Lost in transition: A protocol for a retrospective, longitudinal cohort study for addressing challenges in opioid treatment for transition-age adults.

BACKGROUND: In the United States, there has been a concerning rise in the prevalence of opioid use disorders (OUD) among transition-age (TA) adults, 18 to 25-years old, with a disproportionate impact on individuals and families covered by Medicaid. Of equal concern, the treatment system continues to underperform for many young people, emphasizing the need to address the treatment challenges faced by this vulnerable population at a pivotal juncture in their life course. Pharmacotherapy is the most effective treatment for OUD, yet notably, observational studies reveal gaps in the receipt of and retention in medications for opioid use disorder (MOUD), resulting in poor outcomes for many TA adults in treatment. Few current studies on OUD treatment quality explicitly consider the influence of individual, organizational, and contextual factors, especially for young people whose social roles and institutional ties remain in flux. METHODS: We introduce a retrospective, longitudinal cohort design to study treatment quality practices and outcomes among approximately 65,000 TA adults entering treatment for OUD between 2012 and 2025 in New York. We propose to combine data from multiple sources, including Medicaid claims and encounter data and a state registry of substance use disorder (SUD) treatment episodes, to examine three aspects of OUD treatment quality: 1) MOUD use, including MOUD option (e.g., buprenorphine, methadone, or extended-release [XR] naltrexone); 2) adherence to pharmacotherapy and retention in treatment; and 3) adverse events (e.g., overdoses). Using rigorous analytical methods, we will provide insights into how variation in treatment practices and outcomes are structured more broadly by multilevel processes related to communities, treatment programs, and characteristics of the patient, as well as their complex interplay. DISCUSSION: Our findings will inform clinical decision making by patients and providers as well as public health responses to the rising number of young adults seeking treatment for OUD amidst the opioid and polysubstance overdose crisis in the U.S.

Medicare Advantage Plan Star Ratings and County Social Vulnerability.

Importance: The star rating of a Medicare Advantage (MA) plan is meant to represent plan performance, and it determines the size of quality bonuses. Consumer access to MA plans with a high star rating may vary by the extent of social vulnerability in geographic regions. Objective: To examine the association between a county's Social Vulnerability Index (SVI) and the star rating of a county's MA plans. Design, Setting, and Participants: This cross-sectional study used 2023 Centers for Medicare & Medicaid Services data for all MA plans linked to 2020 county-level SVI data from the Centers for Disease Control and Prevention. Data were analyzed from March to October 2023. Exposure: Quintile rank of county based on composite and theme-specific SVI scores, with quartile 1 (Q1) representing the least vulnerable counties and Q5, the most vulnerable counties. The SVI is a multidimensional measure of a county's social vulnerability across 4 themes: socioeconomic status, household characteristics (such as disability, age, and language), racial and ethnic minority status, and housing type and transportation. Main Outcomes and Measures: County-level mean star rating and the number of MA plans with low-rated (<3.5 stars), high-rated (3.5 or 4.0 stars), and highest-rated (≥4.5 stars) plans. Results: Across 3075 counties, the median county-level star rating was 4.1 (IQR, 3.9-4.3) in Q1 counties and 3.8 (IQR, 3.6-4.0) in Q5 counties (P < .001). The mean star rating of MA plans was lower (difference, -0.24 points; 95% CI, -0.28 to -0.21 points; P < .001), the number of low-rated plans was higher (incidence rate ratio, 1.81; 95% CI, 1.61-2.06; P < .001), and the number of highest-rated plans was lower (incidence rate ratio, 0.75; 95% CI, 0.70-0.81; P < .001) in Q5 counties compared with Q1 counties. Similar patterns were found across theme-specific SVI score quintiles and for 2022 star ratings. Conclusions and Relevance: In this cross-sectional study, the most socially vulnerable counties were found to have the fewest highest-rated plans for MA beneficiaries. As MA enrollment grows in socially vulnerable regions, this may exacerbate regional differences in health outcomes for Medicare beneficiaries.

It Is Time to Consider More Price Regulation in Health Care.

This JAMA Forum discusses the promise and pitfalls of regulating prices in the US health care system.

Unwinding And The Medicaid Undercount: Millions Enrolled In Medicaid During The Pandemic Thought They Were Uninsured.

Policy responses to the March 31, 2023, expiration of the Medicaid continuous coverage provision need to consider the difference between self-reported Medicaid participation on government surveys and administrative records of Medicaid enrollment. The difference between the two is known as the "Medicaid undercount." The size of the undercount increased substantially after the continuous coverage provision took effect in March 2020. Using longitudinal data from the Current Population Survey, we examined this change. We found that assuming that all beneficiaries who ever reported enrolling in Medicaid during the COVID-19 pandemic public health emergency remained enrolled through 2022 (as required by the continuous coverage provision) eliminated the worsening of the undercount. We estimated that nearly half of the 5.9 million people who we projected were likely to become uninsured after the provision expired, or "unwound," already reported that they were uninsured in the 2022 Current Population Survey. This finding suggests that the impact of ending the continuous coverage provision on the estimated uninsurance rate, based on self-reported survey data, may have been smaller than anticipated. It also means that efforts to address Medicaid unwinding should include people who likely remain eligible for Medicaid but believe that they are already uninsured.

