Past Disruptions in Health Insurance Coverage and Access to Care Among Insured Adults.

INTRODUCTION: Although the association between health insurance coverage and access to care is well documented, it is unclear whether the deleterious effects of being uninsured are strictly contemporaneous or whether previous disruptions in coverage have persistent effects. This study addresses this issue using nationally representative data covering 2011-2019 to estimate the extent to which disruptions in health insurance coverage continued to be associated with poor access even after coverage was regained. METHODS: Analysis was conducted in 2022. Using a nationally representative cohort of insured adults aged 18-64 years (N=39,904) and multivariable logistic regression models, the authors estimated the association between past disruptions in coverage (occurring at least 1 year before) and the risks of lacking a usual source of care provider and having unmet medical need. RESULTS: Among insured nonelderly adults, the risk of being without a usual source of care provider was between 18% (risk ratio=1.18; 95% CI=1.00, 1.38) and 75% higher (risk ratio=1.75; 95% CI=1.56, 1.93) than for those with continuous coverage; the risk of having unmet medical needs was between 41% (risk ratio=1.41; 95% CI=1.00, 1.83) and 66% (risk ratio=1.66; 95% CI=1.26, 2.06) higher. Longer insurance disruptions were associated with a higher risk of lacking a usual source of care provider. CONCLUSIONS: Previous disruptions in health insurance coverage continued to be negatively associated with access to care for more than a year after coverage was regained. Improving access to care in the U.S. may require investing in policies and programs that help to strengthen coverage continuity among individuals with insurance coverage rather than focusing exclusively on helping uninsured individuals to gain coverage.

Perceptions of Patient-Provider Communication Across the Six Largest Asian Subgroups in the USA.

BACKGROUND: Asians are the fastest-growing racial/ethnic minority group in the USA and many face communication barriers when seeking health care. Given that a high proportion of Asians are immigrants and have limited English proficiency, poor patient-provider communication may explain Asians' relatively low ratings of care. Though Asians are linguistically, economically, and culturally heterogeneous, research on health care disparities typically combines Asians into a single racial/ethnic category. OBJECTIVES: To estimate racial/ethnic differences in perceptions of provider communication among the six largest Asian subgroups. DESIGN AND PARTICIPANTS: Using a nationally representative sample of adults from the 2014-2017 Medical Expenditure Panel Survey (N = 136,836, round-specific response rates range from 72% to 98%), we estimate racial/ethnic differences in perceptions of provider communication, adjusted for English proficiency, immigration status, and sociodemographic characteristics. MAIN MEASURES: The main dependent variable is a 4-item scale ranging from 0 to 100 measuring how positively patients view their health care providers' communication, adapted from the Consumer Assessment of Healthcare Providers and Systems (CAHPS©) program. Respondents report how often their providers explain things clearly, show respect, listen carefully, and spend enough time with them. KEY RESULTS: Asians, overall, had less positive perceptions of their providers' communication than either Whites or Latinxs. However, only Chinese-White differences remained after differences in English proficiency and immigration status were controlled (difference = - 2.67, 95% CI - 4.83, - 0.51). No other Asian subgroup differed significantly from Whites. CONCLUSIONS: Negative views of provider communication are not pervasive among all Asians but, rather, primarily reflect the perceptions of Chinese and, possibly, Vietnamese patients. Researchers, policymakers, health plan executives, and others who produce or use data on patients' experiences with health care should, if possible, avoid categorizing all Asians into a single group.

Rural-Urban Differences in Access to Primary Care: Beyond the Usual Source of Care Provider.

INTRODUCTION: In the U.S., rural residents have poorer health than urban residents and this disadvantage is growing. Therefore, it is important to understand rural-urban differences in access to medical care. This study compared the percentage of individuals with a usual source of care and characteristics of usual source of care providers across 3 urban-rural categories. METHODS: This study identified 51,920 adults from the 2014-2016 Medical Expenditure Panel Survey and estimated the percentage with a usual source of care across the rural-urban categories. Then, differences in a variety of provider characteristics were examined. Estimates were weighted to be representative of the U.S. non-institutionalized population and adjusted for age, race/ethnicity, self-rated health, and presence of chronic conditions. Analysis was conducted in 2018 and 2019. RESULTS: Compared with metropolitan county residents, residents of the most rural counties were 7 percentage points more likely to have a usual source of care (81% vs 74%), but their providers were 13 percentage points less likely to be physicians (22% vs 35%). Despite having to travel longer to reach their usual source of care providers, residents of the most rural counties were 18 percentage points less likely than metropolitan residents to have usual source of care providers with office hours on nights and weekends (27% vs 39%). CONCLUSIONS: Rural-urban differences in access to care are complex; there is a rural disadvantage on some dimensions of access but not others. To understand rural-urban disparities in healthcare access, research should move beyond the usual source of care provider as an overall indicator and instead investigate disparities using multiple indicators of access based on theoretically distinct domains.

Rural Residents With Mental Health Needs Have Fewer Care Visits Than Urban Counterparts.

Analysis of a nationally representative sample of adults with mental health needs shows that rural residents have fewer ambulatory mental health visits than their urban counterparts do. Even among people already on prescription medications for mental health conditions, rural-urban differences are large.

Patient-Provider Communication Disparities by Limited English Proficiency (LEP): Trends from the US Medical Expenditure Panel Survey, 2006-2015.

