Cost and Cost Savings of Navigation Services to Avoid Rehospitalization for a Comorbid Substance Use Disorder Population.

BACKGROUND: A randomized clinical trial found that patient navigation for hospital patients with comorbid substance use disorders (SUDs) reduced emergency department (ED) and inpatient hospital utilization compared with treatment-as-usual. OBJECTIVE: To compare the cost and calculate any cost savings from the Navigation Services to Avoid Rehospitalization (NavSTAR) intervention over treatment-as-usual. RESEARCH DESIGN: This study calculates activity-based costs from the health care providers and uses a net benefits approach to calculate the cost savings generated from NavSTAR. NavSTAR provided patient navigation focused on engagement in SUD treatment, starting before hospital discharge and continuing for up to 3 months postdischarge. SUBJECTS: Adult hospitalized medical/surgical patients with comorbid SUD for opioids, cocaine, and/or alcohol. COST MEASURES: Cost of the 3-month NavSTAR patient navigation intervention and the cost of all inpatient days and ED visits over a 12-month period. RESULTS OF BASE CASE ANALYSIS: NavSTAR generated $17,780 per participant in cost savings. Ninety-seven percent of bootstrapped samples generated positive cost savings, and our sensitivity analyses did not change our results. LIMITATIONS: Participants were recruited at one hospital in Baltimore, MD through the hospital's addiction consultation service. Findings may not generalize to the broader population. Outpatient health care cost data was not available through administrative records. CONCLUSION: Our findings show that patient navigation interventions should be considered by payors and policy makers to reduce the high hospital costs associated with comorbid SUD patients.

Cost and Cost-Effectiveness of Incentives for Viral Suppression in People Living with HIV.

Only 63% of people living with HIV in the United States are achieving viral suppression. Structural and social barriers limit adherence to antiretroviral therapy which furthers the HIV epidemic while increasing health care costs. This study calculated the cost and cost-effectiveness of a contingency management intervention with cash incentives. People with HIV and detectable viral loads were randomized to usual care or an incentive group. Individuals could earn up to $3650 per year if they achieved and maintained an undetectable viral load. The average 1-year intervention cost, including incentives, was $4105 per patient. The average health care costs were $27,189 per patient in usual care and $35,853 per patient in the incentive group. We estimated a cost of $28,888 per quality-adjusted life-year (QALY) gained, which is well below accepted cost-per-QALY thresholds. Contingency management with cash incentives is a cost-effective intervention for significantly increasing viral suppression.

Stability of Drinking Reductions and Long-term Functioning Among Patients with Alcohol Use Disorder.

BACKGROUND: The World Health Organization (WHO) categorizes alcohol consumption according to grams consumed into low-, medium-, high-, and very-high-risk drinking levels (RDLs). Although abstinence has been considered the ideal outcome of alcohol treatment, reductions in WHO RDLs have been proposed as primary outcomes for alcohol use disorder (AUD) trials. OBJECTIVE: The current study examines the stability of WHO RDL reductions and the association between RDL reductions and long-term functioning for up to 3 years following treatment. DESIGN AND PARTICIPANTS: Secondary data analysis of patients with AUD enrolled in the COMBINE Study and Project MATCH, two multi-site, randomized AUD clinical trials, who were followed for up to 3 years post-treatment (COMBINE: n = 694; MATCH: n = 806). MEASURES: Alcohol use was measured via calendar-based methods. We estimated all models in the total sample and among participants who did not achieve abstinence during treatment. KEY RESULTS: One-level RDL reductions were achieved by 84% of patients at the end of treatment, with 84.9% of those individuals maintaining that reduction at a 3-year follow-up. Two-level RDL reductions were achieved by 68% of patients at the end of treatment, with 77.7% of those individuals maintaining that reduction at a 3-year follow-up. One- and two-level RDL reductions at the end of treatment were associated with significantly better mental health, quality of life (including physical quality of life), and fewer drinking consequences 3 years after treatment (p < 0.05), as compared to no change or increased drinking. CONCLUSION: AUD patients can maintain WHO RDL reductions for up to 3 years after treatment. Patients who had WHO RDL reductions functioned significantly better than those who did not reduce their drinking. These findings are consistent with prior reports suggesting that drinking reductions, short of abstinence, yield meaningful improvements in patient health, well-being, and functioning.

