A national study of clinical discussions about cannabis use among Veteran patients prescribed opioids.

BACKGROUND: The Veterans Health Administration tracks urine drug tests (UDTs) among patients on long-term opioid therapy (LTOT) and recommends discussing the health effects of cannabis use. OBJECTIVE: To determine the occurrence of cannabis-related discussions between providers and patients on LTOT during six months following UDT positive for cannabis, and examine factors associated with documenting cannabis use. DESIGN: We identified patients prescribed LTOT with a UDT positive for cannabis in 2019. We developed a text-processing tool to extract discussions around cannabis use from their charts. SUBJECTS: Twelve thousand seventy patients were included. Chart review was conducted on a random sample of 1,946 patients. MAIN MEASURES: The presence of a cannabis term in the chart suggesting documented cannabis use or cannabis-related discussions. Content of those discussions was extracted in a subset of patients. Logistic regression was used to examine the association between patient factors, including state of residence legal status, with documentation of cannabis use. KEY RESULTS: Among the 12,070 patients, 65.8% (N = 7,948) had a cannabis term, whereas 34.1% (N = 4,122) of patients lacked a cannabis term, suggesting that no documentation of cannabis use or discussion between provider and patient took place. Among the subset of patients who had a discussion documented, 47% related to cannabis use for medical reasons, 35% related to a discussion of VA policy or legal issues, and 17% related to a discussion specific to medical risks or harm reduction strategies. In adjusted analyses, residents of states with legalized recreational cannabis were less likely to have any cannabis-related discussion compared to patients in non-legal states [OR 0.73, 95% CI 0.64-0.82]. CONCLUSIONS: One-third of LTOT patients did not have documentation of cannabis use in the chart in the 6 months following a positive UDT for cannabis. Discussions related to the medical risks of cannabis use or harm reduction strategies were uncommon.

Association of Cannabis Use With Cardiovascular Outcomes Among US Adults.

BACKGROUND: We examined the association between cannabis use and cardiovascular outcomes among the general population, among never-tobacco smokers, and among younger individuals. METHODS AND RESULTS: This is a population-based, cross-sectional study of 2016 to 2020 data from the Behavioral Risk Factor Surveillance Survey from 27 American states and 2 territories. We assessed the association of cannabis use (number of days of cannabis use in the past 30 days) with self-reported cardiovascular outcomes (coronary heart disease, myocardial infarction, stroke, and a composite measure of all 3) in multivariable regression models, adjusting for tobacco use and other characteristics in adults 18 to 74 years old. We repeated this analysis among nontobacco smokers, and among men <55 years old and women <65 years old who are at risk of premature cardiovascular disease. Among the 434 104 respondents, the prevalence of daily and nondaily cannabis use was 4% and 7.1%, respectively. The adjusted odds ratio (aOR) for the association of daily cannabis use and coronary heart disease, myocardial infarction, stroke, and the composite outcome (coronary heart disease, myocardial infarction, and stroke) was 1.16 (95% CI, 0.98-1.38), 1.25 (95% CI, 1.07-1.46), 1.42 (95% CI, 1.20-1.68), and 1.28 (95% CI, 1.13-1.44), respectively, with proportionally lower log odds for days of use between 0 and 30 days per month. Among never-tobacco smokers, daily cannabis use was also associated with myocardial infarction (aOR, 1.49 [95% CI, 1.03-2.15]), stroke (aOR, 2.16 [95% CI, 1.43-3.25]), and the composite of coronary heart disease, myocardial infarction, and stroke (aOR, 1.77 [95% CI, 1.31-2.40]). Relationships between cannabis use and cardiovascular outcomes were similar for men <55 years old and women <65 years old. CONCLUSIONS: Cannabis use is associated with adverse cardiovascular outcomes, with heavier use (more days per month) associated with higher odds of adverse outcomes.

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.

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.

Deep Learning of Electrocardiograms in Sinus Rhythm From US Veterans to Predict Atrial Fibrillation.

