Virtual Engagement in a Social Media Community of Mothers With Substance Use Disorders: Content Analysis.

BACKGROUND: Co-occurring substance use disorder is common among pregnant and parenting women with mental illness, but their engagement with and utilization of relevant services and treatment is low. Social media has the potential to convey benefits and facilitate engagement among this target group. OBJECTIVE: This study aimed to explore the reach and engagement of specific social media posts among pregnant women and mothers with substance use disorders. METHODS: Eighteen posts providing content related to substance use (cannabis, opioids, or alcohol), varying in type of content (informational or experiential) and target (policy-, practice-, or perception-related), were posted in a closed Facebook community page comprising over 33,000 pregnant women and mothers between May 2019 and October 2019. RESULTS: The overall level of reach of these Facebook posts ranged from 453 to 3045 community members. Engagement levels, measured via the number of likes, comments, or posts shared, varied based on the type of post content (ie, informational or experiential). CONCLUSIONS: Participation in a virtual community via social media platforms can facilitate engagement among pregnant women and mothers with mental illness by communicating relevant information about substance use, as well as potentially promoting awareness of, access to, and engagement with treatment services.

Rates and predictors of brief intervention for women veterans returning from recent wars: Examining gaps in service delivery for unhealthy alcohol use.

BACKGROUND: Approximately one in four women veterans accessing the Department of Veterans Affairs (VA) engage in unhealthy alcohol use. There is substantial evidence for gender-sensitive screening (AUDIT-C = 3) and brief intervention (BI) to reduce risks associated with unhealthy alcohol use in women veterans; however, VA policies and incentives remain gender-neutral (AUDIT-C = 5). Women veterans who screen positive at lower-risk-level alcohol use (AUDIT-C = 3 or 4) may screen out and therefore not receive BI. This study aimed to examine gaps in implementation of BI practice for women veterans through identifying rates of BI at different alcohol risk levels (AUDIT-C = 3-4; =5-7; =8-12), and the role of alcohol risk level and other factors in predicting receipt of BI. METHODS: From administrative data (2010-2016), we drew a sample of women veterans returning from recent wars who accessed outpatient and/or inpatient care. Of 869 women veterans, 284 screened positive for unhealthy alcohol use at or above a gender-sensitive cut-point (AUDIT-C ≥ 3). We used chart review methods to abstract variables from the medical record and then employed logistic regression comparing women veterans who received BI at varying alcohol risk levels to those who did not. RESULTS: While almost 60% of the alcohol positive-risk sample received BI, among the subset of women veterans who screened positive for lower-risk alcohol use (57%; AUDIT-C = 3 or 4) only 34% received BI. Nurses in primary care programs were less likely to deliver BI than other types of clinicians (e.g., physicians, psychologists, social workers) in mental health programs; further, nurses in women's health programs were less likely to deliver BI than other types of clinicians in mixed-gender programs; Those women veterans with more medical problems were no more likely to receive BI than those with fewer medical problems. CONCLUSIONS: Given that women veterans are a rapidly growing veteran population and a VA priority, underuse of BI for women veterans screening positive at a lower-risk level and those with more medical comorbidities requires attention, as do potential gaps in service delivery of BI in primary care and women's health programs. Women veterans health and well-being may be improved by tailoring screening for a younger cohort of women veterans at high-risk for, or with co-occurring disorders and then training providers in best practices for BI implementation.

Assessing the postdeployment quality of treatment for substance use disorders among Army enlisted soldiers in the Military Health System.

Little is known about the rates and predictors of substance use treatment received in the Military Health System among Army soldiers diagnosed with a postdeployment substance use disorder (SUD). We used data from the Substance Use and Psychological Injury Combat study to determine the proportion of active duty (n = 338,708) and National Guard/Reserve (n = 178,801) enlisted soldiers returning from an Afghanistan/Iraq deployment in fiscal years 2008 to 2011 who had an SUD diagnosis in the first 150 days postdeployment. Among soldiers diagnosed with an SUD, we examined the rates and predictors of substance use treatment initiation and engagement according to the Healthcare Effectiveness Data and Information Set criteria. In the first 150 days postdeployment 3.3% of active duty soldiers and 1.0% of National Guard/Reserve soldiers were diagnosed with an SUD. Active duty soldiers were more likely to initiate and engage in substance use treatment than National Guard/Reserve soldiers, yet overall, engagement rates were low (25.0% and 15.7%, respectively). Soldiers were more likely to engage in treatment if they received their index diagnosis in a specialty behavioral health setting. Efforts to improve substance use treatment in the Military Health System should include initiatives to more accurately identify soldiers with undiagnosed SUD. Suggestions to improve substance use treatment engagement in the Military Health System will be discussed.

