Racial Inequality in Receipt of Medications for Opioid Use Disorder.

BACKGROUND: Since 2010, Black persons in the United States have had a greater increase in opioid overdose-related mortality than other groups, but national-level evidence characterizing racial and ethnic disparities in the use of medications for opioid use disorder (OUD) is limited. METHODS: We used Medicare claims data from the 2016-2019 period for a random 40% sample of fee-for-service beneficiaries who were Black, Hispanic, or White; were eligible for Medicare owing to disability; and had an index event related to OUD (nonfatal overdose treated in an emergency department or inpatient setting, hospitalization with injection drug use-related infection, or inpatient or residential rehabilitation or detoxification care). We measured the receipt of medications to treat OUD (buprenorphine, naltrexone, and naloxone), the receipt of high-risk medications (opioid analgesics and benzodiazepines), and health care utilization, all in the 180 days after the index event. We estimated differences in outcomes according to race and ethnic group with adjustment for beneficiary age, sex, index event, count of chronic coexisting conditions, and state of residence. RESULTS: We identified 25,904 OUD-related index events among 23,370 beneficiaries, with 3937 events (15.2%) occurring among Black patients, 2105 (8.1%) among Hispanic patients, and 19,862 (76.7%) among White patients. In the 180 days after the index event, patients received buprenorphine after 12.7% of events among Black patients, after 18.7% of those among Hispanic patients, and after 23.3% of those among White patients; patients received naloxone after 14.4%, 20.7%, and 22.9%, respectively; and patients received benzodiazepines after 23.4%, 29.6%, and 37.1%, respectively. Racial differences in the receipt of medications to treat OUD did not change appreciably from 2016 to 2019 (buprenorphine receipt: after 9.1% of index events among Black patients vs. 21.6% of those among White patients in 2016, and after 14.1% vs. 25.5% in 2019). In all study groups, patients had multiple ambulatory visits in the 180 days after the index event (mean number of visits, 6.6 after events among Black patients, 6.7 after events among Hispanic patients, and 7.6 after events among White patients). CONCLUSIONS: Racial and ethnic differences in the receipt of medications to treat OUD after an index event related to this disorder among patients with disability were substantial and did not change over time. The high incidence of ambulatory visits in all groups showed that disparities persisted despite frequent health care contact. (Funded by the National Institute on Drug Abuse and the National Institute on Aging.).

Medications for Alcohol Use Disorder: Rates and Predictors of Prescription Order and Fill in Outpatient Settings.

BACKGROUND: Alcohol use disorders (AUD) are prevalent and responsible for substantial morbidity and mortality; yet efficacious treatments are underused. Previous studies have identified demographic and clinical predictors of medication fills, yet these studies typically do not include patients who were prescribed a medication but did not fill it. OBJECTIVES: To examine rates of and factors associated with prescription order and prescription fill for medications for AUD (MAUD) among individuals diagnosed with AUD in outpatient settings. DESIGN: In a cross-sectional analysis, we used multivariate logistic regression to identify factors associated with prescription order and fill. PATIENTS: We used data from the Optum Labs Data Warehouse that linked 2016-2021 de-identified claims and electronic health record (EHR) data, allowing us to observe prescription orders and whether they were filled. We identified 14,674 patients aged ≥ 18 who had an index outpatient encounter with an AUD diagnosis in the EHR. KEY MEASURES: We computed the proportion for whom a MAUD prescription was ordered within 1 year of index visit, and for whom one was filled within 30 days of the order. KEY RESULTS: 5.8% of the sample had a MAUD prescription order within 1 year of their index visit. Among those with an order, 87% filled their MAUD prescription within 30 days of receipt (i.e., 5.1% of full sample). After multivariable adjustment, receipt of a MAUD prescription order was more likely for patients who were female (adjusted odds ratio (aOR) [95%CI] = 1.44 [1.24-1.67]), or had moderate or severe AUD (1.74 [1.50-2.01]). Patients receiving an order were more likely to fill it if they had a comorbid mental disorder (1.64 [1.09-2.49]). CONCLUSIONS: The low rate of prescription orders was notable. Low use of MAUD appears to result chiefly from prescription order decisions, rather than from prescription fill decisions made by patients.

