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.

Anxiety and Depression Symptoms After the Dobbs Abortion Decision.

Importance: In 2022, the US Supreme Court abolished the federal right to abortion in the Dobbs v Jackson Women's Health Organization decision. In 13 states, abortions were immediately banned via previously passed legislation, known as trigger laws. Objective: To estimate changes in anxiety and depression symptoms following the Dobbs decision among people residing in states with trigger laws compared with those without them. Design, Setting, and Participants: Using the nationally representative repeated cross-sectional Household Pulse Survey (December 2021-January 2023), difference-in-differences models were estimated to examine the change in symptoms of depression and anxiety after Dobbs (either the June 24, 2022, Dobbs decision, or its May 2, 2022, leaked draft benchmarked to the baseline period, prior to May 2, 2022) by comparing the 13 trigger states with the 37 nontrigger states. Models were estimated for the full population (N = 718 753), and separately for 153 108 females and 102 581 males aged 18 through 45 years. Exposure: Residing in states with trigger laws following the Dobbs decision or its leaked draft. Main Outcomes and Measures: Anxiety and depression symptoms were measured via the Patient Health Questionnaire-4 ([PHQ-4]; range, 0-12; scores of more than 5 indicate elevated depression or anxiety symptoms; minimal important difference unknown). Results: The survey response rate was 6.04% overall, and 87% of respondents completed the PHQ-4. The population-weighted mean age was 48 years (SD, 17 years), and 51% were female. In trigger states, the mean PHQ-4 scores in the baseline period and after the Dobbs decision were 3.51 (95% CI, 3.44 to 3.59) and 3.81 (95% CI, 3.75 to 3.87), respectively, and in nontrigger states were 3.31 (95% CI, 3.27 to 3.34) and 3.49 (95% CI, 3.45 to 3.53), respectively. There was a significantly greater increase in the mean PHQ-4 score by 0.11 (95% CI, 0.06 to 0.16; P < .001) in trigger states vs nontrigger states. From baseline to after the draft was leaked, the change in PHQ-4 was not significantly different for those in trigger states vs nontrigger states (difference-in-differences estimate, 0.09; 95% CI, -0.03 to 0.21; P = .15). From baseline to after the Dobbs opinion, there was a significantly greater increase in mean PHQ-4 scores for those in trigger states vs nontrigger states among females aged 18 through 45 years (difference-in-differences estimate, 0.23; 95% CI, 0.08 to 0.37; P = .002). Among males aged 18 through 45 years, the difference-in-differences estimate was not statistically significant (0.14; 95% CI, -0.08 to 0.36; P = .23). Differences in estimates for males and females aged 18 through 45 were statistically significant (P = .02). Conclusions and Relevance: In this study of US survey data from December 2021 to January 2023, residence in states with abortion trigger laws compared with residence in states without such laws was associated with a small but significantly greater increase in anxiety and depression symptoms after the Dobbs decision.

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.

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.

Participation, Pricing, and Enrollment in a Health Insurance "Public Option": Evidence From Washington State's Cascade Care Program.

Policy Points Policymakers considering introduction of a health insurance "public option" to lower health spending and reduce the number of uninsured can learn from Washington State, which offered the nation's first public option ("Cascade Care") through its state exchange in 2021. This article examines insurer participation, pricing, and enrollment in the Washington public option. The public option was the lowest-premium standard silver plan in 9 of the 19 counties in which it was offered. Cascade Care is available solely through private insurers. Voluntary participation of these insurers and uncertainty about the willingness of providers to participate may have hindered greater premium reductions and enrollment in the public option's first year. CONTEXT: State and federal policymakers considering introduction of a health insurance "public option" can learn from Washington State, which established the nation's first public option, with coverage beginning in January 2021. Public option plans were offered voluntarily by private insurers through the Washington Health Benefit Exchange and were subject to state-mandated plan design and payment requirements. METHODS: We used plan data from the Washington Health Benefit Exchange, linked to data from the US Census Bureau, the American Hospital Association, and InterStudy. We compared geographic availability and premiums of, and enrollment in, public option and non-public option plans, as well as characteristics of counties where the public option was available and counties where the public option was the lowest-premium plan. FINDINGS: At least one public option plan was available in 19 of 39 counties and was the lowest-premium option in 9 of the 19 counties where it was available. Five insurers offered public option plans, including one new entrant to the state and one new entrant to the Exchange. While public option availability was more common in counties where the Exchange was bigger and more competitive, public option plans had the lowest premium in smaller, less competitive counties. In the first year, 1% of enrollees selected the public option, in part due to automatic reenrollment of the majority of returning enrollees in their 2020 plan. CONCLUSIONS: Public option plans offered a low-premium choice in counties that otherwise had fewer affordable plans, but voluntary participation of insurers and providers and accompanying uncertainty about participation hindered widespread and substantial premium reductions. States should consider tying public option participation by insurers and providers to other state programs and using decision support tools to promote active enrollment. Federal policymakers can support state efforts while considering establishment of a national public option.