Importance: Early detection of atrial fibrillation (AF) may help prevent adverse cardiovascular events such as stroke. Deep learning applied to electrocardiograms (ECGs) has been successfully used for early identification of several cardiovascular diseases. Objective: To determine whether deep learning models applied to outpatient ECGs in sinus rhythm can predict AF in a large and diverse patient population. Design, Setting, and Participants: This prognostic study was performed on ECGs acquired from January 1, 1987, to December 31, 2022, at 6 US Veterans Affairs (VA) hospital networks and 1 large non-VA academic medical center. Participants included all outpatients with 12-lead ECGs in sinus rhythm. Main Outcomes and Measures: A convolutional neural network using 12-lead ECGs from 2 US VA hospital networks was trained to predict the presence of AF within 31 days of sinus rhythm ECGs. The model was tested on ECGs held out from training at the 2 VA networks as well as 4 additional VA networks and 1 large non-VA academic medical center. Results: A total of 907 858 ECGs from patients across 6 VA sites were included in the analysis. These patients had a mean (SD) age of 62.4 (13.5) years, 6.4% were female, and 93.6% were male, with a mean (SD) CHA2DS2-VASc (congestive heart failure, hypertension, age, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism, vascular disease, age, sex category) score of 1.9 (1.6). A total of 0.2% were American Indian or Alaska Native, 2.7% were Asian, 10.7% were Black, 4.6% were Latinx, 0.7% were Native Hawaiian or Other Pacific Islander, 62.4% were White, 0.4% were of other race or ethnicity (which is not broken down into subcategories in the VA data set), and 18.4% were of unknown race or ethnicity. At the non-VA academic medical center (72 483 ECGs), the mean (SD) age was 59.5 (15.4) years and 52.5% were female, with a mean (SD) CHA2DS2-VASc score of 1.6 (1.4). A total of 0.1% were American Indian or Alaska Native, 7.9% were Asian, 9.4% were Black, 2.9% were Latinx, 0.03% were Native Hawaiian or Other Pacific Islander, 74.8% were White, 0.1% were of other race or ethnicity, and 4.7% were of unknown race or ethnicity. A deep learning model predicted the presence of AF within 31 days of a sinus rhythm ECG on held-out test ECGs at VA sites with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI, 0.85-0.86), accuracy of 0.78 (95% CI, 0.77-0.78), and F1 score of 0.30 (95% CI, 0.30-0.31). At the non-VA site, AUROC was 0.93 (95% CI, 0.93-0.94); accuracy, 0.87 (95% CI, 0.86-0.88); and F1 score, 0.46 (95% CI, 0.44-0.48). The model was well calibrated, with a Brier score of 0.02 across all sites. Among individuals deemed high risk by deep learning, the number needed to screen to detect a positive case of AF was 2.47 individuals for a testing sensitivity of 25% and 11.48 for 75%. Model performance was similar in patients who were Black, female, or younger than 65 years or who had CHA2DS2-VASc scores of 2 or greater. Conclusions and Relevance: Deep learning of outpatient sinus rhythm ECGs predicted AF within 31 days in populations with diverse demographics and comorbidities. Similar models could be used in future AF screening efforts to reduce adverse complications associated with this disease.

Lung Cancer Screening Among U.S. Military Veterans by Health Status and Race and Ethnicity, 2017-2020: A Cross-Sectional Population-Based Study.

Introduction: Veterans are at high risk for lung cancer and are an important group for lung cancer screening. Previous research suggests that lung cancer screening may not be reaching healthier and/or non-White individuals, who stand to benefit most from lung cancer screening. We sought to test whether lung cancer screening is associated with poor health and/or race and ethnicity among veterans. Methods: This cross-sectional, population-based study included veterans eligible for lung cancer screening (aged 55-79 years, ≥30 pack-year smoking history, current smokers or quit within 15 years, no previous lung cancer) in the 2017-2020 Behavioral Risk Factor Surveillance System surveys. Exposures were (1) poor health, defined as fair/poor health status and difficulty walking or climbing stairs, aligning with eligibility criteria for a pivotal lung cancer screening trial, and (2) race/ethnicity. The outcome was a receipt of lung cancer screening. All variables were self-reported. Results: Of 3,376 lung cancer screening-eligible veterans representing an underlying population of 866,000 individuals, 20.3% (95% CI=17.3, 23.6) had poor health, and 13.7% (95% CI=10.6, 17.5) identified as non-White. Poor health was strongly associated with lung cancer screening (adjusted RR=1.64, 95% CI=1.06, 2.27); one third of veterans screened for lung cancer would not qualify for a pivotal lung cancer screening trial in terms of health. Marked racial disparities were observed among veterans: after adjustment, non-White veterans were 67% less likely to report lung cancer screening than White veterans (adjusted RR=0.33, 95% CI=0.11, 0.66). Conclusions: Lung cancer screening is correlated with poorer health and White race/ethnicity among veterans, which may undermine its population-level effectiveness. These results highlight the need to promote lung cancer screening, especially for healthier and/or non-White veterans, an important group of Americans for lung cancer screening.