Physician-Based Approaches to Price Transparency: A Solution in Search of a Problem?

Physician-based transparency approaches have been advanced as a strategy for informing patients of the likely financial consequences of using services. The structure of health care pricing and insurance coverage, and the low uptake of existing tools, suggest these approaches are likely to be unwieldy and unsuccessful. They may also generate new ethical challenges.

Major Traffic Safety Reform and Road Traffic Injuries Among Low-Income New York Residents, 2009-2021.

Objectives. To evaluate the effects of a comprehensive traffic safety policy-New York City's (NYC's) 2014 Vision Zero-on the health of Medicaid enrollees. Methods. We conducted difference-in-differences analyses using individual-level New York Medicaid data to measure traffic injuries and expenditures from 2009 to 2021, comparing NYC to surrounding counties without traffic reforms (n = 65 585 568 person-years). Results. After Vision Zero, injury rates among NYC Medicaid enrollees diverged from those of surrounding counties, with a net impact of 77.5 fewer injuries per 100 000 person-years annually (95% confidence interval = -97.4, -57.6). We observed marked reductions in severe injuries (brain injury, hospitalizations) and savings of $90.8 million in Medicaid expenditures over the first 5 years. Effects were largest among Black residents. Impacts were reversed during the COVID-19 period. Conclusions. Vision Zero resulted in substantial protection for socioeconomically disadvantaged populations known to face heightened risk of injury, but the policy's effectiveness decreased during the pandemic period. Public Health Implications. Many cities have recently launched Vision Zero policies and others plan to do so. This research adds to the evidence on how and in what circumstances comprehensive traffic policies protect public health. (Am J Public Health. 2024;114(6):633-641. https://doi.org/10.2105/AJPH.2024.307617).

The State of Health Insurance Coverage and the 2024 Election.

This JAMA Forum discusses record health insurance enrollments and the risks to continuing gains in coverage.

Housing-Sensitive Health Conditions Can Predict Poor-Quality Housing.

Improving housing quality may improve residents' health, but identifying buildings in poor repair is challenging. We developed a method to improve health-related building inspection targeting. Linking New York City Medicaid claims data to Landlord Watchlist data, we used machine learning to identify housing-sensitive health conditions correlated with a building's presence on the Watchlist. We identified twenty-three specific housing-sensitive health conditions in five broad categories consistent with the existing literature on housing and health. We used these results to generate a housing health index from building-level claims data that can be used to rank buildings by the likelihood that their poor quality is affecting residents' health. We found that buildings in the highest decile of the housing health index (controlling for building size, community district, and subsidization status) scored worse across a variety of housing quality indicators, validating our approach. We discuss how the housing health index could be used by local governments to target building inspections with a focus on improving health.

Enrollment Patterns of Medicare Advantage Beneficiaries by Dental, Vision, and Hearing Benefits.

Importance: Most Medicare beneficiaries now choose to enroll in Medicare Advantage (MA) plans. Racial and ethnic minority group and low-income beneficiaries are increasingly enrolling in MA plans. Objective: To examine whether dental, vision, and hearing supplemental benefits offered in MA plans are associated with the plan choices of traditionally underserved Medicare beneficiaries. Design, Setting, and Participants: This exploratory observational cross-sectional study used data from the 2018 to 2020 Medicare Current Beneficiary Survey linked to MA plan benefits. The nationally representative sample comprised primarily community-dwelling MA beneficiaries enrolled in general enrollment MA plans. Data analysis was performed between April and October 2023. Exposures: Beneficiary self-identified race and ethnicity and combined individual and spouse income and educational attainment. Main Outcomes and Measures: Binary indicators were developed to determine whether beneficiaries were enrolled in a plan offering any dental, comprehensive dental, any vision, eyewear, any hearing, or hearing aid benefit. Mixed-effects logistic regression models were estimated to report average marginal effects adjusted for beneficiary-level demographic and health characteristics, plan attributes, and plan availability. Results: This study included 8139 (weighted N = 31 million) eligible MA beneficiaries, with a mean (SD) age of 77.7 (7.5) years. More than half of beneficiaries (54.9%) were women; 9.8% self-identified as Black, 2.0% as Hispanic, 83.9% as White, and 4.2% as other or multiple races or ethnicities. Plan choices by dental benefits were examined among 7516 beneficiaries who were not enrolled in any dental standalone plan, by vision benefits for 8026 beneficiaries not enrolled in any vision standalone plan, and by hearing benefits for 8131 beneficiaries not enrolled in any hearing standalone plan. Black beneficiaries were more likely to enroll in plans with any dental benefit (9.0 percentage points [95% CI, 3.4-14.4]; P < .001), any comprehensive dental benefit (11.2 percentage points [95% CI, 5.7-16.7]; P < .001), any eye benefit (3.0 percentage points [95% CI, 1.0 to 5.0]; P = .004), or any eyewear benefit (6.0 percentage points [95% CI, 0.6-11.5]; P = .03) compared with White beneficiaries. Lower-income individuals (earning ≤200% of the federal poverty level) were more likely to enroll in a plan with a comprehensive dental benefit (4.4 percentage-point difference [95% CI, 0.1-7.9]; P = .01) compared with higher-income beneficiaries. Beneficiaries without a college degree were more likely to enroll in a plan with a comprehensive dental benefit (4.7 percentage-point difference [95% CI, 1.4-8.0]; P = .005) compared with those with higher educational attainment. Conclusions and Relevance: The results of this study suggest that racial and ethnic minority individuals and those with lower income or educational attainment are more likely to choose MA plans with dental or vision benefits. As the federal government prepares to adjust MA plan star ratings for health equity, implements MA payment cuts, and allows increasing flexibility in supplemental benefit offerings, these findings may inform benefit monitoring for MA.

