreational use, veterans endorsing only medical use reported more cannabis use days but had lower odds of other drug use, alcohol or drug-related problems, or alcohol or drug use disorders. Differences between recreational only users and those using medical and recreational cannabis were minimal. CONCLUSIONS: Veterans enrolled in VHA in states with legalized cannabis may be particularly likely to use cannabis. Veterans identifying as recreational users may be at increased risk for adverse clinical outcomes compared to medical-only users. Prevalence monitoring, assessment, and intervention services should be considered, particularly in states with legalized cannabis. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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.

Clinical leaders and providers' perspectives on delivering medications for the treatment of opioid use disorder in Veteran Affairs' facilities.

BACKGROUND: Improving access to medication treatment of opioid use disorder (MOUD) is a national priority, yet common modifiable barriers (e.g., limited provider knowledge, negative beliefs about MOUD) often challenge implementation of MOUD delivery. To address these barriers, the VA launched a multifaceted implementation intervention focused on planning and educational strategies to increase MOUD delivery in 18 medical facilities. The purpose of this investigation was to determine if a multifaceted intervention approach to increase MOUD delivery changed providers' perceptions about MOUD over the first year of implementation. METHODS: Cross-disciplinary teams of clinic providers and leadership from primary care, pain, and mental health clinics at 18 VA medical facilities received invitations to complete an anonymous, electronic survey prior to intervention launch (baseline) and at 12- month follow-up. Responses were summarized using descriptive statistics, and changes over time were compared using regression models adjusted for gender and prescriber status, and clustered on facility. Responses to open-ended questions were thematically analyzed using a template analysis approach. RESULTS: Survey response rates at baseline and follow-up were 57.1% (56/98) and 50.4% (61/121), respectively. At both time points, most respondents agreed that MOUD delivery is important (94.7 vs. 86.9%), lifesaving (92.8 vs. 88.5%) and evidence-based (85.2 vs. 89.5%). Over one-third (37.5%) viewed MOUD delivery as time-consuming, and only 53.7% affirmed that clinic providers wanted to prescribe MOUD at baseline; similar responses were seen at follow-up (34.5 and 52.4%, respectively). Respondents rated their knowledge about OUD, comfort discussing opioid use with patients, job satisfaction, ability to help patients with OUD, and support from colleagues favorably at both time points. Respondents' ratings of MOUD delivery filling a gap in care were high but declined significantly from baseline to follow-up (85.7 vs. 73.7%, p < 0.04). Open-ended responses identified implementation barriers including lack of support to diagnose and treat OUD and lack of time. CONCLUSIONS: Although perceptions about MOUD generally were positive, targeted education and planning strategies did not improve providers' and clinical leaders' perceptions of MOUD over time. Strategies that improve leaders' prioritization and support of MOUD and address time constraints related to delivering MOUD may increase access to MOUD in non-substance use treatment clinics.