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.

Perceptions of Safety of Daily Cannabis vs Tobacco Smoking and Secondhand Smoke Exposure, 2017-2021.

Importance: While rates of cigarette use are declining, more US adults are using cannabis. Perceptions of safety are important drivers of substance use and public policy; however, little is known about the comparative views of US adults on tobacco and cannabis safety. Objective: To compare public perceptions of safety of cannabis vs tobacco smoke and evaluate how perceptions may be changing over time. Design, Setting, and Participants: This longitudinal survey study was conducted using a web-based survey administered in 2017, 2020, and 2021. US adults participating in Ipsos KnowledgePanel, a nationally representative, population-based survey panel, were included. Data were analyzed from March 2021 through June 2023. Main Outcomes and Measures: Two questions directly compared the perception of safety of cannabis vs tobacco in terms of daily smoking and secondhand smoke exposure. Additional questions assessed perceptions of safety of secondhand tobacco smoke for adults, children, and pregnant women, with an analogous set of questions for secondhand cannabis smoke. Results: A total of 5035 participants (mean [SD] age, 53.4 [16.2] years; 2551 males [50.7%]) completed all 3 surveys and provided responses for tobacco and cannabis risk questions. More than one-third of participants felt that daily smoking of cannabis was safer than tobacco, and their views increasingly favored safety of cannabis vs tobacco over time (1742 participants [36.7%] in 2017 vs 2107 participants [44.3%] in 2021; P < .001). The pattern was similar for secondhand cannabis smoke, with 1668 participants (35.1%) responding that cannabis was safer than tobacco in 2017 vs 1908 participants (40.2%) in 2021 (P < .001). Participants who were younger (adjusted odds ratio [aOR] for ages 18-29 years vs ≥60 years, 1.4 [95% CI, 1.1-1.8]; P = .01) or not married (aOR, 1.2 [95% CI, 1.0-1.4]; P = .01) were more likely to move toward safer views of cannabis use over time, while those who were retired (aOR vs working, 0.8 [95% CI, 0.7-0.9]; P = .01) were less likely to move toward a safer view of cannabis. Participants were also more likely to rate secondhand smoke exposure to cannabis vs tobacco as completely or somewhat safe in adults (629 participants [12.6%] vs. 119 participants [2.4%]; P < .001), children (238 participants [4.8%] vs. 90 participants [1.8%]; P < .001), and pregnant women (264 participants [5.3%] vs. 69 participants [1.4%]; P < .001). Conclusions and Relevance: This study found that US adults increasingly perceived daily smoking and secondhand exposure to cannabis smoke as safer than tobacco smoke from 2017 to 2021. Given that these views do not reflect the existing science on cannabis and tobacco smoke, the findings may have important implications for public health and policy as the legalization and use of cannabis increase.

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.

Comparative mRNA booster effectiveness against death or hospitalization with COVID-19 pneumonia across at-risk US Veteran populations.

Studies of comparative mRNA booster effectiveness among high-risk populations can inform mRNA booster-specific guidelines. The study emulated a target trial of COVID-19 vaccinated U.S. Veterans who received three doses of either mRNA-1273 or BNT162b2 vaccines. Participants were followed for up to 32 weeks between July 1, 2021 to May 30, 2022. Non-overlapping populations were average and high risk; high-risk sub-groups were age ≥65 years, high-risk co-morbid conditions, and immunocompromising conditions. Of 1,703,189 participants, 10.9 per 10,000 persons died or were hospitalized with COVID-19 pneumonia over 32 weeks (95% CI: 10.2, 11.8). Although relative risks of death or hospitalization with COVID-19 pneumonia were similar across at-risk groups, absolute risk varied when comparing three doses of BNT162b2 with mRNA-1273 (BNT162b2 minus mRNA-1273) between average-risk and high-risk populations, confirmed by the presence of additive interaction. The risk difference of death or hospitalization with COVID-19 pneumonia for high-risk populations was 2.2 (0.9, 3.6). Effects were not modified by predominant viral variant. In this work, the risk of death or hospitalization with COVID-19 pneumonia over 32 weeks was lower among high-risk populations who received three doses of mRNA-1273 vaccine instead of BNT162b2 vaccine; no difference was found among the average-risk population and age >65 sub-group.