Access to and Engagement in Substance Use Disorder Treatment Over Time.

OBJECTIVE: This study evaluated whether access to and engagement in substance use disorder treatment has improved from 2010 to 2016. METHODS: Data submitted by commercial and Medicaid health plans, representing over 163 million beneficiaries from 2010 to 2016, were analyzed. RESULTS: For commercial plans, identification increased (from 1.0% to 1.6%, p<0.001), the initiation rate declined (from 41.9% to 33.7%, p<0.001), and the engagement rate also declined (from 15.8% to 12.1%, p<0.001). The decline in the initiation and engagement rates could not be explained by the increasing identification rates. For Medicaid plans, the identification rate increased (from 3.3% to 6.7%, p<0.001), and the initiation and engagement rates were unchanged. CONCLUSIONS: Although an increasing proportion of health plan members are being identified with substance use disorders, the majority of these individuals are not engaging in treatment.

Rural Clients' Continuity Into Follow-Up Substance Use Disorder Treatment: Impacts of Travel Time, Incentives, and Alerts.

PURPOSE: Treatment after discharge from detoxification or residential treatment is associated with improved outcomes. We examined the influence of travel time on continuity into follow-up treatment and whether financial incentives and weekly alerts have a modifying effect. METHODS: For a research intervention during October 2013 to December 2015, detoxification and residential substance use disorder treatment programs in Washington State were randomized into 4 groups: potential financial incentives for meeting performance goals, weekly alerts to providers, both interventions, and control. Travel time was used as both a main effect and interacted with other variables to explore its modifying impact on continuity of care in conjunction with incentives or alerts. Continuity was defined as follow-up care occurring within 14 days of discharge from detoxification or residential treatment programs. Travel time was estimated as driving time from clients' home ZIP Code to treatment agency ZIP Code. FINDINGS: Travel times to the original treatment agency were in some cases significant with longer travel times predicting lower likelihood of continuity. For detoxification clients, those with longer travel times (over 91 minutes from their residence) are more likely to have timely continuity. Conversely, residential clients with travel times of more than 1 hour are less likely to have timely continuity. Interventions such as alerts or incentives for performance had some mitigating effects on these results. Travel times to the closest agency for potential further treatment were not significant. CONCLUSIONS: Among rural clients discharged from detoxification and residential treatment, travel time can be an important factor in predicting timely continuity.

Is it feasible to pay specialty substance use disorder treatment programs based on patient outcomes?

BACKGROUND: Some US payers are starting to vary payment to providers depending on patient outcomes, but this approach is rarely used in substance use disorder (SUD) treatment. PURPOSE: We examine the feasibility of applying a pay-for-outcomes approach to SUD treatment. METHODS: We reviewed several relevant literatures: (1) economic theory papers that describe the conditions under which pay-for-outcomes is feasible in principle; (2) description of the key outcomes expected from SUD treatment, and the measures of these outcomes that are available in administrative data systems; and (3) reports on actual experiences of paying SUD treatment providers based on patient outcomes. RESULTS: The economics literature notes that when patient outcomes are strongly influenced by factors beyond provider control and when risk adjustment performs poorly, pay-for-outcomes will increase provider financial risk. This is relevant to SUD treatment. The literature on SUD outcome measurement shows disagreement on whether to include broader outcomes beyond abstinence from substance use. Good measures are available for some of these broader constructs, but the need for risk adjustment still brings many challenges. Results from two past payment experiments in SUD treatment reinforce some of the concerns raised in the more conceptual literature. CONCLUSION: There are special challenges in applying pay-for-outcomes to SUD treatment, not all of which could be overcome by developing better measures. For SUD treatment it may be necessary to define outcomes more broadly than for general medical care, and to continue conditioning a sizeable portion of payment on process measures.

Disparities in Criminal Justice Outcomes After Beginning Treatment for Substance Use Disorders: The Influence of Race/Ethnicity and Place.