Can Alcohol Use Disorder Recovery Include Some Heavy Drinking? A Replication and Extension up to 9 Years Following Treatment.

BACKGROUND: Recent research indicates some individuals who engage in heavy drinking following treatment for alcohol use disorder fare as well as those who abstain with respect to psychosocial functioning, employment, life satisfaction, and mental health. The current study evaluated whether these findings replicated in an independent sample and examined associations between recovery profiles and functioning up to 6 years later. METHODS: Data were from the 3-year and 7- to 9-year follow-ups of subsamples initially recruited for the COMBINE study (3-year follow-up: n = 694; 30.1% female, 21.0% non-White; 7- to 9-year follow-up: n = 127; 38.9% female, 27.8% non-White). Recovery at 3 years was defined by latent profile analyses including measures of health functioning, quality of life, employment, alcohol consumption, and cannabis and other drug use. Functioning at the 7- to 9-year follow-up was assessed using single items of self-rated general health, hospitalizations, and alcohol consumption. RESULTS: We identified 4 profiles at the 3-year follow-up: (i) low-functioning frequent heavy drinkers (13.9%), (ii) low-functioning infrequent heavy drinkers (15.8%), (iii) high-functioning heavy drinkers (19.4%), and (iv) high-functioning infrequent drinkers (50.9%). At the 7- to 9-year follow-up, the 2 high-functioning profiles had the best self-rated health, and the high-functioning heavy drinking profile had significantly fewer hospitalizations than the low-functioning frequent heavy drinking profile. CONCLUSIONS: Previous findings showing heterogeneity in recovery outcomes were replicated. Most treatment recipients functioned well for years after treatment, and a subset who achieved stable recovery engaged in heavy drinking and reported good health outcomes up to 9 years after treatment. Results question the long-standing emphasis on drinking practices as a primary outcome, as well as abstinence as a recovery criterion in epidemiologic and treatment outcome research and among stakeholder groups and funding/regulatory agencies. Findings support an expanded recovery research agenda that considers drinking patterns, health, life satisfaction, and functioning.

Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California.

BACKGROUND: Twitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks. OBJECTIVES: This study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California. METHODS: From a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities. RESULTS: The modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles. CONCLUSIONS: The most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time.

The Relationship Between End-of-Treatment Alcohol Use and Subsequent Healthcare Costs: Do Heavy Drinking Days Predict Higher Healthcare Costs?

BACKGROUND: A challenge for evaluating alcohol treatment efficacy is determining what constitutes a "good" outcome or meaningful improvement. Abstinence at the end of treatment is an unambiguously good outcome; however, a focus on abstinence ignores the potential benefits of patients reducing their drinking to less problematic levels. Patients may be drinking at low-risk levels at the end of treatment but may be high-functioning and impose few social costs. In this study, we estimate the relationship between drinking at the end of COMBINE treatment and subsequent healthcare costs with an emphasis on heavy and nonheavy drinking levels. METHODS: Indicators of heavy drinking days (HDDs; 5+ drinks for men, 4+ for women) and nonheavy drinking days (non-HDDs) during the last 30 days of COMBINE treatment were constructed for 748 patients enrolled in the COMBINE Economic Study. Generalized linear models were used to model total costs following COMBINE treatment as a function of drinking indicators. Different model specifications analyzed alternative counts of HDDs (e.g., 1 HDD and 2 to 30 HDDs), and groups having Both non-HDDs and HDDs. RESULTS: Patients with HDDs had 66.4% (p < 0.01) higher healthcare costs than those who were abstinent. Having more than 2 HDDs was associated with the highest costs (75.9%, p < 0.01). Patients with non-HDDs had costs that were not significantly different than abstainers, even if they also had HDDs. However, those with HDDs only had costs 91.7% higher than abstainers (p < 0.01). CONCLUSIONS: Having HDDs at the end of treatment is associated with higher costs. Patients who had Only HDDs at the end of treatment had worse subsequent outcomes than those who had Both non-HDDs and HDDs. These findings offer new context for evaluating treatment outcomes and provide new information on the association of drinking with consequences.

