The cost of opioid use disorder-related conditions in Medicare.

BACKGROUND: Medicare coverage excludes some levels of substance use disorder (SUD) care, such as intensive outpatient and residential treatment. Expanding access to SUD treatment could increase Medicare spending. However, these costs could be offset if SUD treatment resulted in cost savings from reducing SUD-related medical events and SUD-related medical comorbidities. METHODS: This study estimated cost savings from expanding access to SUD treatment for persons with opioid use disorders (OUD) using three methods. First, we compared total Medicare fee-for-service spending on individuals with OUD and no treatment with OUD medications (MOUD) to Medicare spending on individuals without OUD after matching on age/sex/Medicare-Medicaid eligibility status. Second, we compared Medicare spending on individuals with OUD who received MOUD to spending individuals with OUD who did not receive MOUD. Third, we determined OUD-attributable Medicare spending for comorbid physical and mental conditions with a strong association with OUD. RESULTS: Beneficiaries with OUD but no MOUD totaled $15.8 billion more than beneficiaries without OUD. Beneficiaries with OUD but no MOUD totaled $12.1 billion more than individuals with OUD and MOUD. Lastly, Medicare spending on OUD-attributable comorbidities was $4.7 billion if all medical and mental health comorbidities were included and $3.0 billion with only medical comorbidities. The totals could be 1.7 times higher if Medicare Advantage enrollees were included. CONCLUSION: Expanding Medicare coverage of appropriate levels of care could improve access to effective treatment and reduce the costs associated with untreated OUD. This will likely result in substantial Medicare cost savings.

Substance Use Disorders Among Medicare Beneficiaries: Prevalence, Mental and Physical Comorbidities, and Treatment Barriers.

INTRODUCTION: This study aimed to determine the prevalence of treated and untreated substance use disorders among Medicare beneficiaries, the characteristics of Medicare beneficiaries with substance use disorders, and reasons for their unmet needs. METHODS: This study used data from the National Survey of Drug Use and Health, 2015-2019. Substance use disorder was defined based on DSM-IV dependence or abuse criteria. Descriptive analyses were conducted in 2021, including testing for differences in unadjusted means. RESULTS: Approximately 1.7 million Medicare beneficiaries were estimated to have past-year substance use disorder (8% of Medicare beneficiaries aged <65 years and 2% aged ≥65 years). Overall, 77% had an alcohol use condition, 16% had a prescription drug use condition, and 10% had a marijuana use condition. Of those who had past-year substance use disorder, 11% received treatment for their condition. Common reasons for not receiving treatment were lack of motivation (41%), financial barriers (33%), concern about what others might think (24%), logistical barriers such as lack of transportation (21%), and uncertainty about treatment efficacy (13%). Medicare beneficiaries with substance use disorders were more than twice as likely to have past-year serious psychological distress as those without substance use disorders (44% vs 21%, p<0.001 for those aged <65 years; 14% vs 4%, p<0.001 for those aged ≥65 years). Percentages of past-year suicidal ideation were also much higher among Medicare beneficiaries with substance use disorders than without (24% vs 6%, p<0.001 for those aged <65 years; 7% vs 2%, p=0.006 for those aged ≥65 years). CONCLUSIONS: Few Medicare beneficiaries who need substance use disorder treatment receive it. Reducing Medicare coverage gaps and stigma may help meet this need.

The association of Medicare Part D prior authorization for buprenorphine-naloxone with adherence to opioid use disorder treatment guidelines in the United States.