OBJECTIVE: This study examined whether racial/ethnic disparities exist in posttreatment arrests and assessed the extent to which community characteristics account for such disparities. METHOD: Administrative data on clients (N = 10,529) receiving publicly funded services in Washington State were linked with criminal justice and census data. Multilevel survival models were used for two outcomes measuring time (in days) to any arrest and to any substance-related arrest. Community characteristics included a factor measuring community economic disadvantage and the proportions of residents in the client's residential census tract who were Black, Latino, or American Indian/Alaskan Native. RESULTS: When we controlled for age, sex, substance use, referral source, and prior criminal justice involvement, Black clients (hazard ratio [HR] = 1.47, p < .01) had a higher hazard of any arrest compared with White clients, and Black (HR = 1.27, p < .05) and Latino (HR = 1.20, p < .05) clients had a higher hazard of a substance-related arrest. Clients living in census tracts with a higher proportion of Black residents had a higher hazard of any arrest (HR = 1.25, p < .01) as well as substance-related arrests (HR = 1.39, p < .01). Community characteristics did not account for racial/ethnic disparities in arrests but provided an independent effect. CONCLUSIONS: Disparities in arrest outcomes are influenced by both individual- and community-level factors; therefore, strategies for reducing disparities in this treatment outcome should be implemented at both levels.

The importance of identification when measuring performance in addiction treatment.

Background: Identifying and effectively treating individuals with substance use disorders (SUDs) is an important priority for state Medicaid programs, given the enormous toll that SUDs take on individuals, their families, and their communities. In this paper, we describe how the Healthcare Effectiveness Data and Information Set (HEDIS) measure "Identification of Alcohol and Other Drug Services" can be used, along with eligible population prevalence rates, to expand states' ability to track how well their Medicaid programs identify enrollees with SUDs and link them with treatment (measured by initiation and engagement performance measures). Methods: We use the 2009 Medicaid MAX data on utilization and enrollment along with information from the National Survey of Drug Use and Health (NSDUH) to obtain state-level estimates of alcohol and drug abuse and dependence among Medicaid beneficiaries for 7 illustrative states. We calculate identification, initiation, and engagement measures using specifications from the National Committee on Quality Assurance (NCQA). Results: NSDUH data showed that the eligible population prevalence rate (the average rate of alcohol or drug abuse or dependence) among the 7 states was 10.0%, whereas the average identification rate was 2.9%. The gap between the prevalence and identification rates ranged from 5.1% to 11.0% among the 7 states. The initiation rates ranged from 36.9% to 57.1%. The states' engagement rates ranged from 11.8% to 31.1%, although rates differ by age, gender, and race/ethnicity in some states. Conclusion: Including identification along with initiation and engagement measures allows states to determine how well they are performing in a more complete spectrum from need, to recognition and documentation of enrollees with SUDs, to initiation of treatment, to continuation of early treatment.

Correction to: Disparities in the Treatment of Substance Use Disorders: Does Where You Live Matter?

The professional degree of co-author Kevin Campbell is incorrect. It should be "DrPH" and not "PhD".

Impact of Agency Receipt of Incentives and Reminders on Engagement and Continuity of Care for Clients With Co-Occurring Disorders.

OBJECTIVE: This study examined whether having co-occurring substance use and mental disorders influenced treatment engagement or continuity of care and whether offering financial incentives, client-specific electronic reminders, or a combination to treatment agencies improved treatment engagement and continuity of care among clients with co-occurring disorders. METHODS: The study used a randomized cluster design to assign agencies (N=196) providing publicly funded substance use disorder treatment in Washington State to a research arm: incentives only, reminders only, incentives and reminders, and a control condition. Data were analyzed for 76,044 outpatient, 32,797 residential, and 39,006 detoxification admissions from Washington's treatment data system. Multilevel logistic regressions were conducted, with clients nested within agencies, to examine the effect of the interventions on treatment engagement and continuity of care. RESULTS: Compared with clients with a substance use disorder only, clients with co-occurring disorders were less likely to engage in outpatient treatment or have continuity of care after discharge from residential treatment, but they were more likely to have continuity of care after discharge from detoxification. The interventions did not influence treatment engagement or continuity of care, except the reminders had a positive impact on continuity of care after residential treatment among clients with co-occurring disorders. CONCLUSIONS: In general, the interventions did not result in improved treatment engagement or continuity of care. The limited number of significant results supporting the influence of incentives and alerts on treatment engagement and continuity of care add to the mixed findings reported by previous research. Multiple interventions may be needed for performance improvement.