Association between self-reports of being high and perceptions about the safety of drugged and drunk driving.

This study examines the relationship between self-reports of being high on marijuana and perceptions about driving high or drunk. Data were collected in 2014 from an online convenience sample of adult, past 30-day marijuana and hashish users in Colorado and Washington (n = 865). Respondents were asked, "Were you high or feeling the effects of marijuana or hashish when you took this survey?" Logistic regression was used to assess the relationship between being high and beliefs about driving high, controlling for demographics and marijuana use. Respondents who reported being high at the time of survey administration had higher odds of agreeing with the statements, "I can safely drive under the influence of marijuana" (OR = 3.13, P < 0.001) and "I can safely drive under the influence of alcohol" (OR = 3.71, P < 0.001) compared with respondents who did not report being high. Respondents who were high also had higher odds of being open to driving high under certain circumstances. Being high may influence perceptions about the safety of drugged and drunk driving. The effectiveness of public health messages to prevent drugged and drunk driving may depend in part on how persuasive they are among individuals who are high.

The Impact of a Mandated Trauma Center Alcohol Intervention on Readmission and Cost per Readmission in Arizona.

BACKGROUND: Persons appearing in trauma centers have a higher prevalence of unhealthy alcohol use than the general population. Screening and brief intervention (SBI) is designed to moderate drinking levels and avoid costly future readmissions, but few studies have examined the impact of SBI on hospital readmissions and health care costs in a trauma population. RESEARCH DESIGN: This study uses comparative interrupted time-series and the Arizona State Inpatient Database to estimate the effect of the American College of Surgeons Committee on Trauma SBI mandate on the probability of readmission and cost per readmission in Arizona trauma centers. We compare individuals with and without an alcohol diagnosis code before and after the mandate was implemented. RESULTS: The mandate resulted in a 2.2 percentage point reduction (44%) in the probability of readmission. Total health care and readmission costs were not affected by the mandate. CONCLUSIONS: The estimates are consistent with a differential effect of SBI: SBI reduces readmissions among those who present with a less serious alcohol-related problem. Persons with more serious alcohol problems are less likely to respond to SBI. These higher risk individuals likely have a higher cost, which may explain the lack of change in readmission costs. Our study is a macrolevel intent-to-treat analysis of SBI's impact that corroborates the potential of SBI implied by efficacy studies in trauma centers and other settings. This study provides a framework for future research involving more states and health systems and evaluating other SBI policies.

Brief intervention for problem drug use in safety-net primary care settings: a randomized clinical trial.