Balancing Investments in Health Care and Social Determinants-The Need for Benefit-Cost Analysis.

This JAMA Forum discusses how to balance investments in health care and social determinants of health, using benefit-cost analysis and other methods to rationally balance investments across sectors.

Improving Labor Outcomes among People with Mild or Moderate Mental Illness through Law and Policy Reform.

Mild and moderate mental illnesses can hinder labor force participation, lead to work interruptions, and hamper earning potential. Targeted interventions have proven effective at addressing these problems. But their potential depends on labor protections that enable people to take advantage of these interventions while keeping jobs and income.

Health Systems and Social Services-A Bridge Too Far?

This JAMA Forum argues that hospitals and health systems should not take the lead in programs to address social determinants of health and provides examples and reasons why.

Lasting scars: The impact of depression in early adulthood on subsequent labor market outcomes.

A growing body of evidence indicates that poor health early in life can leave lasting scars on adult health and economic outcomes. While much of this literature focuses on childhood experiences, mechanisms generating these lasting effects-recurrence of illness and interruption of human capital accumulation-are not limited to childhood. In this study, we examine how an episode of depression experienced in early adulthood affects subsequent labor market outcomes. We find that, at age 50, people who had met diagnostic criteria for depression when surveyed at ages 27-35 earn 10% lower hourly wages (conditional on occupation), work 120-180 fewer hours annually, and earn 24% lower annual wage incomes. A portion of this income penalty (21%-39%) occurs because depression is often a chronic condition, recurring later in life. But a substantial share (25%-55%) occurs because depression in early adulthood disrupts human capital accumulation, by reducing work experience and by influencing selection into occupations with skill distributions that offer lower potential for wage growth. These lingering effects of early depression reinforce the importance of early and multifaceted intervention to address depression and its follow-on effects in the workplace.

The impacts of the 340B Program on health care quality for low-income patients.

OBJECTIVE: To assess the effects of hospital 340B eligibility on quality of inpatient care provided to Medicaid and uninsured patients and for all patients. DATA: Agency for Health Care Research and Quality's Healthcare Cost and Utilization Project State Inpatient Data, Hospital Cost Reporting Information System Data, Office of Pharmacy Affairs Information System Data, and American Hospital Association Annual Survey. DESIGN: Regression discontinuity design comparing hospitals just above the DSH percentage program eligibility threshold to those just below. Quality measures include all-cause mortality and 30-day readmission rates as well as condition-specific measures. DATA EXTRACTION: Inpatient data from general acute care hospitals from 2008 to 2014 in 15 states. Data linked on hospital 340B eligibility and participation. PRINCIPAL FINDINGS: We did not find discontinuities in inpatient care quality across the Program eligibility threshold for Medicaid and uninsured patients; specifically, on all-cause mortality (beta = -0.04 percentage points, 95% CI: -0.16, 0.08), 30-day readmission rates (beta = -0.16 percentage points, 95% CI: -0.81, 0.5), or other measures. Among insured and non-Medicaid patients, we found discontinuities for acute myocardial infarction (beta = -0.87 percentage points, 95% CI: -1.55, -0.2) and postoperative sepsis (beta = -0.15 percentage points, 95% CI: -0.23, -0.07) mortality. CONCLUSIONS: 340B Program participation has not demonstrated improved quality of inpatient care among Medicaid or uninsured patients.

Hospital concentration and low-income populations: Evidence from New York State Medicaid.