Changes in Healthcare Spending Attributable to High Deductible Health Plan Offer Among Enrollees with Comorbid Substance Use Disorder and Cardiovascular Disease.

BACKGROUND: The rise in prevalence of high deductible health plans (HDHPs) in the United States may raise concerns for high-need, high-utilization populations such as those with comorbid chronic conditions. In this study, we examine changes in total and out-of-pocket (OOP) spending attributable to HDHPs for enrollees with comorbid substance use disorder (SUD) and cardiovascular disease (CVD). METHODS: We used de-identified administrative claims data from 2007 to 2017. SUD and CVD were defined using algorithms of ICD 9 and 10 codes and HEDIS guidelines. The main outcome measures of interest were spending measure for all non-SUD/CVD-related services, SUD-specific services, and CVD-specific services, for all services and medications specifically. We assessed both total and OOP spending. We used an intent-to-treat two-part model approach to model spending and computed the marginal effect of HDHP offer as both the dollar change and percent change in spending attributable to HDHP offer. RESULTS: Our sample included 33,684 enrollee-years and was predominantly white and male with a mean age of 53 years. The sample had high demonstrated substantial healthcare utilization with 94% using any non-SUD/CVD services, and 84% and 78% using SUD and CVD services, respectively. HDHP offer was associated with a 17.0% (95% CI = [0.07, 0.27] increase in OOP spending for all non-SUD/CVD services, a 21.1% (95% CI = [0.11, 0.31]) increase in OOP spending for all SUD-specific services, and a 13.1% (95% CI = [0.04, 0.23]) increase in OOP spending for all CVD-specific services. HDHP offer was also associated with a significant increase in OOP spending on non-SUD/CVD-specific medications and SUD-specific medications, but not CVD-specific medications. CONCLUSIONS: This study suggests that while HDHPs do not change overall levels of annual spending among enrollees with comorbid CVD and SUD, they may increase the financial burden of healthcare services by raising OOP costs, which could negatively impact this high-need and high-utilization population.

High-deductible Health Plans and Nonfatal Opioid Overdose.

OBJECTIVES: Opioid-related overdose is a public health emergency in the United States. Meanwhile, high-deductible health plans (HDHPs) have become more prevalent in the United States over the last 2 decades, raising concern about their potential for discouraging high-need populations, like those with opioid use disorder (OUD), from engaging in care that may mitigate the probability of overdose. This study assesses the impact of an employer offering an HDHP on nonfatal opioid overdose among commercially insured individuals with OUD in the United States. RESEARCH DESIGN: We used deidentified insurance claims data from 2007 to 2017 with 97,788 person-years. We used an intent-to-treat, difference-in-differences regression framework to estimate the change in the probability of a nonfatal opioid overdose among enrollees with OUD whose employers began offering an HDHP insurance option during the study period compared with the change among those whose employer never offered an HDHP. We also used an event-study model to account for dynamic time-varying treatment effects. RESULTS: Across both comparison and treatment groups, 2% of the sample experienced a nonfatal opioid overdose during the study period. Our primary model and robustness checks revealed no impact of HDHP offer on the probability of a nonfatal overdose. CONCLUSIONS: Our study suggests that HDHP offer was not associated with an observed increase in the probability of nonfatal opioid overdose among commercially insured person-years with OUD. However, given the strong evidence that medications for OUD (MOUD) can reduce the risk of overdose, research should explore which facets of insurance design may impact MOUD use.

Measurement Approaches to Estimating Methadone Continuity in Opioid Use Disorder Care.