IMPORTANCE: Although brief intervention is effective for reducing problem alcohol use, few data exist on its effectiveness for reducing problem drug use, a common issue in disadvantaged populations seeking care in safety-net medical settings (hospitals and community health clinics serving low-income patients with limited or no insurance). OBJECTIVE: To determine whether brief intervention improves drug use outcomes compared with enhanced care as usual. DESIGN, SETTING, AND PARTICIPANTS: A randomized clinical trial with blinded assessments at baseline and at 3, 6, 9, and 12 months conducted in 7 safety-net primary care clinics in Washington State. Of 1621 eligible patients reporting any problem drug use in the past 90 days, 868 consented and were randomized between April 2009 and September 2012. Follow-up participation was more than 87% at all points. INTERVENTIONS: Participants received a single brief intervention using motivational interviewing, a handout and list of substance abuse resources, and an attempted 10-minute telephone booster within 2 weeks (n = 435) or enhanced care as usual, which included a handout and list of substance abuse resources (n = 433). MAIN OUTCOMES AND MEASURES: The primary outcomes were self-reported days of problem drug use in the past 30 days and Addiction Severity Index-Lite (ASI) Drug Use composite score. Secondary outcomes were admission to substance abuse treatment; ASI composite scores for medical, psychiatric, social, and legal domains; emergency department and inpatient hospital admissions, arrests, mortality, and human immunodeficiency virus risk behavior. RESULTS: Mean days used of the most common problem drug at baseline were 14.40 (SD, 11.29) (brief intervention) and 13.25 (SD, 10.69) (enhanced care as usual); at 3 months postintervention, means were 11.87 (SD, 12.13) (brief intervention) and 9.84 (SD, 10.64) (enhanced care as usual) and not significantly different (difference in differences, ß = 0.89 [95% CI, -0.49 to 2.26]). Mean ASI Drug Use composite score at baseline was 0.11 (SD, 0.10) (brief intervention) and 0.11 (SD, 0.10) (enhanced care as usual) and at 3 months was 0.10 (SD, 0.09) (brief intervention) and 0.09 (SD, 0.09) (enhanced care as usual) and not significantly different (difference in differences, ß = 0.008 [95% CI, -0.006 to 0.021]). During the 12 months following intervention, no significant treatment differences were found for either variable. No significant differences were found for secondary outcomes. CONCLUSIONS AND RELEVANCE: A one-time brief intervention with attempted telephone booster had no effect on drug use in patients seen in safety-net primary care settings. This finding suggests a need for caution in promoting widespread adoption of this intervention for drug use in primary care. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00877331.

Association of Arizona's Implementation of a Behavioral Health Crisis Response System With Suicide Hospitalizations.

OBJECTIVE: In July 2022, the 988 Suicide and Crisis Lifeline went live. The Lifeline is part of larger federal and state efforts to build comprehensive behavioral health crisis response systems that include mobile crisis units and crisis diversion and stabilization centers. Comprehensive response systems are anticipated to reduce hospitalizations for suicide and other behavioral health crises; however, research testing this assumption has been limited. The authors used Arizona-a state known for its comprehensive crisis system-to determine the association between state implementation of a comprehensive behavioral health crisis response system and suicide-related hospitalizations. METHODS: A comparative interrupted time-series (CITS) design was used to compare changes in suicide-related hospitalizations after the 2015 implementation of Arizona's crisis response system (N=215,063). Data were from the 2010-2019 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID). Nevada (N=84,091 hospitalizations) was used as a comparison state because it is a western state that had not yet implemented a comprehensive crisis system and had available HCUP SID data. The CITS model included controls for time-varying differences in state demographic composition. RESULTS: From 2010 to 2014 to 2019, annual suicide-related hospitalizations in Arizona increased from 122.0 to 324.2 to 584.5, respectively, per 100,000 people, and in Nevada, hospitalizations increased from 94.7 to 263.2 to 595.5, respectively, per 100,000 people. Arizona's crisis response system was associated with a significant relative decrease in the quarterly trend of 2.57 suicide-related hospitalizations per 100,000 people (p=0.033). CONCLUSIONS: More research is needed to understand how the implementation of a comprehensive crisis response system may affect suicide-related hospitalizations.

Establishing a Protocol for Determining the Costs of an Integrated Set of Evidence-based Practices Aimed at Reducing Opioid Overdose Deaths.

