Economic Evaluation Design within the HEAL Prevention Cooperative.

The rapid rise in opioid misuse, disorder, and opioid-involved deaths among older adolescents and young adults is an urgent public health problem. Prevention is a vital part of the nation's response to the opioid crisis, yet preventive interventions for those at risk for opioid misuse and opioid use disorder are scarce. In 2019, the National Institutes of Health (NIH) launched the Preventing Opioid Use Disorder in Older Adolescents and Young Adults cooperative as part of its broader Helping to End Addiction Long-term (HEAL) Initiative ( https://heal.nih.gov/ ). The HEAL Prevention Cooperative (HPC) includes ten research projects funded with the goal of developing effective prevention interventions across various settings (e.g., community, health care, juvenile justice, school) for older adolescent and young adults at risk for opioid misuse and opioid use disorder (OUD). An important component of the HPC is the inclusion of an economic evaluation by nine of these research projects that will provide information on the costs, cost-effectiveness, and sustainability of these interventions. The HPC economic evaluation is integrated into each research project's overall design with start-up costs and ongoing delivery costs collected prospectively using an activity-based costing approach. The primary objectives of the economic evaluation are to estimate the intervention implementation costs to providers, estimate the cost-effectiveness of each intervention for reducing opioid misuse initiation and escalation among youth, and use simulation modeling to estimate the budget impact of broader implementation of the interventions within the various settings over multiple years. The HPC offers an extraordinary opportunity to generate economic evidence for substance use prevention programming, providing policy makers and providers with critical information on the investments needed to start-up prevention interventions, as well as the cost-effectiveness of these interventions relative to alternatives. These data will help demonstrate the valuable role that prevention can play in combating the opioid crisis.

Benefits and costs of substance abuse treatment programs for state prison inmates: results from a lifetime simulation model.

Reflecting drug use patterns and criminal justice policies throughout the 1990s and 2000s, prisons hold a disproportionate number of society's drug abusers. Approximately 50% of state prisoners meet the criteria for a diagnosis of drug abuse or dependence, but only 10% receive medically based drug treatment. Because of the link between substance abuse and crime, treating substance abusing and dependent state prisoners while incarcerated has the potential to yield substantial economic benefits. In this paper, we simulate the lifetime costs and benefits of improving prison-based substance abuse treatment and post-release aftercare for a cohort of state prisoners. Our model captures the dynamics of substance abuse as a chronic disease; estimates the benefits of substance abuse treatment over individuals' lifetimes; and tracks the costs of crime and criminal justice costs related to policing, adjudication, and incarceration. We estimate net societal benefits and cost savings to the criminal justice system of the current treatment system and five policy scenarios. We find that four of the five policy scenarios provide positive net societal benefits and cost savings to the criminal justice system relative to the current treatment system. Our study demonstrates the societal gains to improving the drug treatment system for state prisoners.

Costs and Implementation Effectiveness of Generalist Versus Specialist Models for Adolescent Screening and Brief Intervention in Primary Care.

OBJECTIVE: This study analyzed the marginal service and program costs, and conducted a cost-effectiveness analysis (CEA) of two models of implementation of adolescent substance screening, brief intervention, and referral to treatment (SBIRT). METHOD: SBIRT was implemented at seven clinics in a multisite, cluster-randomized trial, through a Specialist model (behavioral health counselor-delivered brief intervention), and a Generalist model (primary care provider-delivered brief intervention). The CEA calculated marginal costs using an activity-based costing methodology for direct SBIRT services, and effectiveness was measured by the proportion of brief interventions delivered among patients who screened positive for alcohol, tobacco, or other drugs. Site-level program costs comprised start-up and maintenance (training and technical assistance). Costs were estimated in 2017 U.S. dollars. RESULTS: The marginal cost of SBIRT per patient with a positive screen for brief intervention was $6.72 in the Specialist model and $6.05 in the Generalist model. Implementation effectiveness was 7.2% (SE = 2.9%) in the Specialist model and 37.7% (SE = 5.6%) in the Generalist model. The program costs to provide SBIRT for 1 year per site were $13,548 for the Specialist site and $12,081 for the Generalist. CONCLUSIONS: The Generalist model was more effective in implementing brief intervention and less expensive than the Specialist model. Results were robust to sensitivity analysis. Brief intervention delivered by primary care providers rather than by handoff to a behavioral health counselor may ensure greater penetration and a lower cost of these services in primary care settings.