BACKGROUND: Long-term treatment with medications for opioid use disorder (OUD), including methadone, is lifesaving. There has been little examination of how to measure methadone continuity in claims data. OBJECTIVES: To develop an approach for measuring methadone continuity in claims data, and compare estimates of methadone versus buprenorphine continuity. RESEARCH DESIGN: Observational cohort study using de-identified commercial claims from OptumLabs Data Warehouse (January 1, 2017-June 30, 2021). SUBJECTS: Individuals diagnosed with OUD, ≥1 methadone or buprenorphine claim and ≥180 days continuous enrollment (N=29,633). MEASURES: OUD medication continuity: months with any use, days of continuous use, and proportion of days covered. RESULTS: 5.4% (N=1607) of the study cohort had any methadone use. Ninety-seven percent of methadone claims (N=160,537) were from procedure codes specifically used in opioid treatment programs. Place of service and primary diagnosis codes indicated that several methadone procedure codes were not used in outpatient OUD care. Methadone billing patterns indicated that estimating days-supply based solely on dates of service and/or procedure codes would yield inaccurate continuity results and that an approach incorporating the time between service dates was more appropriate. Among those using methadone, mean [s.d.] months with any use, days of continuous use, and proportion of days covered were 4.8 [1.8] months, 79.7 [73.4] days, and 0.64 [0.36]. For buprenorphine, the corresponding continuity estimates were 4.6 [1.9], 80.7 [70.0], and 0.73 [0.35]. CONCLUSIONS: Estimating methadone continuity in claims data requires a different approach than that for medications largely delivered by prescription fills, highlighting the importance of consistency and transparency in measuring methadone continuity across studies.

Long-Term Prospects for Telemedicine in Opioid Use Disorder (OUD) Treatment: Results from a Longitudinal Survey of OUD Clinicians.

BACKGROUND: During the pandemic, there was a dramatic shift to telemedicine for opioid use disorder (OUD) treatment. Little is known about how clinician attitudes about telemedicine use for OUD treatment are evolving or their preferences for future use. OBJECTIVE: To understand OUD clinician views of and preferences regarding telemedicine. DESIGN: Longitudinal survey (wave 1, December 2020; wave 2, March 2022). SUBJECTS: National sample of 425 clinicians who treat OUD. MAIN MEASURES: Self-reported proportion of OUD visits delivered via telemedicine (actual vs. preferred), comfort in using video visits for OUD, impact of telemedicine on work-related well-being. KEY RESULTS: The mean reported percentage of OUD visits delivered via telemedicine (vs. in person) dropped from 56.9% in December 2020 to 41.5% in March 2022; the mean preferred post-pandemic percentage of OUD visits delivered via telemedicine was 34.8%. Responses about comfort in using video visits for different types of OUD patients remained similar over time despite clinicians having substantially more experience with telemedicine by spring 2022 (e.g., 35.8% vs. 36.0% report being comfortable using video visits for new patients). Almost three-quarters (70.9%) reported that most of their patients preferred to have the majority of their visits via telemedicine, and 76.7% agreed that the option to do video visits helped their patients remain in treatment longer. The majority (58.7%) reported that telemedicine had a positive impact on their work-related well-being, with higher rates of a positive impact among those who completed training more recently (68.5% of those with < 10 years, 62.1% with 10-19 years, and 45.8% with 20 + years, p < 0.001). CONCLUSIONS: While many surveyed OUD clinicians were not comfortable using telemedicine for all types of patients, most wanted telemedicine to account for a substantial fraction of OUD visits, and most believed telemedicine has had positive impacts for themselves and their patients.

Prescribing Medications for Alcohol Use Disorder: A Qualitative Study of Primary Care Physician Decision Making.

PURPOSE: Over 29 million Americans have alcohol use disorder (AUD). Though there are effective medications for AUD (MAUD) that can be prescribed within primary care, they are underutilized. We aimed to explore how primary care physicians familiar with MAUD make prescribing decisions and to identify reasons for underuse of MAUD within primary care. METHODS: We conducted semistructured interviews with 19 primary care physicians recruited from a large online database of medical professionals. Physicians had to have started a patient on MAUD within the last 6 months in an outpatient setting. Inductive and deductive thematic analysis was informed by the theory of planned behavior. RESULTS: Physicians endorsed that it is challenging to prescribe MAUD due to several reasons, including: (1) somewhat negative personal beliefs about medication effectiveness and likelihood of patient adherence; (2) competing demands in primary care that make MAUD a lower priority; and, (3) few positive subjective norms around prescribing. To make MAUD prescribing a smaller component of their practice, physicians reported applying various rules of thumb to select patients for MAUD. These included recommending MAUD to the patients who seemed the most motivated to reduce drinking, those with the most severe AUD, and those who were also receiving other treatments for AUD. CONCLUSIONS: There is a challenging implementation context for MAUD due to competing demands within primary care. Future research should explore which strategies for identifying a subset of patients for MAUD are the most appropriate and most likely to improve population health and health equity.