OBJECTIVES: In the midst of the opioid overdose crisis, local jurisdictions face a choice of public health interventions. A significant barrier when considering evidence-based practices (EBPs) is the lack of information regarding their implementation cost. This protocol paper provides the methodological foundation for the economic cost evaluations of community-wide strategies on the scale of a national study. It can serve as a resource for other communities, local policymakers, and stakeholders as they consider implementing possible public health strategies in their unique settings. METHODS: We present a protocol that details (1) the process of identifying, reviewing, and analyzing individual strategies for study-funded and non-study-funded costs; (2) prospective costing tool designation, and; (3) data collection. To do this, we set up working groups with community stakeholders, reviewed financial invoices, and surveyed individuals with detailed knowledge of their community implementation. DISCUSSION: There were 3 main challenges/limitations. The first was the lack of a standard structure for documenting nonfunded costs associated with each strategy. The second was the need for timely implementation of cost data. The third was generalizability because our study designed its strategies for selected communities due to their high opioid overdose mortality rates. Future steps include more tailored questions to ask during the categorization/filter process and establishing realistic expectations for organizations regarding documenting. CONCLUSIONS: Data collected will provide a critical methodological foundation for costing large community-based EBP strategies and provide clarity for stakeholders on the cost of implementing EBP strategies to reduce opioid overdose deaths.

Cost of start-up activities to implement a community-level opioid overdose reduction intervention in the HEALing Communities Study.

BACKGROUND: Communities That HEAL (CTH) is a novel, data-driven community-engaged intervention designed to reduce opioid overdose deaths by increasing community engagement, adoption of an integrated set of evidence-based practices, and delivering a communications campaign across healthcare, behavioral-health, criminal-legal, and other community-based settings. The implementation of such a complex initiative requires up-front investments of time and other expenditures (i.e., start-up costs). Despite the importance of these start-up costs in investment decisions to stakeholders, they are typically excluded from cost-effectiveness analyses. The objective of this study is to report a detailed analysis of CTH start-up costs pre-intervention implementation and to describe the relevance of these data for stakeholders to determine implementation feasibility. METHODS: This study is guided by the community perspective, reflecting the investments that a real-world community would need to incur to implement the CTH intervention. We adopted an activity-based costing approach, in which resources related to hiring, training, purchasing, and community dashboard creation were identified through macro- and micro-costing techniques from 34 communities with high rates of fatal opioid overdoses, across four states-Kentucky, Massachusetts, New York, and Ohio. Resources were identified and assigned a unit cost using administrative and semi-structured-interview data. All cost estimates were reported in 2019 dollars. RESULTS: State-level average and median start-up cost (representing 8-10 communities per state) were $268,657 and $175,683, respectively. Hiring and training represented 40%, equipment and infrastructure costs represented 24%, and dashboard creation represented 36% of the total average start-up cost. Comparatively, hiring and training represented 49%, purchasing costs represented 18%, and dashboard creation represented 34% of the total median start-up cost. CONCLUSION: We identified three distinct CTH hiring models that affected start-up costs: hospital-academic (Massachusetts), university-academic (Kentucky and Ohio), and community-leveraged (New York). Hiring, training, and purchasing start-up costs were lowest in New York due to existing local infrastructure. Community-based implementation similar to the New York model may have lower start-up costs due to leveraging of existing infrastructure, relationships, and support from local health departments.

Effect of the Communities that HEAL intervention on receipt of behavioral therapies for opioid use disorder: A cluster randomized wait-list controlled trial.