Messages in prescription drug advertising for four chronic diseases, 2003-2016: A content analysis.

The objective of this study was to examine the frequency and content of messages related to pharmacological and evidence-based, non-pharmaceutical treatments in direct-to-consumer advertising (DTCA) for prescription drugs treating four chronic diseases in the United States. We used content coding to identify theory-informed categories of messages appearing in a large sample of heart disease, diabetes, depression, and osteoarthritis advertisements, appearing on national and local television between 2003 and 2016 (N = 11,347,070). The data were originally accessed in 2019 and analyzed in 2020-2021. The central message in all pharmaceutical DTCA was drug efficacy. Advertisements for diabetes and heart disease, but not depression or osteoarthritis, contained general (not central) messages about diet and exercise. Advertisements for heart disease primarily portrayed diet and exercise as insufficient for controlling the target health condition. No advertisements in our sample portrayed changes in diet or physical activity as an alternative to drugs. Pharmaceutical DTCA across health conditions employ similar strategies to promote use of the advertised drug but vary widely in whether and how they describe non-pharmaceutical treatments that complement or serve as alternatives to medications. Regulators should consider the potential spillover effects of non-pharmaceutical messages in pharmaceutical DTCA when considering future regulatory endeavors.

Scaling Interventions to Manage Chronic Disease: Innovative Methods at the Intersection of Health Policy Research and Implementation Science.

Policy implementation is a key component of scaling effective chronic disease prevention and management interventions. Policy can support scale-up by mandating or incentivizing intervention adoption, but enacting a policy is only the first step. Fully implementing a policy designed to facilitate implementation of health interventions often requires a range of accompanying implementation structures, like health IT systems, and implementation strategies, like training. Decision makers need to know what policies can support intervention adoption and how to implement those policies, but to date research on policy implementation is limited and innovative methodological approaches are needed. In December 2021, the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness and the Johns Hopkins Center for Mental Health and Addiction Policy convened a forum of research experts to discuss approaches for studying policy implementation. In this report, we summarize the ideas that came out of the forum. First, we describe a motivating example focused on an Affordable Care Act Medicaid health home waiver policy used by some US states to support scale-up of an evidence-based integrated care model shown in clinical trials to improve cardiovascular care for people with serious mental illness. Second, we define key policy implementation components including structures, strategies, and outcomes. Third, we provide an overview of descriptive, predictive and associational, and causal approaches that can be used to study policy implementation. We conclude with discussion of priorities for methodological innovations in policy implementation research, with three key areas identified by forum experts: effect modification methods for making causal inferences about how policies' effects on outcomes vary based on implementation structures/strategies; causal mediation approaches for studying policy implementation mechanisms; and characterizing uncertainty in systems science models. We conclude with discussion of overarching methods considerations for studying policy implementation, including measurement of policy implementation, strategies for studying the role of context in policy implementation, and the importance of considering when establishing causality is the goal of policy implementation research.

Disparities in exposure to television advertising of sugar-sweetened and non-nutritive sweetened beverages among U.S. adults and teens, 2007-2013.

The objective of this study was to estimate disparities in exposure to television advertising of sugar-sweetened and non-nutritive sweetened beverages among U.S. adults and teens. Data (2007-2013) came from the National Consumer Survey and included 115,510 adult respondents (age 18+) and 8635 teen respondents (age 12-17). The data was originally accessed in 2018 and analyzed in 2019-2020. The main outcomes were individual-level estimated exposure to advertisements for regular soda, diet soda, and energy/sport drinks. The main exposures were by race/ethnicity, household income, and educational attainment. Non-white adults (teens) were exposed to an estimated (per year) 101.5 (190.1) regular soda ads, 49.5 (61.2) diet soda ads, and 157.1 (279.6) energy/sport ads per year while white respondents were exposed to 97.5 (127.7) regular soda ads, 45.8 (44.2) diet soda ads, and 123.9 (192.0) energy/sport ads per year. Adult (teen) respondents who were non-white with low incomes and with low educational attainment were exposed to 4.7% (53.7%) more regular soda ads, 6.6% (43.8%) more diet ads, and 23.2% (56.2%) more energy/sport ads than respondents who were white with high incomes and high educational attainment. Demographic and socio-economic groups with a higher prevalence of obesity were exposed to significantly more advertisements for sugar-sweetened beverages. When evaluating potential policies to regulate marketing of sugar-sweetened and non-nutritive sweetened beverages, policymakers should consider the disparate exposure of at-risk populations to advertising of sugar-sweetened and non-nutritive sweetened beverages.