Initiating Opioid Use Disorder Medication via Telemedicine During COVID-19: Implications for Proposed Reforms to the Ryan Haight Act.

BACKGROUND: The Ryan Haight Act generally requires a clinician to conduct an in-person visit before prescribing an opioid use disorder (OUD) medication. This requirement has impeded use of telemedicine to expand OUD treatment, and many policymakers have called for its removal. During the COVID-19 pandemic, beginning March 16, 2020, the requirement was temporarily waived. It is unclear whether clinicians who treat OUD patients perceive telemedicine to be a safe and effective means of OUD medication initiation. OBJECTIVE: To understand clinician use of and comfort level with using telemedicine to initiate patients on medication for opioid use disorder. DESIGN: National survey administered electronically via WebMD/Medscape's online clinician panel in fall 2020. PARTICIPANTS: A total of 602 clinicians (primary care providers, psychiatrists, nurse practitioners or certified nurse specialists, and physician assistants) participated in the survey. MAIN MEASURES: Frequency of video, audio-only, and in-person visits for medication initiation, comfort level with using video for new patient visits with OUD. KEY RESULTS: Clinicians varied substantially in their use of telemedicine for medication initiation. Approximately 25% used telemedicine for most initiations while 40% used only in-person visits. The majority (55.8%) expressed at least some discomfort with using telemedicine for treating new OUD patients, although clinicians with more OUD patients were less likely to express such discomfort. CONCLUSION: Findings suggest that a permanent relaxation of the Ryan Haight requirement may not result in widespread adoption of telemedicine for OUD medication initiation without additional supports or incentives.

Impact of High Deductible Health Plans on Continuous Buprenorphine Treatment for Opioid Use Disorder.

BACKGROUND: Long-term, continuous treatment with medication like buprenorphine is the gold standard for opioid use disorder (OUD). As high deductible health plans (HDHPs) become more prevalent in the commercial insurance market, they may pose financial barriers to people with OUD. OBJECTIVE: To estimate the impact of HDHPs on continuity of buprenorphine treatment, concurrent visits for counseling/psychotherapy and OUD-related evaluation and management, and out-of-pocket spending. DESIGN: Difference-in-differences analysis comparing trends in outcomes among enrollees whose employers offer an HDHP (treatment group) to enrollees whose employers never offer an HDHP (comparison group). PARTICIPANTS: Enrollees with OUD from a national sample of commercial health insurance plans during 2007-2017 who initiate buprenorphine treatment. MAIN MEASURES: Number of days of continuous buprenorphine treatment; probabilities of continuous buprenorphine treatment ≥30, ≥90, ≥180, and ≥365 days; probability of concurrent (i.e., within the same month) behavioral therapy (i.e., counseling or psychotherapy); probability of concurrent OUD-related evaluation and management visits; proportions of buprenorphine treatment episodes with counseling/psychotherapy and evaluation and management visits; and out-of-pocket (OOP) spending on buprenorphine, behavioral therapy, and evaluation and management visits. KEY RESULTS: HDHPs were associated with an average increase of $98 (95% CI: $48, $150) on OOP spending on buprenorphine per treatment episode but no change in the number of days of continuous buprenorphine treatment or concurrent use of related services. CONCLUSIONS: HDHPs do not reduce continuity of buprenorphine treatment among commercially insured enrollees with OUD but may increase financial burden for this population.

Prescription Drug Spending in Fee-for-Service Medicare, 2008-2019.

