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BackgroundSubstance use disorders (SUD) elevate the risk for COVID-19 hospitalization, but studies are inconsistent on the relationship of SUD to COVID-19 mortality.MethodsVeterans 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).ResultsAmong 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.ConclusionsIn 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.

BackgroundSubstance use disorders (SUD) elevate the risk for COVID-19 hospitalization, but studies are inconsistent on the relationship of SUD to COVID-19 mortality.MethodsVeterans 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).ResultsAmong 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.ConclusionsIn 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.

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

Background:People with a psychiatric diagnosis smoke at high rates, yet are rarely treated for tobacco use. Health care systems often use a 'no treatment' default for tobacco, such that providers must actively choose (opt-in) to treat their patients who express interest in quitting. Default bias theory suggests that opt-in systems may reinforce the status quo to not treat tobacco use in psychiatry. We aim to conduct a pilot study testing an opt-out system for implementing a 3A's (ask, advise, assist) tobacco treatment model in outpatient psychiatry. Methods:We will use a mixed-methods, cluster-randomized study design. We will implement a tobacco use clinical reminder for outpatient psychiatrists at the VA New York Harbor Healthcare System. Psychiatrists (N = 20) will be randomized 1:1 to one of two groups: (1) Opt-In Treatment Approach: Psychiatrists will receive a reminder that encourages them to offer cessation medications and referral to cessation counseling; or (2) Opt-Out Treatment Approach: Psychiatrists will receive a clinical reminder that includes a standing cessation medication order and a referral to cessation counseling that will automatically generate unless the provider cancels. Prior to implementation of the reminders, we will hold a 1-hour training on tobacco treatment for psychiatrists in both arms. We will use VA administrative data to calculate the study's primary outcomes: 1) the percent of smokers prescribed a cessation medication and 2) the percent of smokers referred to counseling. During the intervention period, we will also conduct post-visit surveys with a cluster sample of 400 patients (20 per psychiatrist) to assess psychiatrist fidelity to the 3 A's approach and patient perceptions of the opt-out system. At six months, we will survey the clustered patient sample again to evaluate the study's secondary outcomes: 1) patient use of cessation treatment in the prior 6 months and 2) self-reported 7-day abstinence at 6 months. At the end of the

Background:People with a psychiatric diagnosis smoke at high rates, yet are rarely treated for tobacco use. Health care systems often use a 'no treatment' default for tobacco, such that providers must actively choose (opt-in) to treat their patients who express interest in quitting. Default bias theory suggests that opt-in systems may reinforce the status quo to not treat tobacco use in psychiatry. We aim to conduct a pilot study testing an opt-out system for implementing a 3A's (ask, advise, assist) tobacco treatment model in outpatient psychiatry. Methods:We will use a mixed-methods, cluster-randomized study design. We will implement a tobacco use clinical reminder for outpatient psychiatrists at the VA New York Harbor Healthcare System. Psychiatrists (N = 20) will be randomized 1:1 to one of two groups: (1) Opt-In Treatment Approach: Psychiatrists will receive a reminder that encourages them to offer cessation medications and referral to cessation counseling; or (2) Opt-Out Treatment Approach: Psychiatrists will receive a clinical reminder that includes a standing cessation medication order and a referral to cessation counseling that will automatically generate unless the provider cancels. Prior to implementation of the reminders, we will hold a 1-hour training on tobacco treatment for psychiatrists in both arms. We will use VA administrative data to calculate the study's primary outcomes: 1) the percent of smokers prescribed a cessation medication and 2) the percent of smokers referred to counseling. During the intervention period, we will also conduct post-visit surveys with a cluster sample of 400 patients (20 per psychiatrist) to assess psychiatrist fidelity to the 3 A's approach and patient perceptions of the opt-out system. At six months, we will survey the clustered patient sample again to evaluate the study's secondary outcomes: 1) patient use of cessation treatment in the prior 6 months and 2) self-reported 7-day abstinence at 6 months. At the end of the

People with a psychiatric diagnosis smoke at high rates, yet are rarely treated for tobacco use. Health care systems often use a 'no treatment' default for tobacco, such that providers must actively choose (opt-in) to treat their patients who express interest in quitting. Default bias theory suggests that opt-in systems may reinforce the status quo to not treat tobacco use in psychiatry. We aim to conduct a pilot study testing an opt-out system for implementing a 3A's (ask, advise, assist) tobacco treatment model in outpatient psychiatry. We will use a mixed-methods, cluster-randomized study design. We will implement a tobacco use clinical reminder for outpatient psychiatrists at the VA New York Harbor Healthcare System. Psychiatrists (N = 20) will be randomized 1:1 to one of two groups: (1) Opt-In Treatment Approach: Psychiatrists will receive a reminder that encourages them to offer cessation medications and referral to cessation counseling; or (2) Opt-Out Treatment Approach: Psychiatrists will receive a clinical reminder that includes a standing cessation medication order and a referral to cessation counseling that will automatically generate unless the provider cancels. Prior to implementation of the reminders, we will hold a 1-hour training on tobacco treatment for psychiatrists in both arms. We will use VA administrative data to calculate the study's primary outcomes: 1) the percent of smokers prescribed a cessation medication and 2) the percent of smokers referred to counseling. During the intervention period, we will also conduct post-visit surveys with a cluster sample of 400 patients (20 per psychiatrist) to assess psychiatrist fidelity to the 3 A's approach and patient perceptions of the opt-out system. At six months, we will survey the clustered patient sample again to evaluate the study's secondary outcomes: 1) patient use of cessation treatment in the prior 6 months and 2) self-reported 7-day abstinence at 6 months. At the end of the intervention perio