A systematic review and meta-analysis of health care utilization outcomes in alcohol screening and brief intervention trials.

OBJECTIVE: This systematic review and meta-analysis examines the effect of screening and brief intervention (SBI) on outpatient, emergency department (ED), and inpatient health care utilization outcomes. Much of the current literature speculates that SBI provides cost savings through reduced health care utilization, but no systematic review or meta-analysis examines this assertion. METHOD: Publications were abstracted from online journal collections and targeted Web searches. The systematic review included any publications that examined the association between SBI and health care utilization. Each publication was rated independently by 2 study authors and assigned a consensus methodological score. The meta-analysis focused on those studies examined in the systematic review, but it excluded publications that had incomplete data, low methodological quality, or a cluster-randomized design. RESULTS: Systematic review results suggest that SBI has little to no effect on inpatient or outpatient health care utilization, but it may have a small, negative effect on ED utilization. A random effects meta-analysis using the Hedges method confirms the ED result for SBI delivered across settings (standardized mean difference = -0.06, I = 13.9%) but does not achieve statistical significance (confidence interval: -0.15, 0.03). CONCLUSIONS: SBI may reduce overall health care costs, but more studies are needed. Current evidence is inconclusive for SBI delivered in ED and non-ED hospital settings. Future studies of SBI and health care utilization should report the estimated effects and variance, regardless of the effect size or statistical significance.

Alcohol Consumption in Response to the COVID-19 Pandemic in the United States.

OBJECTIVES: Excessive alcohol use is a serious and growing public health problem. Alcoholic beverage sales in the United States increased greatly immediately after the stay-at-home orders and relaxing of alcohol restrictions associated with the COVID-19 pandemic. However, it is not known to what degree alcohol consumption changed. This study assesses differences in alcohol drinking patterns before and after the enactment of stay-at-home orders. METHODS: In May 2020, a cross-sectional online survey of 993 individuals using a probability-based panel designed to be representative of the US population aged 21 and older was used to assess alcohol drinking patterns before (February, 2020) and after (April, 2020) the enactment of stay-at-home orders among those who consumed alcohol in February, 2020 (n = 555). Reported differences in alcohol consumption were computed, and associations between differences in consumption patterns and individual characteristics were examined. RESULTS: Compared to February, respondents reported consuming more drinks per day in April (+29%, P < 0.001), and a greater proportion reported exceeding recommended drinking limits (+20%, P < 0.001) and binge drinking (+21%, P = 0.001) in April. These differences were found for all sociodemographic subgroups assessed. February to April differences in the proportion exceeding drinking limits were larger for women than men (P = 0.026) and for Black, non-Hispanic people than White, non-Hispanic people (P = 0.028). CONCLUSIONS: There is an association among the COVID-19 pandemic, the public health response to it, changes in alcohol policy, and alcohol consumption. Public health monitoring of alcohol consumption during the pandemic is warranted.

Computer- vs. nurse practitioner-delivered brief intervention for adolescent marijuana, alcohol, and sex risk behaviors in school-based health centers.