BACKGROUND: The U.S. opioid overdose crisis persists. Outpatient behavioral health services (BHS) are essential components of a comprehensive response to opioid use disorder and overdose fatalities. The Helping to End Addiction Long-Term® (HEALing) Communities Study developed the Communities That HEAL (CTH) intervention to reduce opioid overdose deaths in 67 communities in Kentucky, Ohio, New York, and Massachusetts through the implementation of evidence-based practices (EBPs), including BHS. This paper compares the rate of individuals receiving outpatient BHS in Wave 1 intervention communities (n = 34) to waitlisted Wave 2 communities (n = 33). METHODS: Medicaid data included individuals ≥18 years of age receiving any of five BHS categories: intensive outpatient, outpatient, case management, peer support, and case management or peer support. Negative binomial regression models estimated the rate of receiving each BHS for Wave 1 and Wave 2. Effect modification analyses evaluated changes in the effect of the CTH intervention between Wave 1 and Wave 2 by research site, rurality, age, sex, and race/ethnicity. RESULTS: No significant differences were detected between intervention and waitlisted communities in the rate of individuals receiving any of the five BHS categories. None of the interaction effects used to test the effect modification were significant. CONCLUSIONS: Several factors should be considered when interpreting results-no significant intervention effects were observed through Medicaid claims data, the best available data source but limited in terms of capturing individuals reached by the intervention. Also, the 12-month evaluation window may have been too brief to see improved outcomes considering the time required to stand-up BHS. TRIAL REGISTRATION: Clinical Trials.gov http://www. CLINICALTRIALS: gov: Identifier: NCT04111939.

Impact of the Communities That HEAL Intervention on Buprenorphine-Waivered Practitioners and Buprenorphine Prescribing: A Prespecified Secondary Analysis of the HCS Randomized Clinical Trial.

Importance: Buprenorphine significantly reduces opioid-related overdose mortality. From 2002 to 2022, the Drug Addiction Treatment Act of 2000 (DATA 2000) required qualified practitioners to receive a waiver from the Drug Enforcement Agency to prescribe buprenorphine for treatment of opioid use disorder. During this period, waiver uptake among practitioners was modest; subsequent changes need to be examined. Objective: To determine whether the Communities That HEAL (CTH) intervention increased the rate of practitioners with DATA 2000 waivers and buprenorphine prescribing. Design, Setting, and Participants: This prespecified secondary analysis of the HEALing Communities Study, a multisite, 2-arm, parallel, community-level, cluster randomized, open, wait-list-controlled comparison clinical trial was designed to assess the effectiveness of the CTH intervention and was conducted between January 1, 2020, to December 31, 2023, in 67 communities in Kentucky, Massachusetts, New York, and Ohio, accounting for approximately 8.2 million adults. The participants in this trial were communities consisting of counties (n = 48) and municipalities (n = 19). Trial arm randomization was conducted using a covariate constrained randomization procedure stratified by state. Each state was balanced by community characteristics including urban/rural classification, fatal opioid overdose rate, and community population. Thirty-four communities were randomized to the intervention and 33 to wait-list control arms. Data analysis was conducted between March 20 and September 29, 2023, with a focus on the comparison period from July 1, 2021, to June 30, 2022. Intervention: Waiver trainings and other educational trainings were offered or supported by the HEALing Communities Study research sites in each state to help build practitioner capacity. Main Outcomes and Measures: The rate of practitioners with a DATA 2000 waiver (overall, and stratified by 30-, 100-, and 275-patient limits) per 100 000 adult residents aged 18 years or older during July 1, 2021, to June 30, 2022, were compared between the intervention and wait-list control communities. The rate of buprenorphine prescribing among those waivered practitioners was also compared between the intervention and wait-list control communities. Intention-to-treat and per-protocol analyses were performed. Results: A total of 8 166 963 individuals aged 18 years or older were residents of the 67 communities studied. There was no evidence of an effect of the CTH intervention on the adjusted rate of practitioners with a DATA 2000 waiver (adjusted relative rate [ARR], 1.04; 95% CI, 0.94-1.14) or the adjusted rate of practitioners with a DATA 2000 waiver who actively prescribed buprenorphine (ARR, 0.97; 95% CI, 0.86-1.10). Conclusions and Relevance: In this randomized clinical trial, the CTH intervention was not associated with increases in the rate of practitioners with a DATA 2000 waiver or buprenorphine prescribing among those waivered practitioners. Supporting practitioners to prescribe buprenorphine remains a critical yet challenging step in the continuum of care to treat opioid use disorder. Trial Registration: ClinicalTrials.gov Identifier: NCT04111939.