Importance: Prescription drug spending is a topic of increased interest to the public and policymakers. However, prior assessments have been limited by focusing on retail spending (Part D-covered drugs), omitting clinician-administered (Part B-covered) drug spending, or focusing on all fee-for-service Medicare beneficiaries, regardless of their enrollment into prescription drug coverage. Objective: To estimate the proportion of health care spending contributed by prescription drugs and to assess spending for retail and clinician-administered prescriptions. Design, Setting, and Participants: Descriptive, serial, cross-sectional analysis of a 20% random sample of fee-for-service Medicare beneficiaries in the United States from 2008 to 2019 who were continuously enrolled in Parts A (hospital), B (medical), and D (prescription drug) benefits, and not in Medicare Advantage. Exposure: Calendar year. Main Outcomes and Measures: Net spending on retail (Part D-covered) and clinician-administered (Part B-covered) prescription drugs; prescription drug spending (spending on Part B-covered and Part D-covered drugs) as a percentage of total per-capita health care spending. Measures were adjusted for inflation and for postsale rebates (for Part D-covered drugs). Results: There were 3 201 284 beneficiaries enrolled in Parts A, B, and D in 2008 and 4 502 718 in 2019. In 2019, beneficiaries had a mean (SD) age of 71.7 (12.0) years, documented sex was female for 57.7%, and 69.5% had no low-income subsidies. Total per-capita spending was $16 345 in 2008 and $20 117 in 2019. Comparing 2008 with 2019, per-capita Part A spending was $7106 (95% CI, $7084-$7128) vs $7120 (95% CI, $7098-$7141), Part B drug spending was $720 (95% CI, $713-$728) vs $1641 (95% CI, $1629-$1653), Part B nondrug spending was $5113 (95% CI, $5105-$5122) vs $6702 (95% CI, $6692-$6712), and Part D net spending was $3122 (95% CI, $3117-$3127) vs $3477 (95% CI, $3466-$3489). The proportion of total annual spending attributed to prescription drugs increased from 24.0% in 2008 to 27.2% in 2019, net of estimated rebates and discounts. Conclusions and Relevance: In 2019, spending on prescription drugs represented approximately 27% of total spending among fee-for-service Medicare beneficiaries enrolled in Part D, even after accounting for postsale rebates.

Patterns of Mental Health Care Before Initiation of Telemental Health Services.

BACKGROUND: Use of telemental health has increased among rural Medicare beneficiaries, particularly among individuals with serious mental illness (SMI). Little is known about what leads to the initiation of telemental health. OBJECTIVE: To categorize the different patterns of mental health care use before initiation of telemental health services among individuals with SMI. METHODS: A cohort of rural beneficiaries with SMI (defined as schizophrenia/related psychotic disorders or bipolar disorder) with an index telemental health visit in 2010-2017 was built using claims for a 20% random sample of fee-for-service Medicare beneficiaries. The authors used latent class analysis to identify classes of mental health care use in the 6 months before the index telemental health visits. Across the classes, the authors also described characteristics of index and subsequent mental health visits. RESULTS: The cohort included 4930 rural Medicare beneficiaries with SMI. Three classes of mental health care use before initiation of telemental health were identified. The largest class (n=3066) had minimal use of primary care provider mental health care and the second largest class (n=1537) had minimal specialty mental health care. The smallest class (n=327) was characterized by recent hospitalization or emergency department care. In the overall cohort, index visits were frequently established visits and were often with specialty prescribers. CONCLUSIONS: Our findings highlight 3 distinct patterns of care before telemental health initiation, providing insight into the role that telemedicine may play in mental health care for rural Medicare beneficiaries with SMI. Overall, telemental health was most often used to maintain care with existing providers.

Trends in Contracting and Common Ownership Between Hospice Agencies and Nursing Homes.