BACKGROUND: This study examined approaches to delivering brief interventions (BI) for risky substance use and sexual behaviors in school-based health centers (SBHCs). METHODS: 300 Adolescents (ages 14-18; 54 % female) with risky marijuana and/or alcohol use identified via CRAFFT screening (scores >1) were recruited from two SBHCs and randomized to computer-delivered BI (CBI) or nurse practitioner-delivered BI (NBI). Both BIs included motivational and didactic content targeting marijuana, alcohol, and risky sexual behaviors. Assessments at baseline, 3-month, and 6-month follow-up included past 30-day frequency of marijuana use, alcohol use, binge drinking, unprotected sex, and sex while intoxicated; marijuana and alcohol problems; and health-related quality-of-life (HRQoL). A focused cost-effectiveness analysis was conducted. An historical 'assessment-only' cohort (N=50) formed a supplementary quasi-experimental comparison group. RESULTS: There were no significant differences between NBI and CBI on any outcomes considered (e.g., days of marijuana use; p=.26). From a cost-effectiveness perspective, CBI was 'dominant' for HRQoL and marijuana use. Participants' satisfaction with BI was significantly higher for NBI than CBI. Compared to the assessment-only cohort, participants who received a BI had lower frequency of marijuana (3-months: Incidence Rate Ratio [IRR] = .74 [.57, .97], p=.03), alcohol (3-months: IRR = .43 [.29, .64], p<.001; 6-months: IRR = .58 [.34, .98], p = .04), alcohol-specific problems (3-months: IRR = .63 [.45, .89], p=.008; 6-months: IRR = .63 [.41, .97], p = .04), and sex while intoxicated (6-months: IRR = .42 [.21, .83], p = .013). CONCLUSIONS: CBI and NBI did not yield different risk behavior outcomes in this randomized trial. Supplementary quasi-experimental comparisons suggested potential superiority over assessment-only. Both NBI and CBI could be useful in SBHCs.

Course of major depressive disorder and labor market outcome disruption.

BACKGROUND: Major depressive disorder (MDD) has been found to be negatively associated with labor market outcomes. However, MDD has many different courses that are chronic or persistent, relapsing and remitting, or limited to a single lifetime episode. Such heterogeneity has been ignored in most past analyses. AIMS OF THE STUDY: We examine the impact of heterogeneity in course of MDD on labor market outcomes. METHODS: Wave I (2001-2002) respondents of the National Epidemiological Survey on Alcohol and Related Conditions - a nationally representative panel survey - were interviewed on average 3 years later (2004-2005). We categorized changes in MDD before and after wave I and before wave II into six courses: incident, recent remission, persistent remission, relapse, persistent depression, and no history of MDD. Odds ratios (ORs) and marginal effects of MDD transitions in multivariable multinomial regressions of labor market outcomes (being out of the labor force, being unemployed, working part-time, and working full-time -- the reference outcome) are reported. RESULTS: Men and women who exhibited persistent remission (2 to 3 years) were equally likely to be in the labor force, employed, and working full-time, compared to those with no history of MDD (reference group). For men, recently remitted MDD (less than 1 year), compared to the reference group, increased the likelihood of being unemployed (3.2% higher probability of being unemployed conditional on being in the labor force; OR = 1.97, 95% confidence interval [CI] = 1.13--3.44) and working part-time (5.8% higher probability of working part-time conditional on being employed; OR = 1.75, 95% CI = 1.10-2.80). For women, no statistically significant effect for recent remission was found. The negative effects of incident onset, relapse, and persistence of MDD were found on some labor market outcomes for men and, to a lesser extent, for women. DISCUSSION: Clinical treatment for depression should be coordinated and/or integrated with work-related interventions that help individuals who are recovering from depression to maintain their jobs. Such coordination will add to the value of clinical treatment for depression. IMPLICATIONS FOR HEALTH POLICIES: The impact of MDD on labor market outcomes varies by course of illness. Past studies may have underestimated lost earnings due to mental illness because they did not distinguish between recent and persistent remission and thus did not account for lost earnings due to recent remission. IMPLICATIONS FOR FURTHER RESEARCH: Further research is needed to understand why there are differential impacts for men and women and to make causal inferences on the relationships between MDD and labor market outcomes.

Costs of using motivational interviewing for problem drinking in the U.S. Air Force.