Modeling the impact of COVID-19 pandemic-driven increases in alcohol consumption on health outcomes and hospitalization costs in the United States.

BACKGROUND AND AIMS: Alcohol consumption increased in the early phases of the COVID-19 pandemic in the United States. Alcohol use disorder (AUD) and risky drinking are linked to harmful health effects. This paper aimed to project future health and cost impacts of shifts in alcohol consumption during the COVID-19 pandemic. DESIGN: An individual-level simulation model of the long-term drinking patterns for people with life-time AUD was used to simulate 10 000 individuals and project model outcomes to the estimated 25.9 million current drinkers with life-time AUD in the United States. The model considered three scenarios: (1) no change (counterfactual for comparison); (2) increased drinking levels persist for 1 year ('increase-1') and (3) increased drinking levels persist for 5 years ('increase-5'). SETTING: United States. PARTICIPANTS: Current drinkers with life-time AUD. MEASUREMENTS: Life expectancy [life-years (LYs)], quality-adjusted life-years (QALYs), alcohol-related hospitalizations and associated hospitalization costs and alcohol-related deaths, during a 5-year period. FINDINGS: Short-term increases in alcohol consumption (increase-1 scenario) resulted in a loss of 79 000 [95% uncertainty interval (UI]) 26 000-201 000] LYs, a loss of 332 000 (104 000-604 000) QALYs and 295 000 (82 000-501 000) more alcohol-related hospitalizations, costing an additional $5.4 billion ($1.5-9.3 billion) over 5 years. Hospitalizations for cirrhosis of the liver accounted for approximately $3.0 billion ($0.9-4.8 billion) in hospitalization costs, more than half the increase across all alcohol-related conditions. Health and cost impacts were more pronounced for older age groups (51+), women and non-Hispanic black individuals. Increasing the duration of pandemic-driven increases in alcohol consumption in the increase-5 scenario resulted in larger impacts. CONCLUSIONS: Simulations show that if the increase in alcohol consumption observed in the United States in the first year of the pandemic continues, alcohol-related mortality, morbidity and associated costs will increase substantially over the next 5 years.

Cost and cost-effectiveness of abstinence contingent wage supplements.

BACKGROUND: Substance use disorders are correlated with unemployment and poverty. However, few interventions aim to improve substance use, unemployment, and, distally, poverty. The Abstinence-Contingent Wage Supplement (ACWS) randomized controlled trial combined a therapeutic workplace with abstinence-contingent wage supplements to address substance use and unemployment. The ACWS study found that abstinence-contingent wage supplements increased the percentage of participants who had negative drug tests, who were employed, and who were above the poverty line during the intervention period. This study presents the cost of ACWS and calculates the cost-effectiveness of ACWS compared with usual care. METHODS: To calculate the cost and cost-effectiveness of ACWS, we used activity-based costing methods to cost the intervention and calculated the costs from the provider and healthcare sector perspective. We calculated incremental cost-effectiveness ratios and cost-effectiveness acceptability curves for negative drug tests and employment. RESULTS: ACWS cost $11,310 per participant over the 12-month intervention period. Total intervention and healthcare costs per participant over the intervention period were $20,625 for usual care and $30,686 for ACWS. At the end of the intervention period an additional participant with a negative drug test cost $1437 while an additional participant employed cost $915. CONCLUSIONS: ACWS increases drug abstinence and employment and may be cost-effective at the end of the 12-month intervention period if decision makers are willing to pay the incremental cost associated with the intervention.

Systems analysis and improvement approach to improve naloxone distribution within syringe service programs: study protocol of a randomized controlled trial.