Applying American Society of Addiction Medicine Performance Measures in Commercial Health Insurance and Services Data.

OBJECTIVES: ASAM's Standards of Care for the Addiction Specialist established appropriate care for the treatment of substance use disorders. ASAM identified three high priority performance measures for specification and testing for feasibility in various systems using administrative claims: use of pharmacotherapy for alcohol use disorder (AUD); use of pharmacotherapy for opioid use disorder (OUD); and continuity of care after withdrawal management services. This study adds to the initial testing of these measures in the Veteran's Health Administration (VHA) by testing the feasibility of specifications in commercial insurance data (Cigna). METHODS: Using 2014 and 2015 administrative data, the proportion of individuals with an AUD or OUD diagnosis each year who filled prescriptions or were dispensed appropriate FDA-approved pharmacotherapy. For withdrawal management follow up, the proportion with an outpatient encounter within seven days was calculated. The sensitivity of specifications was also tested. RESULTS: Rates of pharmacotherapy for AUD ranged from 6.2% to 7.6% (depending on year and specification details), and rates for OUD pharmacotherapy were 25.0% to 29.7%. Seven-day follow up rate after withdrawal management in an outpatient setting was 20.5%, and an additional 39.7% in an inpatient or residential setting. CONCLUSIONS: Application of ASAM specifications is feasible in commercial administrative data. Because of varying system needs and payment practices across health systems, measures may require adjustment for different settings. Moving forward, important focus will be on the continued refinement of these measures with the new ICD-10 coding systems, new formulations of current medications, and new payment approaches such as bundled payment.

Employment after beginning treatment for substance use disorders: The impact of race/ethnicity and client community of residence.

Employment is an important substance use treatment outcome, frequently used to assess individual progress during and after treatment. This study examined whether racial/ethnic disparities exist in employment after beginning treatment. It also examined the extent to which characteristics of clients' communities account for such disparities. Analyses are based on data that linked individual treatment information from Washington State's Behavioral Health Administration with employment data from the state's Employment Security Department. Analyses subsequently incorporated community-level data from the U.S. Census Bureau. The sample includes 10,636 adult clients (Whites, 68%; American Indians, 13%, Latinos, 10%; and Blacks, 8%) who had a new outpatient treatment admission to state-funded specialty treatment. Heckman models were used to test whether racial/ethnic disparities existed in the likelihood of post-admission employment, as well as employment duration and wages earned. Results indicated that there were no racial/ethnic disparities in the likelihood of employment in the year following treatment admission. However, compared to White clients, American Indian and Black clients had significantly shorter lengths of employment and Black clients had significantly lower wages. With few exceptions, residential community characteristics were associated with being employed after initiating treatment, but not with maintaining employment or with wages. After accounting for community-level variables, disparities in length of employment and earned wages persisted. These findings highlight the importance of considering the race/ethnicity of a client when examining post-treatment employment alongside community characteristics, and suggest that the effect of race/ethnicity and community characteristics on post-treatment employment may differ based on the stage of the employment process.

Disparities in the Treatment of Substance Use Disorders: Does Where You Live Matter?

This study focused on (1) whether disparities in timely receipt of substance use services can be explained in part by the characteristics of the community in which the clients reside and (2) whether the effect of community characteristics on timely receipt of services was similar across racial/ethnic groups. The sample was composed of adults receiving publicly funded outpatient treatment in Washington State. Treatment data were linked to data from the US census. The outcome studied was "Initiation and Engagement" in treatment (IET), a measure noting timely receipt of services at the beginning of treatment. Community characteristics studied included community level economic disadvantage and concentration of American Indian, Latino, and Black residents in the community. Black and American Indian clients were less likely to initiate or engage in treatment compared to non-Latino white clients, and American Indian clients living in economically disadvantaged communities were at even greater risk of not initiating treatment. Community economic disadvantage and racial/ethnic makeup of the community were associated with treatment initiation, but not engagement, although they did not entirely explain the disparities found in IET.

Federal Parity and Access to Behavioral Health Care in Private Health Plans.