BACKGROUND: In recent years, policymakers have paid particular attention to the emergence of a robust for-profit hospice sector and increased hospice use by nursing home residents. Previous research has explored financial incentives for nursing home-hospice use, but there has been limited research on nursing home-hospice partnerships and none on the extent of nursing home-hospice common ownership. OBJECTIVE: To describe trends in nursing home-hospice contracting and common ownership and to identify potential tradeoffs in care provided by nursing homes and hospice agencies that share common ownership. RESEARCH DESIGN: Retrospective cohort study of nursing home-hospice patients between 2005 and 2015. RESULTS: Between 2005 and 2015, the number of hospice agencies and nursing homes with common ownership grew substantially, now representing almost 1-in-5 providers in each sector. Relative to individuals using hospice in nursing homes without common ownership, adjusted analyses found that individuals receiving hospice from a commonly owned agency had a greater likelihood of having stays of 90 days or more [odds ratio (OR)=1.06; 95% confidence interval (CI), 1.02-1.10], having a stay resulting in a live discharge (OR=1.06; 95% CI, 1.02-1.11), and having at least 1 registered nurse/licensed practical nurse visit during the last 3 days of life (OR=1.17; 95% CI, 1.05-1.29); these individuals also had a lower mean visit hours per day (-0.07; P=0.003). CONCLUSIONS: Common ownership between hospice agencies and nursing homes is an emerging trend that reflects a broader push toward consolidation in the health care sector. Our analyses highlight potential concerns relevant to Medicare payment policy and are a first step toward improving our understanding of these trends and their implications.

Medication Utilization for Alcohol Use Disorder in a Commercially Insured Population.

OBJECTIVE: Examine patterns of alcohol use disorder (AUD) medication use and identify factors associated with prescription fill among commercially insured individuals with an index AUD visit. DESIGN: Using 2008-2018 claims data from a large national insurer, estimate days to first AUD medication using cause-specific hazards approach to account for competing risk of benefits loss. PARTICIPANTS: Aged 17-64 with ≥ 1 AUD visit. MAIN MEASURE: Days to AUD medication fill. KEY RESULTS: A total of 13.3% of the 151,128 with an index visit filled an AUD prescription after that visit, while 69.8% lost benefits before filling and 17.0% remained enrolled but did not fill (median days observed = 305). Almost half (46.3%) of those who filled a prescription received substance use disorder (SUD) inpatient care within 7 days before the fill, and 63.4% received SUD outpatient care. Likelihood of medication use was higher for those aged 26-35, 36-45, and 46-55 years relative to 56-64 years (e.g., 26-35: hazard ratio = 1.29 [95% confidence interval 1.23-1.36]); those diagnosed with moderate/severe AUD (2.05 [1.98-2.12]), co-occurring opioid use disorder (OUD) (1.33 [1.26-1.39]), or severe mental illness (1.31 [1.27-1.35]); those with a chronic alcohol-related diagnosis (1.08 [1.04-1.12]); and those whose index visit was in an inpatient/emergency department (1.27 [1.23-1.31]) or intermediate care setting (1.13 [1.07-1.20]) relative to outpatient. Likelihood of use was higher in later years relative to 2008 (e.g., 2018:2.02 [1.89-2.15]) and higher for those who received the majority of AUD care in a practice with a psychiatrist/addiction medicine specialist (1.13 [1.10-1.16]). Likelihood of use was lower for those diagnosed with a SUD other than AUD or OUD (0.88 [0.85-0.92]), those with an acute alcohol-related condition (0.79 [0.75-0.84]), and males (0.71 [0.69-0.73]). CONCLUSIONS: While AUD medication use increased and was more common among individuals with greater severity, few patients who could benefit from medications are using them. More efforts are needed to identify and treat individuals in non-acute care settings earlier in their course of AUD.

Telemental Health and US Rural-Urban Differences in Specialty Mental Health Use, 2010-2017.