Despite the popularity of motivational interviewing (MI) to address heavy drinking, limited evidence exists on the costs of using MI to address heavy drinking. This study examines the costs of using MI to address heavy drinking at four U.S. Air Force (USAF) bases. Clients were referred to and assessed at a base program to address their drinking as a result of an incident; those who were not alcohol dependent were invited to participate in the study. Participants consented and were randomly assigned to one of three intervention arms: individual MI (IMI), group MI (GMI), and Substance Abuse Awareness Seminar (SAAS). Three cost perspectives were taken: USAF, client, and the two combined. Data were collected from bases and public sources. The start-up cost per base ranged from $1340 to $2400 per provider staff member. Average implementation costs across bases were highest for the SAAS intervention ($148 per client).

Implementation science on the margins: How do we demonstrate the value of implementation strategies?

Implementation science (IS) has developed as a field to assess effective ways to implement and disseminate evidence-based practices. Although the size and rigor of the field has improved, the economic evaluation of implementation strategies has lagged behind other areas of IS (Roberts, Healey, & Sevdalis, 2019). Beyond demonstrating the effectiveness of implementation strategies, there needs to be evidence that investments in these strategies are efficient or financially sustainable. In this editorial, we lay out conceptual challenges in applying economic evaluation to IS and the implications for conducting economic analyses in integrated primary care research. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Assessing the impact of the national 'truth' antismoking campaign on beliefs, attitudes, and intent to smoke by race/ethnicity.

OBJECTIVE: To examine racial/ethnic differences in the association between exposure to the 'truth' antismoking campaign and youth's beliefs and attitudes about cigarette companies and their intent to smoke. DESIGN: The data are for 31,758 youth aged 12-17 from seven waves of the Legacy Media Tracking Survey (LMTS), conducted in the USA between December 1999 and July 2003. LMTS was designed to include sufficient proportions of African Americans (n=4631), Hispanics (n=6311), and Asians (n=2469) to assess tobacco countermarketing campaign associations in individual racial/ethnic groups. Separate belief and attitude indices were created. An indicator for the respondent not intending to smoke during the next year was created for non-smokers only, and models were estimated separately by ever-/never-smoking status. RESULTS: Exposure to the truth campaign was positively associated with increased antitobacco beliefs and attitudes among youth overall. When analyzed by race/ethnicity, this association was statistically significant for white and African American youth. An examination of the individual belief and attitude items that composed the measurement indices suggests that different messages appealed to youth based on their race/ethnicity. Among never smokers, those exposed to the truth campaign had significantly higher odds of not intending to smoke. When analyzed separately by race/ethnicity, the estimates for African American youth were statistically significant and the estimates for white and Hispanic youth approached significance. Among ever smokers and across all racial/ethnic groups, those exposed to the truth campaign had significantly higher odds of not intending to smoke, and every racial/ethnic group had an odds ratio greater than one that was also statistically significant. CONCLUSIONS: The findings suggest that the individual items comprising the indices may be less meaningful for some non-white groups of youth. Analyses of intention to smoke indicated that, among those who had never smoked, there were greater odds of not intending to smoke when examining all youth together without stratifying by race/ethnicity; however, a statistically significant effect was found only for the African American group when examining the effect by race/ethnicity. Among those who had ever smoked, a statistically significant effect was found for most racial/ethnic groups. This is a rich area for further research and is potentially critical to the success of future efforts to reach youth through behavior change messages.

Psychiatric disorders and the labor market: an analysis by disorder profiles.