AIMS: To assess differences in the quality of opioid use disorder (OUD) treatment received by Medicare beneficiaries enrolled in health plans that used prior authorization (PA) for buprenorphine-naloxone compared with those enrolled in plans that did not use PA. DESIGN, SETTING AND PARTICIPANTS: Cross-sectional observational study, United States. Continuously enrolled beneficiaries (71 294) with an OUD who filled at least one prescription for buprenorphine-naloxone between March 2012 and July 2017. MEASUREMENTS: Percentage of patients tested for hepatis B, hepatis C, HIV and liver functioning; percentage of patients with urine drug screens and number of urine drug screens; continuous use of buprenorphine-naloxone for at least 180 days; co-use of benzodiazepines; number of outpatient visits with and without an OUD diagnosis. FINDINGS: PA was significantly associated with a lower likelihood of testing for hepatitis B [-3.5, 95% confidence interval (CI) = -4.4, -2.7] and C (-5.9, 95% CI = -6.9, -4.9), but the findings were inconclusive as to whether or not there was a difference in HIV (-1.1, 95% CI = -2.5, 0.4) or liver function testing (1.3, 95% CI = -0.1, 2.7). PA was associated with a lower likelihood of urine drug screening (-25.5, 95% CI = -26.8, -24.1) and with fewer drug screens (-2.5, 95% CI = -3.0, -2.1). Findings were inconclusive as to whether or not there was a difference in continuous use of buprenorphine-naloxone (0.3, 95% CI = -1.2, 1.8). PA was associated with fewer outpatient visits (-2.1, 95% CI = -3.0, -1.2) and fewer outpatient visits with an OUD diagnosis (-1.7, 95% CI = -2.1, -1.3). PA was associated with a lower likelihood of filling benzodiazepine prescriptions before and after buprenorphine-naloxone induction (-28.9, 95% CI = -29.6, -28.3) but a greater likelihood of only using benzodiazepines after buprenorphine-naloxone induction (10.6, 95% CI = 9.3, 11.8). CONCLUSIONS: US Medicare patients subject to prior authorization for buprenorphine-naloxone are not more likely to receive high-quality treatment for opioid use disorder than patients not subject to prior authorization.

Prior Authorization for Opioid Use Disorder Versus Pain Medications: Lessons Learned for Parity Enforcement.

OBJECTIVE: This study characterized the use of prior authorization for opioid use disorder medications as compared with that for opioid pain medications in the United States among Medicare Part D plans. METHOD: Medicare Part D formulary data from 2017-2019 were used to describe differences in prior authorization between opioid use disorder medications and opioid pain medications. RESULTS: In 2017, 72% of Medicare Part D formularies required prior authorization for brand buprenorphine-naloxone, whereas 6% of formularies required prior authorization for brand oxycodone. In 2019, 3% of formularies required prior authorization for brand buprenorphine-naloxone, whereas 16% of formularies required prior authorization for brand oxycodone. Throughout the study period, other formulary restrictions such as quantity limits were similar for both medications. CONCLUSIONS: The disparate use of prior authorization in 2017 for opioid use disorder medications as compared with opioid pain medications suggests that formulary decision making may be inconsistent between medications used to treat substance use disorders and those used to treat pain. If Part D formularies publicly released their decision-making criteria, then there would be a greater understanding of why prior authorization was differentially applied. Greater transparency would help ensure that formulary decisions are not the result of biases and stigma toward substance use disorders.

Estimating Crime Laboratory Efficiency in the Testing of Sexual Assault Kits.

Over the past decade, the large numbers of untested sexual assault kits (SAKs) have been highlighted as a systematic problem that jeopardizes or delays justice for victims. Considering the benefits of testing SAKs, researchers have worked to shed light on why sexual assault evidence has not been effectively submitted to and processed by crime laboratories. Missing from this discourse has been an understanding of the types of practices or qualities that encourage efficiency in the testing of SAKs in crime laboratories. We analyzed results of a national survey administered to all publicly funded state and local crime laboratories (N = 132 respondents) to provide critical information about (i) the extent to which laboratories are testing all of the SAKs possible given the resources they have available; and (ii) the impact that staffing, equipment, policies, and other practices have on SAK testing efficiency. We find that the average laboratory tests only about 69% of the SAKs possible given the resources available to them. However, although technical inefficiencies explain a large proportion of the number of untested SAKs, the accumulation of untested SAKs must also be attributed to laboratories having insufficient resources (e.g., too few forensic analysts). Moreover, results from stochastic frontier models show that doubling the number of forensic analysts in the typical laboratory would allow them to expand their SAK testing capacity by nearly 50%. Implications of these findings are discussed as they relate to the prioritization of resources for crime laboratories, which often operate under strict budgetary realities.

Association of Formulary Prior Authorization Policies With Buprenorphine-Naloxone Prescriptions and Hospital and Emergency Department Use Among Medicare Beneficiaries.

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 buprenorphine-naloxone 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.

Medicaid Accountable Care Organizations in Four States: Implementation and Early Impacts.

Policy Points 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.

Medical cannabis legalization and state-level prevalence of serious mental illness in the National Survey on Drug Use and Health (NSDUH) 2008-2015.