OBJECTIVE: The 2008 Mental Health Parity and Addiction Equity Act (MHPAEA) sought to improve access to behavioral health care by regulating health plans' coverage and management of services. Health plans have some discretion in how to achieve compliance with MHPAEA, leaving questions about its likely effects on health plan policies. In this study, the authors' objective was to determine how private health plans' coverage and management of behavioral health treatment changed after the federal parity law's full implementation. METHODS: A nationally representative survey of commercial health plans was conducted in 60 market areas across the continental United States, achieving response rates of 89% in 2010 (weighted N=8,431) and 80% in 2014 (weighted N=6,974). Senior executives at responding plans were interviewed regarding behavioral health services in each year and (in 2014) regarding changes. Student's t tests were used to examine changes in services covered, cost-sharing, and prior authorization requirements for both behavioral health and general medical care. RESULTS: In 2014, 68% of insurance products reported having expanded behavioral health coverage since 2010. Exclusion of eating disorder coverage was eliminated between 2010 (23%) and 2014 (0%). However, more products reported excluding autism treatment in 2014 (24%) than 2010 (8%). Most plans reported no change to prior-authorization requirements between 2010 and 2014. CONCLUSIONS: Implementation of federal parity legislation appears to have been accompanied by continuing improvement in behavioral health coverage. The authors did not find evidence of widespread noncompliance or of unintended effects, such as dropping coverage of behavioral health care altogether.

Agency-level financial incentives and electronic reminders to improve continuity of care after discharge from residential treatment and detoxification.

BACKGROUND: Despite the importance of continuity of care after detoxification and residential treatment, many clients do not receive further treatment services after discharged. This study examined whether offering financial incentives and providing client-specific electronic reminders to treatment agencies lead to improved continuity of care after detoxification or residential treatment. METHODS: Residential (N = 33) and detoxification agencies (N = 12) receiving public funding in Washington State were randomized into receiving one, both, or none (control group) of the interventions. Agencies assigned to incentives arms could earn financial rewards based on their continuity of care rates relative to a benchmark or based on improvement. Agencies assigned to electronic reminders arms received weekly information on recently discharged clients who had not yet received follow-up treatment. Difference-in-difference regressions controlling for client and agency characteristics tested the effectiveness of these interventions on continuity of care. RESULTS: During the intervention period, 24,347 clients received detoxification services and 20,685 received residential treatment. Overall, neither financial incentives nor electronic reminders had an effect on the likelihood of continuity of care. The interventions did have an effect among residential treatment agencies which had higher continuity of care rates at baseline. CONCLUSIONS: Implementation of agency-level financial incentives and electronic reminders did not result in improvements in continuity of care, except among higher performing agencies. Alternative strategies at the facility and systems levels should be explored to identify ways to increase continuity of care rates in specialty settings, especially for low performing agencies.

Behavioral Health Coverage Under the Affordable Care Act: What Can We Learn From Marketplace Products?

OBJECTIVE: The 2008 federal parity law and the 2010 Affordable Care Act (ACA) sought to expand access to behavioral health services. There was concern that health plans might discourage enrollment by individuals with behavioral health conditions who tend to be higher cost. This study compared behavioral health benefits available in the group insurance market (nonmarketplace) to those sold through the ACA marketplaces to check for evidence of less generous behavioral health coverage in marketplace plans. METHODS: Data were from a 2014 nationally representative survey of commercial health plans regarding behavioral health services (80% response rate). The sample included the most common silver marketplace product and, as a comparison, the most common nonmarketplace product of the same type (for example, health maintenance organization or preferred provider organization) from each health plan (N=106 marketplace and nonmarketplace pairs, or 212 products). RESULTS: Marketplace and nonmarketplace products were similar in terms of coverage, prior authorization, and continuing review requirements. Marketplace products were more likely to employ narrow and tiered behavioral health provider networks. Narrow and tiered networks were more common in state than in federal marketplaces. CONCLUSIONS: Provider network design is a tool that health plans may use to control cost and possibly discourage enrollment by high-cost users, including those with behavioral health conditions. The ACA was successful in ensuring robust behavioral health coverage in marketplace plans. As the marketplaces evolve or are replaced, these data provide an important baseline to which future systems can be compared.

Influencing quality of outpatient SUD care: Implementation of alerts and incentives in Washington State.