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.

A national population-based study of cannabis use and correlates among U.S. veterans prescribed opioids in primary care.

BACKGROUND: Cannabis is marketed as a treatment for pain. There is limited data on the prevalence of cannabis use and its correlates among Veterans prescribed opioids. OBJECTIVE: To examine the prevalence and correlates of cannabis use among Veterans prescribed opioids. DESIGN: Cross-sectional study. PARTICIPANTS: Veterans with a urine drug test (UDT) from Primary Care 2014-2018, in 50 states, Washington, D.C., and Puerto Rico. A total of 1,182,779 patients were identified with an opioid prescription within 90 days prior to UDT. MAIN MEASURES: Annual prevalence of cannabis positive UDT by state. We used multivariable logistic regression to assess associations of demographic factors, mental health conditions, substance use disorders, and pain diagnoses with cannabis positive UDT. RESULTS: Annual prevalence of cannabis positive UDT ranged from 8.5% to 9.7% during the study period, and in 2018 was 18.15% in Washington, D.C. and 10 states with legalized medical and recreational cannabis, 6.1% in Puerto Rico and 25 states with legalized medical cannabis, and 4.5% in non-legal states. Younger age, male sex, being unmarried, and marginal housing were associated with use (p < 0.001). Post-traumatic stress disorder (adjusted odds ratio [AOR] 1.17; 95% confidence interval [CI] 1.13-1.22, p < 0.001), opioid use disorder (AOR 1.14; CI 1.07-1.22, p < 0.001), alcohol use disorder or positive AUDIT-C (AOR 1.34; 95% CI 1.28-1.39, p < 0.001), smoking (AOR 2.58; 95% CI 2.49-2.66, p < 0.001), and other drug use disorders (AOR 1.15; 95% CI 1.03-1.29, p = 0.02) were associated with cannabis use. Positive UDT for amphetamines AOR 1.41; 95% CI 1.26-1.58, p < 0.001), benzodiazepines (AOR 1.41; 95% CI 1.31-1.51, p < 0.001) and cocaine (AOR 2.04; 95% CI 1.75-2.36, p < 0.001) were associated with cannabis positive UDT. CONCLUSIONS: Cannabis use among Veterans prescribed opioids varied by state and by legalization status. Veterans with PTSD and substance use disorders were more likely to have cannabis positive UDT. Opioid-prescribed Veterans using cannabis may benefit from screening for these conditions, referral to treatment, and attention to opioid safety.

Assessment of a multi-center tele-urgent care program to decrease emergency department referral rates in the Veterans Health Administration.

The use of emergency departments for non-emergent issues has led to overcrowding and decreased the quality of care. Telemedicine may be a mechanism to decrease overutilization of this expensive resource. From April to September 2020, we assessed (a) the impact of a multi-center tele-urgent care program on emergency department referral rates and (b) the proportion of individuals who had a subsequent emergency department visit within 72 h of tele-urgent care evaluation when they were not referred to the emergency department. We then performed a chart review to assess whether patients presented to the emergency department for the same reason as was stated for their tele-urgent care evaluation, whether subsequent hospitalization was needed during that emergency department visit, and whether death occurred. Among the 2510 patients who would have been referred to in-person emergency department care, but instead received tele-urgent care assessment, one in five (21%; n = 533) were subsequently referred to the emergency department. Among those not referred following tele-urgent care, 1 in 10 (11%; n = 162) visited the emergency department within 72 h. Among these 162 individuals, most (91%) returned with the same or similar complaint as what was assessed during their tele-urgent care visit, with one in five requiring hospitalization (19%, n = 31) with one individual (0.01%) dying. In conclusion, tele-urgent care may safely decrease emergency department utilization.

Cost-Related Access Barriers, Medical Debt, and Dissatisfaction with Care Among Privately Insured Americans.