Although research has established a link between cannabis legalization and use, and cannabis use and mental health, the relationship between medical cannabis legalization and mental health remains uncharacterized. This analysis investigated the relationship between state medical cannabis laws (restrictive, i.e. covering a narrow set of medical conditions; or liberal, i.e. covering a broad range of medical conditions), whether the law permits patients to petition their physician to approve medical cannabis use for specific medical conditions, and state prevalence of serious mental illness (SMI) in the National Survey of Drug Use and Health 2008-2015. In a covariate-adjusted meta-regression, liberal laws were significantly associated with higher prevalence of SMI (Coeff = 0.003, SE = 0.001, p < .001). Restrictive laws (Coeff = 0.001, SE = 0.001, p = .285) and the ability to petition physician approval (Coeff = -0.001, SE = 0.001, p = .140) were non-significant. When added to the model, state past-year cannabis use was significantly associated with higher prevalence of SMI (Coeff = 0.037, SE = 0.015, p = .018), liberal laws remained significant (Coeff = 0.002, SE = 0.001, p = .015), and restrictive laws (Coeff = -0.0001, SE = 0.001, p = .945) and the ability to petition a physician (Coeff = 0.001, SE = 0.001, p = .290) remained non-significant. Medical cannabis laws are likely related to state mental health, and a higher prevalence of cannabis use partially explains this relationship.

Impact of Medical Homes on Expenditures and Utilization for Beneficiaries With Behavioral Health Conditions.

OBJECTIVE: Individuals with behavioral health conditions may benefit from enhanced care management provided by a patient-centered medical home (PCMH). In late 2011 and early 2012 Medicare began participating in PCMH initiatives in eight states through the Multi-Payer Advanced Primary Care Practice (MAPCP) demonstration. This study examined how the initiatives addressed the needs of patients with behavioral health conditions and the impacts of the demonstration on expenditures and utilization for this population. METHODS: Semistructured interviews provided insight into states' approaches to improving care, and multivariate difference-in-difference regressions of Medicare and Medicaid claims data were used to model changes in utilization and expenditures, comparing Medicare and Medicaid beneficiaries with behavioral health conditions in MAPCP demonstration practices with similar beneficiaries in non-PCMH primary care practices. Utilization included inpatient admissions and emergency department visits for all causes and for behavioral health conditions and outpatient visits for behavioral health conditions. Expenditure outcomes included expenditures for all services and those with a principal diagnosis of a behavioral health condition. RESULTS: Practices reported screening more patients for behavioral health conditions, linking patients to community-based behavioral health resources, and hiring behavioral health specialists to provide care. Several states embarked on unique initiatives to improve access to behavioral health services. However, few significant associations were found between participation in the MAPCP demonstration and utilization and expenditures for behavioral health services. CONCLUSIONS: Even though PCMHs made concerted efforts to improve access to care for their patients with behavioral health conditions, few substantial changes in patterns of care were noted.

Estimation of Breast Cancer Incident Cases and Medical Care Costs Attributable to Alcohol Consumption Among Insured Women Aged <45 Years in the U.S.

INTRODUCTION: This study estimated the percentage of breast cancer cases, total number of incident cases, and total annual medical care costs attributable to alcohol consumption among insured younger women (aged 18-44 years) by type of insurance and stage at diagnosis. METHODS: The study used the 2012-2013 National Survey on Drug Use and Health, cancer incidence data from two national registry programs, and published relative risk measures to estimate the: (1) alcohol-attributable fraction of breast cancer cases among younger women by insurance type; (2) total number of breast cancer incident cases attributable to alcohol consumption by stage at diagnosis and insurance type among younger women; and (3) total annual medical care costs of treating breast cancer incident cases attributable to alcohol consumption among younger women. Analyses were conducted in 2016; costs were expressed in 2014 U.S. dollars. RESULTS: Among younger women enrolled in Medicaid, private insurance, and both groups, 8.7% (95% CI=7.4%, 10.0%), 13.8% (95% CI=13.3%, 14.4%), and 12.3% (95% CI=11.4%, 13.1%) of all breast cancer cases, respectively, were attributable to alcohol consumption. Localized stage was the largest proportion of estimated attributable incident cases. The estimated total number of breast cancer incident alcohol-attributable cases was 1,636 (95% CI=1,570, 1,703) and accounted for estimated total annual medical care costs of $148.4 million (95% CI=$140.6 million, $156.1 million). CONCLUSIONS: Alcohol-attributable breast cancer has estimated medical care costs of nearly $150 million per year. The current findings could be used to support evidence-based interventions to reduce alcohol consumption in younger women.

A new methodological approach to adjust alcohol exposure distributions to improve the estimation of alcohol-attributable fractions.

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.