BACKGROUND: A key societal cost of mental illness is its impact on the labor market. In examining the relationship between psychiatric disorders and the labor market, the literature to date either examines psychiatric disorders in broad classes or focuses on the impact of specific conditions. AIMS OF THE STUDY: The aim is to examine the relationships among meaningful profiles of concurrent past year disorders and labor market outcomes by gender. METHODS: Data are from the National Epidemiologic Survey on Alcohol and Related Conditions for 2001/2002 (NESARC), a representative sample of the noninstitutionalized population aged 18 or older residing in the United States. The analysis sample contains 18,429 women and 16,426 men (unweighted). We examined the relationship between profiles of psychiatric disorders and three labor market outcomes: labor force participation; employment, conditional on labor force participation; and working full-time conditional on being employed. Because no attempt was made to control for potential endogeneity between the labor market outcomes and the psychiatric profiles, we are unable to establish the causal direction of the associations estimated. RESULTS: First, anxiety disorders among women appear to be associated with labor market outcomes (e.g., anxiety profile in employment outcome: OR=0.76, p<.05). Second, for employment among women large effects were seen for mood disorder and mood and anxiety; in contrast for men, these disorder profiles had significant associations with working full-time rather than employment. Third, for women, of the three labor market outcomes, employment status is particularly sensitive to the profiles of disorders. For men, no such pattern was found for any single labor market outcome. DISCUSSION: Concurrent psychiatric disorder profiles affect men and women differently in the labor market. The greatest differences are in (i) the relationship between labor market outcomes and profiles exhibiting anxiety disorders, and (ii) which labor market outcomes are influenced. The main methodological limitation is that the approach does not attempt to assert a direction of causation between mental health conditions and the labor market outcomes. Unobserved heterogeneity and endogeneity are both possible and likely to some degree. Other limitations pertain to the data, which are cross-sectional and exclude some relatively rare disorders (e.g., schizophrenia). IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: The results may have significant implications for access to appropriate treatment, which may vary greatly by psychiatric disorder profile and by gender. IMPLICATIONS FOR HEALTH POLICIES: In the United States, private third-party coverage for treatment is obtained either directly through working full-time at a medium to large firm or through a spouse being employed. The findings thus suggest that mental health policy may need to account for labor market policy. IMPLICATIONS FOR FURTHER RESEARCH: Additional research is needed to disentangle the findings presented. For example, it is important to separate the influence of substance use disorders from mood disorder and uncover the pathways by which the different conditions in substance use disorders may influence the job market.

Examining variation in treatment costs: a cost function for outpatient methadone treatment programs.

OBJECTIVES: To estimate a hybrid cost function of the relationship between total annual cost for outpatient methadone treatment and output (annual patient days and selected services), input prices (wages and building space costs), and selected program and patient case-mix characteristics. DATA SOURCES: Data are from a multistate study of 159 methadone treatment programs that participated in the Center for Substance Abuse Treatment's Evaluation of the Methadone/LAAM Treatment Program Accreditation Project between 1998 and 2000. STUDY DESIGN: Using least squares regression for weighted data, we estimate the relationship between total annual costs and selected output measures, wages, building space costs, and selected program and patient case-mix characteristics. PRINCIPAL FINDINGS: Findings indicate that total annual cost is positively associated with program's annual patient days, with a 10 percent increase in patient days associated with an 8.2 percent increase in total cost. Total annual cost also increases with counselor wages (p<.01), but no significant association is found for nurse wages or monthly building costs. Surprisingly, program characteristics and patient case mix variables do not appear to explain variations in methadone treatment costs. Similar results are found for a model with services as outputs. CONCLUSIONS: This study provides important new insights into the determinants of methadone treatment costs. Our findings concur with economic theory in that total annual cost is positively related to counselor wages. However, among our factor inputs, counselor wages are the only significant driver of these costs. Furthermore, our findings suggest that methadone programs may realize economies of scale; however, other important factors, such as patient access, should be considered.

Behavioral Health Coverage In The Individual Market Increased After ACA Parity Requirements.