Objectives. To examine whether growing use of telemental health (TMH) has reduced the rural-urban gap in specialty mental health care use in the United States.Methods. Using 2010-2017 Medicare data, we analyzed trends in the rural-urban difference in rates of specialty visits (in-person and TMH).Results. Among rural beneficiaries diagnosed with schizophrenia or bipolar disorder, TMH use grew by 425% over the 8 years and, in higher-use rural areas, accounted for one quarter of all specialty mental health visits in 2017. Among patients with schizophrenia or bipolar disorder, TMH visits differentially grew in rural areas by 0.14 visits from 2010 to 2017. This growth partially offset the 0.42-visit differential decline in in-person visits in rural areas. In net, the gap between rural and urban patients in specialty visits was larger by 2017.Conclusions. TMH has improved access to specialty care in rural areas, particularly for individuals diagnosed with schizophrenia or bipolar disorder. While growth in TMH use has been insufficient to eliminate the overall rural-urban difference in specialty care use, this difference may have been larger if not for TMH.Public Health Implications. Targeted policy to extend TMH to underserved areas may help offset declines in in-person specialty care.

Association between physician adoption of a new oral anti-diabetic medication and Medicare and Medicaid drug spending.

BACKGROUND: In the United States, there is well-documented regional variation in prescription drug spending. However, the specific role of physician adoption of brand name drugs on the variation in patient-level prescription drug spending is still being investigated across a multitude of drug classes. Our study aims to add to the literature by determining the association between physician adoption of a first-in-class anti-diabetic (AD) drug, sitagliptin, and AD drug spending in the Medicare and Medicaid populations in Pennsylvania. METHODS: We obtained physician-level data from QuintilesIMS Xponent™ database for Pennsylvania and constructed county-level measures of time to adoption and share of physicians adopting sitagliptin in its first year post-introduction. We additionally measured total AD drug spending for all Medicare fee-for-service and Part D enrollees (N = 125,264) and all Medicaid (N = 50,836) enrollees with type II diabetes in Pennsylvania for 2011. Finite mixture model regression, adjusting for patient socio-demographic/clinical characteristics, was used to examine the association between physician adoption of sitagliptin and AD drug spending. RESULTS: Physician adoption of sitagliptin varied from 44 to 99% across the state's 67 counties. Average per capita AD spending was $1340 (SD $1764) in Medicare and $1291 (SD $1881) in Medicaid. A 10% increase in the share of physicians adopting sitagliptin in a county was associated with a 3.5% (95% CI: 2.0-4.9) and 5.3% (95% CI: 0.3-10.3) increase in drug spending for the Medicare and Medicaid populations, respectively. CONCLUSIONS: In a medication market with many choices, county-level adoption of sitagliptin was positively associated with AD spending in Medicare and Medicaid, two programs with different approaches to formulary management.

Coverage of Medications That Treat Opioid Use Disorder and Opioids for Pain Management in Marketplace Plans, 2017.

BACKGROUND: Efficacious medications to treat opioid use disorders (OUDs) have been slow to diffuse into practice, and insurance coverage limits may be one important barrier. OBJECTIVES: To compare coverage for medications used to treat OUDs and opioids commonly prescribed for pain management in plans offered on the 2017 Health Insurance Marketplace exchanges. RESEARCH DESIGN: We identified a sample of 100 plans offered in urban and in rural counties on the 2017 Marketplaces, weighting by population. We accessed publicly available plan coverage information on healthcare.gov for states with a federally facilitated exchange, the state exchange website for state-based exchanges, and insurer websites. RESULTS: About 14% of plans do not cover any formulations of buprenorphine/naloxone. Plans were more likely to require prior authorization for any of the covered office-based buprenorphine or naltrexone formulations preferred for maintenance OUD treatment (ie, buprenorphine/naloxone, buprenorphine implants, injectable long-acting naltrexone) than of short-acting opioid pain medications (63.6% vs. 19.4%; P<0.0001). Only 10.6% of plans cover implantable buprenorphine, 26.1% cover injectable naltrexone, and 73.4% cover at least 1 abuse-deterrent opioid pain medication. CONCLUSIONS: Many Marketplace plans either do not cover or require prior authorization for coverage of OUD medications, and these restrictions are often more common for OUD medications than for short-acting opioid pain medications. Regulators tasked with enforcement of the Mental Health Parity and Addiction Equity Act, which requires that standards for formulary design for mental health and substance use disorder drugs be comparable to those for other medications, should focus attention on formulary coverage of OUD medications.