Adults with medical multimorbidity (≥2 chronic conditions) present challenges for health care systems to provide coordinated care. Substance use can complicate the management of chronic medical conditions, but little research has focused on the intersection of medical multimorbidity and substance use. This study uses cross-sectional analysis of 115,335 adult respondents of the 2012-2014 administrations of the National Survey on Drug Use and Health to estimate the prevalence and correlates of past-year drug use among adults with multimorbidity. The prevalence of past-year drug use was compared between individuals reporting 0, 1, and ≥2 chronic medical conditions. We used multivariable logistic regression to determine correlates of past-year drug use among adults with ≥2 chronic medical conditions. 53.1% reported no chronic conditions, 29.5% reported one chronic condition, and 17.4% reported ≥2 chronic conditions. Past-year drug use was reported by 18.3% of those with no chronic conditions, 14.8% with 1 chronic condition, and 11.6% with ≥2 chronic conditions. Cannabis and opioid analgesics (nonmedical use) were the most common drugs used across all three groups. In the adjusted model, among adults with medical multimorbidity, adults with past-year drug use were more likely to be younger, male, have lower income, and report current tobacco use, alcohol dependence, past-year depression, and having received mental health treatment in the past year. In this national cohort, fewer adults with multimorbidity reported substance use compared to adults with no or one chronic condition, however, this population with high multimorbidity may be particularly vulnerable to the negative effects of drug use.

BackgroundSmoking is the leading preventable cause of death in the United States, but evidence-based smoking cessation therapy is underutilized. Financial incentive strategies represent an innovative approach for increasing the use of counseling and pharmacotherapy. If effective, they could supplement or supplant resource-intensive policy options, particularly in populations for whom smoking has substantial societal costs. FIESTA (Financial IncEntives for Smoking TreAtment) will randomize hospitalized smokers to receive usual smoking cessation care alone or usual smoking care augmented with financial incentives. We aim to compare the impact of these two strategies on 1) smoking abstinence, 2) use of counseling and nicotine replacement therapy, and 3) quality of life of participants. We also will evaluate the short-term and long-term return on the investment of incentives. The FIESTA Oral Microbiome Substudy will compare the oral microbiome of smokers and nonsmokers to longitudinally assess whether smoking cessation changes oral microbiome composition.MethodsWe will enroll 182 inpatient participants from the Manhattan campus of the Veterans Affairs New York Harbor Healthcare System. All participants receive enhanced usual care, including screening for tobacco use, counseling while hospitalized, access to nicotine replacement therapy, and referral to a state Quitline. Patients in the financial incentive arm receive enhanced usual care and up to $550 for participating in the New York Smoker's Quitline, using nicotine replacement therapy (NRT), and achieving biochemically confirmed smoking cessation at 2 months and 6 months. In the microbiome substudy, we enroll nonsmoking control participants matched to each recruited smoker's hospital ward, sex, age, diabetes status, and antibiotic use. After discharge, participants are asked to complete periodic phone interviews at 2 weeks, 2 months, 6 months, and 12 months and provide expired carbon monoxide and saliva samples at 2

Adults with medical multimorbidity (≥2 chronic conditions) present challenges for health care systems to provide coordinated care. Substance use can complicate the management of chronic medical conditions, but little research has focused on the intersection of medical multimorbidity and substance use. This study uses cross-sectional analysis of 115,335 adult respondents of the 2012-2014 administrations of the National Survey on Drug Use and Health to estimate the prevalence and correlates of past-year drug use among adults with multimorbidity. The prevalence of past-year drug use was compared between individuals reporting 0, 1, and ≥2 chronic medical conditions. We used multivariable logistic regression to determine correlates of past-year drug use among adults with ≥2 chronic medical conditions. 53.1% reported no chronic conditions, 29.5% reported one chronic condition, and 17.4% reported ≥2 chronic conditions. Past-year drug use was reported by 18.3% of those with no chronic conditions, 14.8% with 1 chronic condition, and 11.6% with ≥2 chronic conditions. Cannabis and opioid analgesics (nonmedical use) were the most common drugs used across all three groups. In the adjusted model, among adults with medical multimorbidity, adults with past-year drug use were more likely to be younger, male, have lower income, and report current tobacco use, alcohol dependence, past-year depression, and having received mental health treatment in the past year. In this national cohort, fewer adults with multimorbidity reported substance use compared to adults with no or one chronic condition, however, this population with high multimorbidity may be particularly vulnerable to the negative effects of drug use.