As of January 1, 2014, the Affordable Care Act designated mental health and substance use services as an essential health benefit in Marketplace plans and extended parity protections to the individual and small-group markets. We analyzed documents for seventy-eight individual and small-group plans in 2014 (after parity provisions took effect) and sixty comparison plans in 2013 (the year before parity provisions took effect) to understand the degree to which coverage for mental health and substance use care improved relative to medical/surgical benefits. The results suggest that plan issuers did what the provisions required them to do. Although in 2013 a lower proportion of plans covered mental health or substance use care, compared to medical/surgical care, in 2014 the proportions were the same. If essential health benefit requirements were to be removed and mental health and substance use coverage becomes similar to that in 2013, as many as 20 percent of the plans in our sample would not cover these conditions. To determine whether increases in behavioral health coverage will result in improved access to behavioral health services requires complementary data on the size of provider networks and use of services.

Cost and cost-effectiveness of computerized vs. in-person motivational interventions in the criminal justice system.

INTRODUCTION: Although substance use is common among probationers in the United States, treatment initiation remains an ongoing problem. Among the explanations for low treatment initiation are that probationers are insufficiently motivated to seek treatment, and that probation staff have insufficient training and resources to use evidence-based strategies such as motivational interviewing. A web-based intervention based on motivational enhancement principles may address some of the challenges of initiating treatment but has not been tested to date in probation settings. The current study evaluated the cost-effectiveness of a computerized intervention, Motivational Assessment Program to Initiate Treatment (MAPIT), relative to face-to-face Motivational Interviewing (MI) and supervision as usual (SAU), delivered at the outset of probation. METHODS: The intervention took place in probation departments in two U.S. cities. The baseline sample comprised 316 participants (MAPIT = 104, MI = 103, and SAU = 109), 90% (n = 285) of whom completed the 6-month follow-up. Costs were estimated from study records and time logs kept by interventionists. The effectiveness outcome was self-reported initiation into any treatment (formal or informal) within 2 and 6 months of the baseline interview. The cost-effectiveness analysis involved assessing dominance and computing incremental cost-effectiveness ratios and cost-effectiveness acceptability curves. Implementation costs were used in the base case of the cost-effectiveness analysis, which excludes both a hypothetical license fee to recoup development costs and startup costs. An intent-to-treat approach was taken. RESULTS: MAPIT cost $79.37 per participant, which was ~$55 lower than the MI cost of $134.27 per participant. Appointment reminders comprised a large proportion of the cost of the MAPIT and MI intervention arms. In the base case, relative to SAU, MAPIT cost $6.70 per percentage point increase in the probability of initiating treatment. If a decision-maker is willing to pay $15 or more to improve the probability of initiating treatment by 1%, estimates suggest she can be 70% confident that MAPIT is good value relative to SAU at the 2-month follow-up and 90% confident that MAPIT is good value at the 6-month follow-up. CONCLUSIONS: Web-based MAPIT may be good value compared to in-person delivered alternatives. This conclusion is qualified because the results are not robust to narrowing the outcome to initiating formal treatment only. Further work should explore ways to improve access to efficacious treatment in probation settings.

Service costs of caring for adolescents with mental illness in a rural community, 1993-2000.

OBJECTIVE: Costs of treating child psychiatric disorders fall on educational, primary care, juvenile justice, and social service agencies as well as on psychiatric services. The authors estimated multiagency mental health costs by integrating service unit costs with utilization rates in an 11-county area. Using psychiatric diagnoses made independently of service use records, the authors calculated costs across agencies as well as the extent of unmet need for psychiatric care. METHOD: Annual parent and child reports were used to measure mental health care needs and units of service across 21 types of settings for the population-based Great Smoky Mountain Study sample of 1,420 adolescents from ages 13 to 16. Unit costs for services were generated from information from service providers and records. The authors calculated costs overall, costs by type of service, and costs by diagnosis. RESULTS: Average annual costs per adolescent treated were $3,146. Juvenile justice and inpatient/residential facilities accounted for well over half of the total costs. Costs for youths with two or more diagnoses were twice as much as costs of those with a single disorder. Among adolescents with service needs, 66.9% received no services. Public health insurance was associated with higher rates of specialty mental health care than either private insurance or no insurance. CONCLUSIONS: Annual costs across all services were three to four times greater than recent health insurance estimates alone. Many costs for adolescents with mental health problems were borne by agencies not designed primarily to provide psychiatric or psychological services. Only one in three adolescents needing psychiatric care received any mental health services.

