Medicaid Expansion and Implementation of Medication for Opioid Use Disorder Treatment Planning in U.S. Publicly Funded Specialty Treatment Systems

Technical Summary: Medicaid Expansion and Implementation of Medication for Opioid Use Disorder Treatment Planning in U.S. Publicly Funded Specialty Treatment Systems

Problem Statement
While Medications for Opioid Use Disorder (MOUD)—including methadone, buprenorphine, and extended-release naltrexone—are the established standard of care for reducing overdose mortality, their implementation within publicly funded specialty treatment systems in the United States remains uneven. Although the Affordable Care Act (ACA) Medicaid expansion significantly increased insurance coverage for low-income adults, including those with behavioral health conditions, there is limited evidence regarding whether this financing reform translated into documented changes in MOUD treatment planning within these specific systems. Publicly funded programs operate at the intersection of Medicaid reimbursement and federal block grant financing (Substance Use Prevention, Treatment, and Recovery Services Block Grant, or SUBG), yet it remains unclear if expanded coverage alone drives the adoption of evidence-based treatment planning for vulnerable populations.

Methodology
This retrospective study utilized national administrative data from the Treatment Episode Data Set–Admissions (TEDS-A) covering the period from 2006 to 2023. The analytic sample included over 10 million opioid-related treatment admissions from all 50 states, the District of Columbia, and Puerto Rico.

• Primary Outcome: Documented MOUD planning at admission, defined as the inclusion of methadone, buprenorphine, or extended-release naltrexone in the treatment plan. This metric reflects planning rather than confirmed medication receipt or adherence.
• Primary Exposure: State Medicaid expansion status, coded based on the first full calendar year of implementation.
• Statistical Approach: The authors employed an event-study difference-in-differences (DID) framework using multivariable logistic regression. This model estimated changes in documented MOUD planning across pre- and post-expansion periods while controlling for:
  • State fixed effects (to account for time-invariant state differences).
  • Calendar-year fixed effects (to account for national secular trends).
  • Admission-level covariates (demographics, clinical characteristics, housing status, criminal justice referral, etc.).
• Data Handling: Missing values in key variables (e.g., race, education) were retained using explicit "Not Reported" categories to preserve the sample size and account for structural reporting variations rather than random nonresponse. Standard errors were clustered at the state level.

Key Results

• Overall Prevalence: Of the 10.1 million opioid-related admissions analyzed, 28.7% included a documented MOUD plan.
• Impact of Medicaid Expansion: The study found that Medicaid expansion was associated with a statistically significant, short-term increase in the odds of documented MOUD planning during the first two years following implementation:
  • Year 1: Adjusted Odds Ratio (aOR) = 1.58 (95% CI: 1.14–2.19).
  • Year 2: aOR = 1.59 (95% CI: 1.19–2.12).
  • Long-term: No statistically significant associations were observed beyond two years post-expansion, indicating that the initial gains were not sustained.
• Pre-Expansion Trends: Event-time estimates prior to expansion were not statistically significant, supporting the parallel trends assumption required for the DID model.
• Population Disparities: Significant variation persisted across demographic and clinical groups even after adjusting for expansion status:
  • Lower Odds: Individuals experiencing homelessness (aOR = 0.49), those referred through the criminal justice system (aOR = 0.55), and those with co-occurring substance use (e.g., alcohol, stimulants) had significantly lower odds of MOUD planning.
  • Higher Odds: Pregnant individuals (aOR = 2.72) and those reporting injection drug use (aOR = 1.26) had higher odds.
• Geographic Variation: Substantial geographic heterogeneity remained, with higher levels of documented planning concentrated in the Northeast and West, and lower levels in parts of the South and Midwest, independent of Medicaid expansion timing.

Key Contributions

• National Evaluation of Implementation: This study provides one of the first national-level evaluations of documented MOUD treatment planning within publicly funded specialty treatment systems using TEDS-A data, a critical resource for monitoring federal block grant performance.
• Distinction Between Coverage and Implementation: The research distinguishes between insurance coverage expansion and the actual implementation of clinical practices, demonstrating that while coverage expanded, the structural adoption of MOUD planning in public systems did not follow a sustained trajectory.
• Identification of Vulnerable Populations: The analysis highlights that Medicaid expansion alone did not mitigate disparities for high-risk groups, such as those experiencing homelessness or involved in the criminal justice system, who continued to face barriers to documented evidence-based treatment planning.

Significance and Claims
The authors conclude that Medicaid expansion was associated with modest, short-term increases in documented MOUD planning, but these effects were not sustained over time. The paper posits that broader insurance coverage alone is insufficient to fundamentally alter implementation patterns within publicly funded specialty treatment systems.

The significance of these findings lies in the implication that factors beyond financing—such as treatment system organization, service integration, provider capacity, workforce availability, and implementation infrastructure—are critical determinants of evidence-based treatment adoption. The authors argue that while insurance expansion facilitates initial access, it does not automatically resolve the complex operational challenges of integrating MOUD into diverse clinical settings, particularly for vulnerable populations. Consequently, the study suggests that future policy efforts must look beyond coverage expansion to address the structural and operational barriers that limit equitable delivery of evidence-based opioid treatment. The authors also emphasize the need for more standardized performance monitoring and data collection to better evaluate implementation across jurisdictions.