An examination of structure-function claims in dietary supplement advertising in the U.S.: 2003-2009.

Dietary supplement advertising cannot claim a causal link between the product and the treatment, prevention, or cure of a disease unless manufacturers seek approval from the FDA for a health claim. Manufacturers can make structure-function (S-F) claims without FDA approval linking a supplement to a body function or system using words such as "may help" or "promotes." These S-F claims are examined in this study in order to determine whether they mimic health claims for which the FDA requires stricter scientific evidence. Data include S-F claims in supplement advertisements (N=6179) appearing in US nationally circulated magazines (N=137) from 2003 to 2009. All advertisements were comprehensively coded for S-F claims, seals of approval, and other claims of guarantee. S-F claims associate supplements with a wide variety of health conditions, many of which are serious diseases and/or ailments. A significant number of the specific verbs used in these S-F claims are indicative of disease treatment/cure effects, thereby possibly mimicking health claims to the average consumer. The strength of the clinical associations made are largely unsubstantiated in the medical literature. Claims that a product is "scientifically proven" or "guaranteed" were largely unsubstantiated by clinical literature. Ads carrying externally validating seals of approval were highly prevalent. S-F claims that strongly mimic FDA-prohibited health claims are likely to create confusion in interpretation and possible public health concerns are discussed.

Employment in Office-Based and Intensive Behavioral Health Settings in the US, 2016-2021.

This study uses employment census data to show trends in behavioral health employment during and after the COVID-19 pandemic.

Job Flows Into and Out of Health Care Before and After the COVID-19 Pandemic.

Importance: Anecdotal evidence suggests that health care employers have faced increased difficulty recruiting and retaining staff in the wake of the COVID-19 pandemic. Empirical research is needed to understand the magnitude and persistence of these changes, and whether they have disproportionate implications for certain types of workers or regions of the country. Objective: To quantify the number of workers exiting from and entering into the health care workforce before and after the pandemic and to examine variations over time and across states and worker demographics. Design, Setting, and Participants: This cohort study used US Census Bureau state unemployment insurance data on job-to-job flows in the continental US to construct state-level quarterly exit and entry rates for the health care industry from January 2018 through December 2021 (Arkansas, Mississippi, and Tennessee were omitted due to missing data). An event study design was used to compute quarterly mean adjusted rates of job exit from and entry into the health care sector as defined by the North American Industry Classification System. Data were examined from January to June 2023. Exposure: The COVID-19 pandemic. Main Outcomes and Measures: The main outcomes were the mean adjusted health care worker exit and entry rates in each quarter by state and by worker demographics (age, gender, race and ethnicity, and education level). Results: In quarter 1 of 2020, there were approximately 18.8 million people (14.6 million females [77.6%]) working in the health care sector in our sample. The exit rate for health care workers increased at the onset of the pandemic, from a baseline quarterly mean of 5.9 percentage points in 2018 to 8.0 (95% CI, 7.7-8.3) percentage points in quarter 1 of 2020. Exit rates remained higher than baseline levels through quarter 4 of 2021, when the health care exit rate was 7.7 (95% CI, 7.4-7.9) percentage points higher than the 2018 baseline. In quarter 1 of 2020, the increase in health care worker exit rates was dominated by an increase in workers exiting to nonemployment (78% increase compared with baseline); in contrast, by quarter 4 of 2021, the exit rate was dominated by workers exiting to employment in non-health care sectors (38% increase compared with baseline). Entry rates into health care also increased in the postpandemic period, from 6.2 percentage points at baseline to 7.7 percentage points (95% CI, 7.4-7.9 percentage points) in the last quarter of 2021, suggesting increased turnover of health care staff. Compared with prepandemic job flows, the share of workers exiting health care after the pandemic who were female was disproportionately larger, and the shares of workers entering health care who were female or Black was disproportionately smaller. Conclusions and Relevance: Results of this cohort study suggest a substantial and persistent increase in health care workforce turnover after the pandemic, which may have long-lasting implications for workers' willingness to remain in health care jobs. Policymakers and health care organizations may need to act to prevent further losses of experienced staff.