BACKGROUND: More than half a million Americans died of an opioid-related overdose between 1999 and 2020, the majority occurring between 2015 and 2020. The opioid overdose mortality epidemic disproportionately impacts Black, Indigenous, and people of color (BIPOC): since 2015, overdose mortality rates have increased substantially more among Black (114%) and Latinx (97%) populations compared with White populations (32%). This is in part due to disparities in access to naloxone, an opioid antagonist that can effectively reverse opioid overdose to prevent death. Our recent pilot work determined that many barriers to naloxone access can be identified and addressed by syringe service programs (SSPs) using the Systems Analysis and Improvement Approach to Naloxone distribution (SAIA-Naloxone). This randomized controlled trial will test SAIA-Naloxone's ability to improve naloxone distribution in general and among BIPOC specifically. METHODS: We will conduct a trial with 32 SSPs across California, randomly assigning 16 to the SAIA-Naloxone arm and 16 to receive implementation as usual. SAIA-Naloxone is a multifaceted, multilevel implementation strategy through which trained facilitators work closely with SSPs to (1) assess organization-level barriers, (2) prioritize barriers for improvement, and (3) test solutions through iterative change cycles until achieving and sustaining improvements. SSPs receiving SAIA-Naloxone will work with a trained facilitator for a period of 12 months. We will test SAIA-Naloxone's ability to improve SSPs' naloxone distribution using an interrupted time series approach. Data collection will take place during a 3-month lead-in period, the 12-month active period, and for an additional 6 months afterward to determine whether impacts are sustained. We will use a structured approach to specify SAIA-Naloxone to ensure strategy activities are clearly defined and to assess SAIA-Naloxone fidelity to aid in interpreting study results. We will also assess the costs associated with SAIA-Naloxone and its cost-effectiveness. DISCUSSION: This trial takes a novel approach to improving equitable distribution of naloxone amid the ongoing epidemic and associated racial disparities. If successful, SAIA-Naloxone represents an important organizational-level solution to the multifaceted and multilevel barriers to equitable naloxone distribution.

Health care use and cost of treatment for adolescents and young adults with opioid use disorder.

BACKGROUND: Few studies have examined the cost of medication for opioid use disorder (MOUD) with counseling for the adolescent and young adult population. This study calculated the health care utilization and cost of MOUD treatment, other substance use disorder treatment, and general health care for adolescents and young adults receiving treatment for opioid use disorder. METHODS: The study randomized youth ages 15 to 21 (N = 288) equally into the two study conditions: extended-release naltrexone (XR-NTX) or treatment as usual (TAU). While participants committed to treatment based on randomization the study observed considerable nonadherence to both randomized conditions. Instead of using the randomly assigned study conditions, we present descriptive costs by the type of MOUD treatment received: XR-NTX only, buprenorphine only, any other combination of MOUD treatments, and no MOUD. Health care use was aggregated over the 6-month period for each participant, and we calculated average/participant utilization for each treatment group. To determine participant costs, we multiplied the unit costs of health care services obtained from the literature by the reported amount of health care utilization for each participant. We then calculated the mean, standard error, median and IQR for MOUD costs, other substance use disorder treatment costs and general healthcare cost from the health care sector perspective. RESULTS: On average, participants in the XR-NTX only group received 2.6 doses of XR-NTX (equivalent to approximately 78 days of treatment). The buprenorphine only group had an average of 97 days of buprenorphine treatment. The XR-NTX only group had higher/patient costs compared to participants in the buprenorphine only group ($10,491 vs. $8765) and higher XR-NTX utilization would further increase costs. Participants in the any other MOUD combination group had the highest total costs ($14,627) while participants in the no MOUD group at the lowest ($3453). DISCUSSION: Our cost analysis calculates the real-world cost of MOUD treatment and, while not generalizable, provides policy makers an estimate of costs for adolescents and young adults. We found that participants in the XR-NTX only group received fewer days of medication compared to the buprenorphine only group, but their medication costs were higher due to the cost of XR-NTX injections. While the buprenorphine only group had the highest number of days of medication utilization of all the groups, the average number of days of medication utilization was considerably shorter than the six-month treatment period.