While a large body of evidence has examined hospital concentration, its effects on health care for low-income populations are less explored. We use comprehensive discharge data from New York State to measure the effects of changes in market concentration on hospital-level inpatient Medicaid volumes. Holding fixed hospital factors constant, a one percent increase in HHI leads to a 0.6% (s.e. = 0.28%) decrease in the number of Medicaid admissions for the average hospital. The strongest effects are on admissions for birth (-1.3%, s.e. = 0.58%). These average hospital-level decreases largely reflect redistribution of Medicaid patients across hospitals, rather than overall reductions in hospitalizations for Medicaid patients. In particular, hospital concentration leads to a redistribution of admissions from non-profit hospitals to public hospitals. We find evidence that for births, physicians serving high shares of Medicaid beneficiaries in particular experience reduced admissions as concentration increased. These reductions may reflect preferences among these physicians or reduced admitting privileges by hospitals as a means to screen out Medicaid patients.

Using machine-learning methods to predict in-hospital mortality through the Elixhauser index: A Medicare data analysis.

Accurate in-hospital mortality prediction can reflect the prognosis of patients, help guide allocation of clinical resources, and help clinicians make the right care decisions. There are limitations to using traditional logistic regression models when assessing the model performance of comorbidity measures to predict in-hospital mortality. Meanwhile, the use of novel machine-learning methods is growing rapidly. In 2021, the Agency for Healthcare Research and Quality published new guidelines for using the Present-on-Admission (POA) indicator from the International Classification of Diseases, Tenth Revision, for coding comorbidities to predict in-hospital mortality from the Elixhauser's comorbidity measurement method. We compared the model performance of logistic regression, elastic net model, and artificial neural network (ANN) to predict in-hospital mortality from Elixhauser's measures under the updated POA guidelines. In this retrospective analysis, 1,810,106 adult Medicare inpatient admissions from six US states admitted after September 23, 2017, and discharged before April 11, 2019 were extracted from the Centers for Medicare and Medicaid Services data warehouse. The POA indicator was used to distinguish pre-existing comorbidities from complications that occurred during hospitalization. All models performed well (C-statistics >0.77). Elastic net method generated a parsimonious model, in which there were five fewer comorbidities selected to predict in-hospital mortality with similar predictive power compared to the logistic regression model. ANN had the highest C-statistics compared to the other two models (0.800 vs. 0.791 and 0.791). Elastic net model and AAN can be applied successfully to predict in-hospital mortality.

Human Reactions to Public Health Interventions-Implications for Evaluation and Well-being.

This JAMA Forum discusses the public health community's reaction to a recent Cochrane Collaboration review on whether face masks and other physical public health interventions reduced the spread of the COVID-19 and provides counterarguments to the review's findings that these interventions did not help.

The Debt Ceiling and Health Care Entitlements.

This JAMA Forum discusses the US budget and debt ceiling, proposals that have been made to reduce health entitlement spending, and alternative ways to control health care spending.

Racial and Ethnic Segregation in Primary Care and Association of Practice Composition With Quality of Care.

OBJECTIVE: To assess the extent of segregation between racial and ethnic minority and White patients across primary care physicians and the association of practice panel racial/ethnic composition with the quality of care delivered. RESEARCH DESIGN: We examined the degree of racial/ethnic dissimilarity (a measure of segregation) in visits and the allocation of patient visits by different groups across primary care physicians (PCPs). We assessed the regression-adjusted relationship between the racial/ethnic composition of PCP practices and measures of the quality of care delivered. We compared outcomes in the pre-Affordable Care Act (ACA) and post-ACA (2006-2010/2011-2016) periods. SUBJECTS: We analyzed data on all primary care visits to office-based practitioners in the 2006-2016 National Ambulatory Medical Care Survey. PCPs were defined as general/family practice or internal medicine physicians. We excluded cases with imputed race or ethnicity information. For the quality of care analyses, we limited the sample to adults. RESULTS: Racial and ethnic minority patients remain concentrated within a small group of PCPs: 35% of PCPs accounted for 80% of non-White patients' visits; 63% of non-White (or White) patients would need to switch physicians to make the distribution of visits across PCPs proportional between the groups. We observed little correlation between the PCPs panel's racial/ethnic composition and quality of care. These patterns did not change substantially over time. CONCLUSIONS: PCPs remain segregated, but the racial/ethnic composition of a practice panel is not associated with the quality of health care that individual patients receive in either the pre or post-ACA passage periods.

Stopping the "Medicaid Churn"-Addressing Medicaid Coverage After the COVID-19 Public Health Emergency Ends.

This JAMA Forum discusses Medicaid continuous enrollment and coverage under the American Rescue Plan Act and the Inflation Reduction Act and ways that the government can continue to decrease Medicaid churn (individuals cycling in and out of the program) after the COVID-19 Public Health Emergency Ends.