Financial incentives for quality improvement and feedback on specific clients are two approaches to improving the quality of treatment for individuals with substance use disorders. We examined the impacts of these interventions in Washington State by randomizing outpatient substance use treatment agencies into intervention and control groups. From October 2013 through December 2015, agencies could earn financial incentives for meeting performance goals incorporating both achievement relative to a benchmark and improvement from agencies' own baselines. Weekly feedback was e-mailed to agencies in the alert or alert plus incentives arms. Difference-in difference regressions controlling for client and agency characteristics showed that none of the interventions significantly affected client engagement after outpatient admissions, overall or for sub-groups based on race/ethnicity, age, rural residence, or agency baseline performance. Treatment agencies offered insights related to several themes: delivery system context (e.g., agency time and resources needed during transition to a managed behavioral healthcare system), implementation (e.g., data lag), agency issues (e.g., staff turnover), and client factors (e.g., motivation). Interventions took place during a time of Medicaid expansion and planning for statewide integration of mental health and substance use disorder treatment into a managed care model, which may have resulted in agencies not responding to the interventions. Moreover, incentives and alerts at the agency-level may not be effective when factors are at play beyond the agency's control.

The Role of Health Plans in Supporting Behavioral Health Integration.

Health plan policies can influence delivery of integrated behavioral health and general medical care. This study provides national estimates for the prevalence of practices used by health plans that may support behavioral health integration. Results indicate that health plans employ financing and other policies likely to support integration. They also directly provide services that facilitate integration. Behavioral health contracting arrangements are associated with use of these policies. Delivery of integrated care requires systemic changes by both providers and payers thus health plans are key players in achieving this goal.

How Do Private Health Plans Manage Specialty Behavioral Health Treatment Entry and Continuing Care?

OBJECTIVE: This study examined private health plans' arrangements for accessing and continuing specialty behavioral health treatment in 2010 as federal health reforms were being implemented. These management practices have historically been stricter in behavioral health care than in general medical care; however, the Mental Health Parity and Addiction Equity Act of 2010 required parity in management policies. METHODS: The data source was a nationally representative survey of private health plans' behavioral health treatment management approaches in 2010. Health plan executives were asked about activities for their plan's three products with highest enrollment (weighted N=8,427, 88% response rate). RESULTS: Prior authorization for outpatient behavioral health care was rarely required (4.7% of products), but 75% of products required authorization for ongoing care and over 90% required prior authorization for other levels of care. The most common medical necessity criteria were self-developed and American Society of Addiction Medicine criteria. Nearly all products had formal standards to limit waiting time for routine and urgent treatment, but almost 30% lacked such standards for detoxification services. A range of wait time-monitoring approaches was used. CONCLUSIONS: Health plans used a variety of methods to influence behavioral health treatment entry and continuing care. Few relied on prior authorization for outpatient care, but the use of other approaches to influence, manage, or facilitate access was common. Results provide a baseline for understanding the current management environment for specialty behavioral health care. Tracking health plans' approaches over time will be important to ensure that access to behavioral health care is not prohibitively restrictive.

Reducing Behavioral Health Inpatient Readmissions for People With Substance Use Disorders: Do Follow-Up Services Matter?

OBJECTIVE: Individuals with substance use disorders are at high risk of hospital readmission. This study examined whether follow-up services received within 14 days of discharge from an inpatient hospital stay or residential detoxification reduced 90-day readmissions among Medicaid enrollees whose index admission included a substance use disorder diagnosis. METHODS: Claims data were analyzed for Medicaid enrollees ages 18-64 with a substance use disorder diagnosis coded in any position for an inpatient hospital stay or residential detoxification in 2008 (N=30,439). Follow-up behavioral health services included residential, intensive outpatient, outpatient, and medication-assisted treatment (MAT). Analyses included data from ten states or fewer, based on a minimum number of index admissions and the availability of follow-up services or MAT. Survival analyses with time-varying independent variables were used to test the association of receipt of follow-up services and MAT with behavioral health readmissions. RESULTS: Two-thirds (67.7%) of these enrollees received no follow-up services within 14 days. Twenty-nine percent were admitted with a primary behavioral health diagnosis within 90 days of discharge. Survival analyses showed that MAT and residential treatment were associated with reduced risk of 90-day behavioral health admission. Receipt of outpatient treatment was associated with increased readmission risk, and, in only one model, receipt of intensive outpatient services was also associated with increased risk. CONCLUSIONS: Provision of MAT or residential treatment for substance use disorders after an inpatient or detoxification stay may help prevent readmissions. Medicaid programs should be encouraged to reduce barriers to MAT and residential treatment in order to prevent behavioral health admissions.