The cost-effectiveness of brief intervention versus brief treatment of Screening, Brief Intervention and Referral to Treatment (SBIRT) in the United States.

AIMS: To conduct a cost-effectiveness analysis (CEA) comparing the delivery of brief intervention (BI) with brief treatment (BT) within Screening, Brief Intervention and Referral to Treatment (SBIRT) programs. DESIGN: Quasi-experimental differences in observed baseline characteristics between BI and BT patients were adjusted using propensity score techniques. Incremental comparison of costs and health outcomes associated with BI and BT. SETTING: Health-care settings in four US states participating in Substance Abuse and Mental Health Services Administration SBIRT grant programs. PARTICIPANTS: Ninety patients who received BT and 878 who received BI. MEASUREMENTS: Per-patient cost of SBIRT, patient demographics and six measures of substance use: proportion using alcohol, proportion using alcohol to intoxication, days of alcohol use, days of alcohol use to intoxication, proportion using drugs and days using drugs. FINDINGS: BI and BT were associated with better outcomes. The cost of SBIRT was significantly higher for BT patients ($75.54 versus 16.32, 95% confidence interval, P < 0.01). BT would be cost-effective if the decision-maker had a willingness to pay of $8.90 for a 1 percentage point reduction in the probability of using any alcohol. For the other five outcomes, BT was less effective and more costly, and BI would be a better use of resources. CONCLUSIONS: It might be cost-effective to offer brief treatment if the goal is to abstain from alcohol. However, the higher effectiveness of brief treatment for this outcome is associated with considerable uncertainty and, because both brief intervention and brief treatment improve all outcomes, brief treatment does not appear to be a good use of resources.

A time and motion study of Screening, Brief Intervention, and Referral to Treatment implementation in health-care settings.

AIMS: Screening and brief intervention for harmful substance use in medical settings is being promoted heavily in the United States. To justify service provision fiscally, the field needs accurate estimates of the number and type of staff required to provide services, and thus the time taken to perform activities used to deliver services. This study analyzed the time spent in activities for the component services of the substance misuse Screening, Brief Intervention and Referral to Treatment (SBIRT) program implemented in emergency departments, in-patient units and ambulatory clinics. DESIGN: Observers timed activities according to 18 distinct codes among SBIRT practitioners. SETTING: Twenty-six US sites within four grantees. PARTICIPANTS: Five hundred and one practitioner-patient interactions; 63 SBIRT practitioners. MEASUREMENTS: Timing of practitioner activities. INTERVENTIONS: Delivery of component services of SBIRT. FINDINGS: The mean (standard error) time to deliver services was 1:19 (0:06) for a pre-screen (n = 210), 4:28 (0:24) for a screen (n = 97) and 6:51 (0:38) for a brief intervention (n = 66). Estimates of service duration varied by setting. Overall, practitioners spent 40% of their time supporting SBIRT delivery to patients and 13% of their time delivering services. CONCLUSIONS: In the United States, support activities (e.g. reviewing the patient's chart, locating the patient, writing case-notes) for substance abuse Screening, Brief Intervention and Referral to Treatment require more staff time than delivery of services. Support time for screens and brief interventions in the emergency department/trauma setting was high compared with the out-patient setting.

Sustaining SBIRT in the wild: simulating revenues and costs for Screening, Brief Intervention and Referral to Treatment programs.