BackgroundSmoking is the leading preventable cause of death in the United States, but evidence-based smoking cessation therapy is underutilized. Financial incentive strategies represent an innovative approach for increasing the use of counseling and pharmacotherapy. If effective, they could supplement or supplant resource-intensive policy options, particularly in populations for whom smoking has substantial societal costs. FIESTA (Financial IncEntives for Smoking TreAtment) will randomize hospitalized smokers to receive usual smoking cessation care alone or usual smoking care augmented with financial incentives. We aim to compare the impact of these two strategies on 1) smoking abstinence, 2) use of counseling and nicotine replacement therapy, and 3) quality of life of participants. We also will evaluate the short-term and long-term return on the investment of incentives. The FIESTA Oral Microbiome Substudy will compare the oral microbiome of smokers and nonsmokers to longitudinally assess whether smoking cessation changes oral microbiome composition.MethodsWe will enroll 182 inpatient participants from the Manhattan campus of the Veterans Affairs New York Harbor Healthcare System. All participants receive enhanced usual care, including screening for tobacco use, counseling while hospitalized, access to nicotine replacement therapy, and referral to a state Quitline. Patients in the financial incentive arm receive enhanced usual care and up to $550 for participating in the New York Smoker's Quitline, using nicotine replacement therapy (NRT), and achieving biochemically confirmed smoking cessation at 2 months and 6 months. In the microbiome substudy, we enroll nonsmoking control participants matched to each recruited smoker's hospital ward, sex, age, diabetes status, and antibiotic use. After discharge, participants are asked to complete periodic phone interviews at 2 weeks, 2 months, 6 months, and 12 months and provide expired carbon mon

AimsTo estimate the prevalence and predictors of failed biochemical verification of self-reported abstinence among participants enrolled in trials of hospital-initiated smoking cessation interventions.DesignComparison of characteristics between participants who verified and those who failed to verify self-reported abstinence.SettingsMulti-site randomized clinical trials conducted between 2010 and 2014 in hospitals throughout the United States.ParticipantsRecently hospitalized smokers who reported tobacco abstinence 6 months post-randomization and provided a saliva sample for verification purposes (n = 822).MeasurementsOutcomes were salivary cotinine-verified smoking abstinence at 10 and 15 ng/ml cut-points. Predictors and correlates included participant demographics and tobacco use; hospital diagnoses and treatment; and study characteristics collected via surveys and electronic medical records.FindingsUsable samples were returned by 69.8% of the 1178 eligible trial participants who reported 7-day point prevalence abstinence. The proportion of participants verified as quit was 57.8% [95% confidence interval (CI) = 54.4, 61.2; 10 ng/ml cut-off] or 60.6% (95% CI = 57.2, 63.9; 15 ng/ml). Factors associated independently with verification at 10 ng/ml were education beyond high school education [odds ratio (OR) = 1.51; 95% CI = 1.07, 2.11], continuous abstinence since hospitalization (OR = 2.82; 95% CI = 2.02, 3.94), mailed versus in-person sample (OR = 3.20; 95% CI = 1.96, 5.21) and race. African American participants were less likely to verify abstinence than white participants (OR = 0.64; 95% CI = 0.44, 0.93). Findings were similar for verification at 15 ng/ml. Verification rates did not differ by treatment group.ConclusionsIn the United States, high rates (40%) of recently hospitalized smokers enrolled in smoking cessation trials fail biochemical verification of their self-reported abstinence.

AimsTo estimate the prevalence and predictors of failed biochemical verification of self-reported abstinence among participants enrolled in trials of hospital-initiated smoking cessation interventions.DesignComparison of characteristics between participants who verified and those who failed to verify self-reported abstinence.SettingsMulti-site randomized clinical trials conducted between 2010 and 2014 in hospitals throughout the United States.ParticipantsRecently hospitalized smokers who reported tobacco abstinence 6 months post-randomization and provided a saliva sample for verification purposes (n = 822).MeasurementsOutcomes were salivary cotinine-verified smoking abstinence at 10 and 15 ng/ml cut-points. Predictors and correlates included participant demographics and tobacco use; hospital diagnoses and treatment; and study characteristics collected via surveys and electronic medical records.FindingsUsable samples were returned by 69.8% of the 1178 eligible trial participants who reported 7-day point prevalence abstinence. The proportion of participants verified as quit was 57.8% [95% confidence interval (CI) = 54.4, 61.2; 10 ng/ml cut-off] or 60.6% (95% CI = 57.2, 63.9; 15 ng/ml). Factors associated independently with verification at 10 ng/ml were education beyond high school education [odds ratio (OR) = 1.51; 95% CI = 1.07, 2.11], continuous abstinence since hospitalization (OR = 2.82; 95% CI = 2.02, 3.94), mailed versus in-person sample (OR = 3.20; 95% CI = 1.96, 5.21) and race. African American participants were less likely to verify abstinence than white participants (OR = 0.64; 95% CI = 0.44, 0.93). Findings were similar for verification at 15 ng/ml. Verification rates did not differ by treatment group.ConclusionsIn the United States, high rates (40%) of recently hospitalized smokers enrolled in smoking cessation tr