Acquisitions of behavioral health treatment facilities from 2010 to 2021.

Private equity (PE) and other for-profit ownership of behavioral health (mental health and substance use) treatment facilities have become increasingly prevalent, but data on these acquisitions are not readily available. In this study, we describe a novel database that contains information on the universe of behavioral health acquisitions that occurred between 2010 and 2021. We found that the frequency of behavioral health facilities involved in acquisitions increased substantially, from 32 facilities in 2010 to 1330 in 2021. The total number of facilities involved in acquisitions was 2806. Most of these facilities provided outpatient services only (N = 2073) and offered only mental health services (N = 1428). Private equity-backed acquisitions accounted for around 60% of all acquisition activity (N = 1678 facilities PE, N = 1128 facilities other for-profit). 25% of acquired facilities were located within 20 miles of one another (N = 561), 50% occurred within 80 miles (N = 1403), and 75% occurred within 319 miles (N = 2104). Future research should evaluate the effects of this consolidation on behavioral healthcare access, quality, spending, and patient outcomes.

Licensure Policies May Help States Ensure Access To Opioid Use Disorder Medication In Specialty Addiction Treatment.

Despite the devastating toll of the overdose crisis in the United States, many addiction treatment programs do not offer medications for opioid use disorder (MOUD). Several states have incorporated MOUD requirements into their standards for treatment program licensure. This study examined policy officials' and treatment providers' perspectives on the implementation of these policies. During 2020-22, we conducted thirty-one semistructured interviews with forty policy officials and treatment providers in nine states identified through a legal analysis. Of these states, three states required treatment organizations to offer MOUD, and two prohibited organizations from denying admission to people receiving MOUD. Qualitative findings revealed that licensure policies were part of a broader effort to transition the specialty treatment system to a model of care more consistent with medical evidence; states perceived tension between raising quality standards and maintaining adequate treatment capacity; aligning other state policies with MOUD access goals facilitated implementation of the licensure requirement; and measuring compliance was challenging. Licensure may offer states an opportunity to take a more active role in ensuring access to effective treatment.

Deductible imputation in administrative medical claims datasets.

OBJECTIVE: To validate imputation methods used to infer plan-level deductibles and determine which enrollees are in high-deductible health plans (HDHPs) in administrative claims datasets. DATA SOURCES AND STUDY SETTING: 2017 medical and pharmaceutical claims from OptumLabs Data Warehouse for US individuals <65 continuously enrolled in an employer-sponsored plan. Data include enrollee and plan characteristics, deductible spending, plan spending, and actual plan-level deductibles. STUDY DESIGN: We impute plan deductibles using four methods: (1) parametric prediction using individual-level spending; (2) parametric prediction with imputation and plan characteristics; (3) highest plan-specific mode of individual annual deductible spending; and (4) deductible spending at the 80th percentile among individuals meeting their deductible. We compare deductibles' levels and categories for imputed versus actual deductibles. DATA COLLECTION/EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: All methods had a positive predictive value (PPV) for determining high- versus low-deductible plans of ≥87%; negative predictive values (NPV) were lower. The method imputing plan-specific deductible spending modes was most accurate and least computationally intensive (PPV: 95%; NPV: 91%). This method also best correlated with actual deductible levels; 69% of imputed deductibles were within $250 of the true deductible. CONCLUSIONS: In the absence of plan structure data, imputing plan-specific modes of individual annual deductible spending best correlates with true deductibles and best predicts enrollees in HDHPs.

Navigating addiction treatment during COVID-19: policy insights from state health leaders.

To mitigate pandemic-related disruptions to addiction treatment, US federal and state governments made significant changes to policies regulating treatment delivery. State health agencies played a key role in implementing these policies, giving agency leaders a distinct vantage point on the feasibility and implications of post-pandemic policy sustainment. We interviewed 46 state health agency and other leaders responsible for implementing COVID-19 addiction treatment policies across 8 states with the highest COVID-19 death rate in their census region. Semi-structured interviews were conducted from April through October 2022. Transcripts were analyzed using summative content analysis to characterize policies that interviewees perceived would, if sustained, benefit addiction treatment delivery long-term. State policies were then characterized through legal database queries, internet searches, and analysis of existing policy databases. State leaders viewed multiple pandemic-era policies as useful for expanding addiction treatment access post-pandemic, including relaxing restrictions for telehealth, particularly for buprenorphine induction and audio-only treatment; take-home methadone allowances; mobile methadone clinics; and out-of-state licensing flexibilities. All states adopted at least 1 of these policies during the pandemic. Future research should evaluate these policies outside of the acute COVID-19 pandemic context.

