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IMPORTANCE Prior authorization requirements may be a barrier to accessing medications for opioid use disorder treatment and may, therefore, be associated with poor health care outcomes. OBJECTIVE To determine the association of prior authorization with use of buprenorphinenaloxone and health care outcomes. DESIGN, SETTING, AND PARTICIPANTS This comparative interrupted time series analysis examined enrollment and insurance claims data from Medicare beneficiaries with an opioid use disorder diagnosis or who filled a prescription for an opioid use disorder medication between 2012 and 2017. Over this period, 775 874 members were in 1479 Part D plans that always required prior authorization, 113 286 members were in 206 plans that removed prior authorization, 189 461 members were in 489 plans that never required prior authorization, and 619 919 members were in 485 plans that added prior authorization. Data analysis was performed from April 2019 to February 2020. EXPOSURES Removal or addition of prior authorization and new prescriptions filled for buprenorphine-naloxone. MAIN OUTCOMES AND MEASURES Buprenorphine-naloxone use, inpatient admissions, emergency department visits, and prescription drug and medical expenditures. RESULTS The study population in 2012 included 949 206 Medicare beneficiaries (mean [SD] age, 57 [15] years; 550 445 women [58%]). Removal of prior authorization was associated with an increase of 17.9 prescriptions (95% CI, 1.1 to 34.7 prescriptions) filled for buprenorphine-naloxone per plan per year, which is a doubling of the number of prescriptions, on average. Each prescription filled was associated with statistically significant decreases in adverse health care outcomes: substance use disorder-related inpatient admissions decreased by 0.1 admission per plan per year (95% CI, −0.2 to −0.1 admission per plan per year), and substance use disorder-related emergency department visits decreased by 0.1 visit per plan per year (95% CI, −0.13 to −0.03 visit per plan per year) (all P < .001). Combining these results, removal of prior authorization was associated with a reduction in substance use disorder-related inpatient admissions by 2.0 admissions per plan per year (95% CI, −4.3 to −0.1 admissions per plan per year) and substance use disorder-related emergency department visits by 1.4 visits per plan per year (95% CI, −3.2 to −0.1 visits per plan per year). CONCLUSIONS AND RELEVANCE Removing prior authorization for buprenorphine-naloxone was associated with an increase in the medication use and decreases in health care utilization and expenditures.

Maine, Massachusetts, Minnesota, and Vermont leveraged State Innovation Model awards to implement Medicaid accountable care organizations (ACOs). Flexibility in model design, ability to build on existing reforms, provision of technical assistance to providers, and access to feedback data all facilitated ACO development. Challenges included sustainability of transformation efforts and the integration of health care and social service providers. Early estimates showed promising improvements in hospital‐related utilization and Vermont was able to reduce or slow the growth of Medicaid costs. These states are sustaining Medicaid ACOs owing in part to provider support and early successes in generating shared savings. The states are modifying their ACOs to include greater accountability and financial risk. Context As state Medicaid programs consider alternative payment models (APMs), many are choosing accountable care organizations (ACOs) as a way to improve health outcomes, coordinate care, and reduce expenditures. Four states (Maine, Massachusetts, Minnesota, and Vermont) leveraged State Innovation Model awards to create or expand Medicaid ACOs. Methods We used a mixed‐methods design to assess achievements and challenges with ACO implementation and the impact of Medicaid ACOs on health care utilization, quality, and expenditures in three states. We integrated findings from key informant interviews, focus groups, document review, and difference‐in‐difference analyses using data from Medicaid claims and an all‐payer claims database. Findings States built their Medicaid ACOs on existing health care reforms and infrastructure. Facilitators of implementation included allowing flexibility in design and implementation, targeting technical assistance, and making clinical, cost, and use data readily available to providers. Barriers included provider concerns about their ability to influence patient behavior, sustainability of provider practice transformation efforts when shared savings are reinvested into the health system and not shared with participating clinicians, and limited integration between health care and social service providers. Medicaid ACOs were associated with some improvements in use, quality, and expenditures, including statistically significant reductions in emergency department visits. Only Vermont's ACO demonstrated slower growth in total Medicaid expenditures. Conclusions Four states demonstrated that adoption of ACOs for Medicaid beneficiaries was both possible and, for three states, associated with some improvements in care. States revised these models over time to address stakeholder concerns, increase provider participation, and enable some providers to accept financial risk for Medicaid patients. Lessons learned from these early efforts can inform the design and implementation of APMs in other Medicaid programs.

Background and Aims To assess the burden of excessive alcohol use, researchers estimate alcohol-attributable fractions (AAFs) routinely. However, under-reporting in survey data can bias these estimates. We present an approach that adjusts for under-reporting in the estimation of AAFs, particularly within subgroups. This framework is a refinement of a previous method conducted by Rehm et al. Methods We use a measurement error model to derive the ‘true’ alcohol distribution from a ‘reported’ alcohol distribution. The ‘true’ distribution leverages per-capita sales data to identify the distribution average and then identifies the shape of the distribution with self-reported survey data. Data are from the National Alcohol Survey (NAS), the National Household Survey on Drug Abuse (NHSDA) and the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). We compared our approach with previous approaches by estimating the AAF of female breast cancer cases. Results Compared with Rehm et al.’s approach, our refinement performs similarly under a gamma assumption. For example, among females aged 18–25 years, the two approaches produce estimates from NHSDA that are within a percentage point. However, relaxing the gamma assumption generally produces more conservative evidence. For example, among females aged 18–25 years, estimates from NHSDA based on the best-fitting distribution are only 19.33% of breast cancer cases, which is a much smaller proportion than the gamma-based estimates of approximately 28%. Conclusions A refinement of Rehm et al.’s approach to adjusting for underreporting in the estimation of alcohol-attributable fractions provides more flexibility. This flexibility can avoid biases associated with failing to account for the underlying differences in alcohol consumption patterns across different study populations. Comparisons of our refinement with Rehm et al.’s approach show that results are similar when a gamma distribution is assumed. However, results are appreciably lower when the best-fitting distribution is chosen versus gamma-based results.

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