BACKGROUND: Understanding experiences with private important to improving the quality of health care coverage. OBJECTIVE: To examine the association of health with cost-related access barriers, medical debt, and dissatisfaction with care among privately insured Americans. DESIGN: We classified Americans with private insurance by self-reported health status into five groups (excellent, very good, good, fair, and poor health). We examined self-reported difficulty seeing a doctor due to costs, not taking medications due to costs, medical debt, and dissatisfaction with care among individuals with differing health status. We used logistic regression to examine the association of health status with individuals' experiences after accounting for baseline characteristics. The analysis was repeated among individuals with different forms of private insurance. Odds ratios were converted to risk ratios to improve ease of interpretation of the results. SETTING: Behavioral Risk Factor Surveillance System of Americans in 17 states RESULTS: The sample included 82,494 US adults with private insurance. Following adjustment, compared to individuals with excellent health those in very good health, good health, fair health, and poor health reported increasingly higher risks of difficulty seeing a doctor due to costs with risk ratios of 1.02 (95% CI 1.01, 1.03), 1.07 (95% CI 1.06, 1.08), 1.18 (95% CI 1.17, 1.20), and 1.29 (95% CI 1.27, 1.31), respectively. Compared to individuals with excellent health, those in very good health, good health, fair health, and poor health reported increasingly higher risks of not taking medication due to costs, outstanding medical debt, and dissatisfaction with care. Similar relationships were seen across individually purchased and employer-sponsored insurance. CONCLUSION: Cost-related access barriers, medical debt, and dissatisfaction with care were common among individuals with private insurance and most pronounced among those with fair and poor health who likely need and use their health insurance the most.

Association of a Positive Drug Screening for Cannabis With Mortality and Hospital Visits Among Veterans Affairs Enrollees Prescribed Opioids.

Importance: Cannabis has been proposed as a therapeutic with potential opioid-sparing properties in chronic pain, and its use could theoretically be associated with decreased amounts of opioids used and decreased risk of mortality among individuals prescribed opioids. Objective: To examine the risks associated with cannabis use among adults prescribed opioid analgesic medications. Design, Setting, and Participants: This cohort study was conducted among individuals aged 18 years and older who had urine drug screening in 2014 to 2019 and received any prescription opioid in the prior 90 days or long-term opioid therapy (LTOT), defined as more than 84 days of the prior 90 days, through the Veterans Affairs health system. Data were analyzed from November 2020 through March 2022. Exposures: Biologically verified cannabis use from a urine drug screen. Main Outcomes and Measures: The main outcomes were 90-day and 180-day all-cause mortality. A composite outcome of all-cause emergency department (ED) visits, all-cause hospitalization, or all-cause mortality was a secondary outcome. Weights based on the propensity score were used to reduce confounding, and hazard ratios [HRs] were estimated using Cox proportional hazards regression models. Analyses were conducted among the overall sample of patients who received any prescription opioid in the prior 90 days and were repeated among those who received LTOT. Analyses were repeated among adults aged 65 years and older. Results: Among 297 620 adults treated with opioids, 30 514 individuals used cannabis (mean [SE] age, 57.8 [10.5] years; 28 784 [94.3%] men) and 267 106 adults did not (mean [SE] age, 62.3 [12.3] years; P < .001; 247 684 [92.7%] men; P < .001). Among all patients, cannabis use was not associated with increased all-cause mortality at 90 days (HR, 1.07; 95% CI, 0.92-1.22) or 180 days (HR, 1.00; 95% CI, 0.90-1.10) but was associated with an increased hazard of the composite outcome at 90 days (HR, 1.05; 95% CI, 1.01-1.07) and 180 days (HR, 1.04; 95% CI, 1.01-1.06). Among 181 096 adults receiving LTOT, cannabis use was not associated with increased risk of all-cause mortality at 90 or 180 days but was associated with an increased hazard of the composite outcome at 90 days (HR, 1.05; 95% CI, 1.02-1.09) and 180 days (HR, 1.05; 95% CI, 1.02-1.09). Among 77 791 adults aged 65 years and older receiving LTOT, cannabis use was associated with increased 90-day mortality (HR, 1.55; 95% CI, 1.17-2.04). Conclusions and Relevance: This study found that cannabis use among adults receiving opioid analgesic medications was not associated with any change in mortality risk but was associated with a small increased risk of adverse outcomes and that short-term risks were higher among older adults receiving LTOT.