US payment policy for medications to treat opioid use disorder: landscape and opportunities.

Offering patients medications for opioid use disorder (MOUD) is the standard of care for opioid use disorder (OUD), but an estimated 75%-90% of people with OUD who could benefit from MOUD do not receive medication. Payment policy, defined as public and private payers' approaches to covering and reimbursing providers for MOUD, is 1 contributor to this treatment gap. We conducted a policy analysis and qualitative interviews (n = 21) and surveys (n = 31) with US MOUD payment policy experts to characterize MOUD insurance coverage across major categories of US insurers and identify opportunities for reform and innovation. Traditional Medicare, Medicare Advantage, and Medicaid all provide coverage for at least 1 formulation of buprenorphine, naltrexone, and methadone for OUD. Private insurance coverage varies by carrier and by plan, with methadone most likely to be excluded. The experts interviewed cautioned against rigid reimbursement models that force patients into one-size-fits-all care and endorsed future development and adoption of value-based MOUD payment models. More than 70% of experts surveyed reported that Medicare, Medicaid, and private insurers should increase payment for office- and opioid treatment program-based MOUD. Validation of MOUD performance metrics is needed to support future value-based initiatives.

Trends in Opioid Use Disorder Outpatient Treatment and Telehealth Utilization Before and During the COVID-19 Pandemic.

OBJECTIVE: The authors examined trends in opioid use disorder treatment and in-person and telehealth modalities before and after COVID-19 pandemic onset among patients who had received treatment prepandemic. METHODS: The sample included 13,113 adults with commercial insurance or Medicare Advantage and receiving opioid use disorder treatment between March 2018 and February 2019. Trends in opioid use disorder outpatient treatment, treatment with medications for opioid use disorder (MOUD), and in-person and telehealth modalities were examined 1 year before pandemic onset and 2 years after (March 2019-February 2022). RESULTS: From March 2019 to February 2022, the proportion of patients with opioid use disorder outpatient and MOUD visits declined by 2.8 and 0.3 percentage points, respectively. Prepandemic, 98.6% of outpatient visits were in person; after pandemic onset, at least 34.9% of patients received outpatient care via telehealth. CONCLUSIONS: Disruptions in opioid use disorder outpatient and MOUD treatments were marginal during the pandemic, possibly because of increased telehealth utilization.

Association between non-profit hospital community benefit spending and health outcomes.

OBJECTIVE: To determine if greater non-profit hospital spending for community benefits is associated with better health outcomes in the county where they are located. DATA SOURCES AND STUDY SETTING: Community benefit data from IRS Form 990/Schedule H was linked to health outcome data from Area Health Resource Files, Map the Meal Gap, and Medicare claims from the Center for Medicare and Medicaid Services at the county level. Counties with at least one non-profit hospital in the United States from 2015 to 2019 (N = 5469 across the 5 years) were included. STUDY DESIGN: We ran multiple regressions on community benefit expenditures linked with the number of health professionals, food insecurity, and adherence to diabetes and hypertension medication for each county. DATA COLLECTION: The three outcomes were chosen based on prior studies of community benefit and a recent survey sent to 12 health care executives across four regions of the U.S. Data on community benefit expenditures and health outcomes were aggregated at the county level. PRINCIPAL FINDINGS: Average hospital community benefit spending in 2019 was $63.6 million per county ($255 per capita). Multivariable regression results did not demonstrate significant associations of total community benefit spending with food insecurity or medication adherence for diabetes. Statistically significant associations with the number of health professionals per 1000 (coefficient, 12.10; SE, 0.32; p < 0.001) and medication adherence for hypertension (marginal effect, 0.27; SE, 0.09; p = 0.003) were identified, but both would require very large increases in community benefit spending to meaningfully improve outcomes. CONCLUSIONS: Despite varying levels of non-profit hospital community benefit investment across counties, higher community benefit expenditures are not associated with an improvement in the selected health outcomes at the county level. Hospitals can use this information to reassess community benefit strategies, while federal, state, and local governments can use these findings to redefine the measures of community benefit they use to monitor and grant tax exemption.