AIMS: To examine the conditions under which Screening, Brief Intervention and Referral to Treatment (SBIRT) programs can be sustained by health insurance payments. DESIGN: A mathematical model was used to estimate the number of patients needed for revenues to exceed costs. SETTING: Three medical settings in the United States were examined: in-patient, out-patient and emergency department. Components of SBIRT were delivered by combinations of health-care practitioners (generalists) and behavioral health specialists. PARTICIPANTS: Practitioners in seven SBIRT programs who received grants from the US Substance Abuse and Mental Health Services Administration (SAMHSA). MEASUREMENTS: Program costs and revenues were measured using data from grantees. Patient flows were measured from administrative data and adjusted with prevalence and screening estimates from the literature. FINDINGS: SBIRT can be sustained through health insurance reimbursement in out-patient and emergency department settings in most staffing mixes. To sustain SBIRT in in-patient programs, a patient flow larger than the national average may be needed; if that flow is achieved, the range of screens required to maintain a surplus is narrow. Sensitivity analyses suggest that the results are very sensitive to changes in the proportion of insured patients. CONCLUSIONS: Screening, Brief Intervention and Referral to Treatment programs in the United States can be sustained by health insurance payments under a variety of staffing models. Screening, Brief Intervention and Referral to Treatment programs can be sustained only in an in-patient setting with above-average patient flow (more than 2500 screens). Screening, Brief Intervention and Referral to Treatment programs in out-patient and emergency department settings can be sustained with below-average patient flows (fewer than 125 000 out-patient visits and fewer than 27 000 emergency department visits).

Formal treatment, self-help, or no treatment for alcohol-use disorders? Evidence from the National Household Survey on Drug Abuse.

OBJECTIVE: The purpose of this study was to examine further alcohol treatment choice by using data from a nationally representative sample of adults with alcohol-use disorders to test which of three models-sequential, multinomial, or nested best fit the data. The goals were to provide evidence about how this choice was made and to provide improved coefficient estimates, as well as to inform future analyses of treatment choice. METHOD: Data from the 2000 National Household Survey of Drug Abuse include respondents ages 18-64 reporting symptoms consistent with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) diagnoses of alcohol abuse or dependence. A nested multinomial framework is used to determine the preferred model and to estimate the effect of respondents' characteristics on the decisions to receive help and what kind of help to receive. RESULTS: A sequential model, in which the choice of whether to receive help is unaffected by the level of satisfaction afforded by the alternatives, best fit the data. Older respondents had higher odds of both receiving help and choosing self-help, and those with a DSM-IV diagnosis of abuse had lower odds of receiving help but higher odds of entering self-help. CONCLUSIONS: The decision to receive help for alcohol problems appears unaffected by the perceived differences between these two broad categories of alternatives: self-help or formal treatment. This result may indicate the need to provide more information on the full range of treatment options to those for whom self-help may not be sufficient.

Cost of Screening, Brief Intervention, and Referral to Treatment in Health Care Settings.

AIMS: This study analyzed service unit and annual costs of substance abuse screening, brief intervention, and referral to treatment (SBIRT) programs implemented in emergency department (ED), inpatient, and outpatient medical settings in three U.S. states and one tribal organization. METHODS: Unit costs and annual costs were estimated from the perspective of service providers. Data for unit costs came from 26 performance sites, and data for annual costs came from 10 programs. A bottom-up approach was used to derive unit costs and included labor, space, and materials used in each SBIRT activity. Activities included direct SBIRT services and activities that support direct service delivery. Labor time spent in each activity was collected by trained observers using a time-and-motion approach. A top-down approach used cost questionnaires completed by program administrators to calculate annual costs and included labor, space, contracted services, overhead, training, travel, equipment, and supplies and materials. Costs were estimated in 2012 U.S. dollars. RESULTS: Average unit costs for prescreening, screening, brief intervention, brief treatment, and referral to treatment were $0.61, $6.59, $10.48, $22.63, and $12.06 in ED; $0.86, $6.33, $9.07, $27.61, and $8.03 in inpatient; and $0.84, $3.98, $7.81, $27.94, and $9.23 in outpatient settings, respectively; over half of the costs were attributable to support activities. Across all settings, the average cost to provide SBIRT per positive screen, for 1year, was about $400. CONCLUSIONS: Support activities comprise a large proportion of costs. Health administrators can use the results to budget and compare how much sites are reimbursed for SBIRT to how much services actually cost.