BACKGROUND: Individuals with limited English proficiency (LEP) have worse healthcare access and report lower quality of care compared to individuals who are proficient in English. Policy efforts to improve patient-provider communication for LEP individuals have been going on for decades but linguistic disparities persist. OBJECTIVE: To describe trends in patient-provider communication by limited English proficiency (LEP) from 2006 to 2015. DESIGN: We estimated interrupted time series models for three measures of patient-provider communication, testing for differences in both means (intercepts) and trends (slopes) before and after 2010 and differences in differences by English proficiency. PARTICIPANTS: A nationally representative sample of the US non-institutionalized population with at least one office-based medical visit from the 2006-2015 Medical Expenditure Panel Survey (N = 27,001). MAIN MEASURES: Patient-provider communication is measured with three variables indicating whether individuals reported that their providers always explained things in a way that was easy to understand, showed respect for what they had to say, and listened carefully. KEY RESULTS: Although patient-provider communication improved for all groups over the study period, before 2010, it was getting worse among LEP individuals and disparities in patient-provider communication were widening. After 2010, patient-provider communication improved for LEP individuals and language disparities by English proficiency either narrowed or remained the same. For example, between 2006 and 2010, the percent of LEP individuals reporting that their provider explained things clearly declined by, on average, 1.4 percentage points per year (p value = 0.102); after 2010, it increased by 3.0 percentage points per year (p value = 0.003). CONCLUSIONS: Our study sheds light on trends in patient-provider communication before and after 2010, a year that marked substantial efforts to reform the US healthcare system. Though patient-provider communication among LEP individuals has improved since 2010, linguistic disparities persist and constitute a formidable challenge to achieving healthcare equity, a long-standing US policy goal.

Do People with Health Insurance Coverage Who Live in Areas with High Uninsurance Rates Pay More for Emergency Department Visits?

OBJECTIVE: To investigate the relationship between the percent uninsured in a county and expenditures associated with the typical emergency department visit. DATA SOURCES: The Medical Expenditure Panel Survey linked to county-level data from the American Community Survey, the Healthcare Cost and Utilization Project, and the Area Health Resources Files. STUDY DESIGN: We use a nationally representative sample of emergency department visits that took place between 2009 and 2013 to estimate the association between the percent uninsured in counties and the amount paid for a typical visit. Final estimates come from a diagnosis-level fixed-effects model, with additional controls for a wide variety of visit, individual, and county characteristics. PRINCIPAL FINDINGS: Among those with private insurance, we find that an increase of 1 percentage point in the county uninsurance rate is associated with a $20 increase in the mean emergency department payment. No such association is observed among visits covered by other insurance types. CONCLUSIONS: Results provide tentative evidence that the costs associated with high uninsurance rates spill over to those with insurance, but future research needs to replicate these findings with longitudinal data and methods before drawing causal conclusions. Recent data on changes in area uninsurance rates following the ACA's insurance expansions and subsequent changes in emergency department expenditures afford a valuable opportunity to do this.

The availability of community health center services and access to medical care.

BACKGROUND: Community Health Centers (CHCs) funded by Section 330 of the Public Health Service Act are an essential part of the health care safety net in the US. The Patient Protection and Affordable Care Act expanded the program significantly, but the extent to which the availability of CHCs improve access to care in general is not clear. In this paper, we examine the associations between the availability of CHC services in communities and two key measures of ambulatory care access - having a usual source of care and having any office-based medical visits over a one year period. METHODS: We pooled six years of data from the Medical Expenditure Panel Survey (2008-2013) and linked it to geographic data on CHCs from Health Resources and Services Administration's Health Center Program Uniform Data System. We also link other community characteristics from the Area Health Resource File and the Dartmouth Institute's data files. The associations between CHC availability and our access measures are estimated with logistic regression models stratified by insurance status. RESULTS: The availability of CHC services was positively associated with both measures of access among those with no insurance coverage. Additionally, it was positively associated with having a usual source of care among those with Medicaid and private insurance. These findings persist after controlling for key individual- and community-level characteristics. CONCLUSIONS: Our findings suggest that an enhanced CHC program could be an important resource for supporting the efficacy of expanded Medicaid coverage under the Affordable Care Act and, ultimately, improving access to quality primary care for underserved Americans.

Access To Care Improved For People Who Gained Medicaid Or Marketplace Coverage In 2014.

Newly available longitudinal survey data show that people who lacked health insurance in 2013 and gained coverage through Medicaid or the Marketplaces in 2014 were far more likely to obtain a usual source of care and receive preventive care services than their counterparts who remained uninsured in 2014.

The ACA's Zero Cost-Sharing Mandate and Trends in Out-of-Pocket Expenditures on Well-Child and Screening Mammography Visits.

BACKGROUND: Starting in September of 2010, the Patient Protection and Affordable Care Act required most health insurance policies to cover evidence-based preventive care with no cost-sharing (no copays, coinsurance, or deductibles). It is unknown, however, whether declines in out-of-pocket costs for preventive services are large enough to prompt increases in utilization, the ultimate goal of the policy. METHODS: In this study, we use a nationally representative sample of ambulatory care visits to estimate the impact of the zero cost-sharing mandate on out-of-pocket expenditures on well-child and screening mammography visits. Estimates are made using 2-part interrupted time-series models, with well-woman visits serving as the control group because they were not covered under the zero cost-sharing mandate until after our study period. RESULTS: Results indicate a substantial reduction in out-of-pocket costs attributable to the Affordable Care Act. Between January 2011 and September 2012, the zero cost-sharing mandate reduced per-visit out-of-pocket costs for well-child visits from $18.46 to $8.08 (56%) and out-of-pocket costs for screening mammography visits from $25.43 to $6.50 (74%). No reduction was apparent for well-woman visits. CONCLUSIONS: The Affordable Care Act's zero cost-sharing mandate for preventive care has had a large impact on out-of-pocket expenditures for well-child and mammography visits. To increase preventive service use, research is needed to better understand barriers to obtaining preventive care that are not directly related to cost.

'Double jeopardy' measure suggests blacks and hispanics face more severe disparities than previously indicated.

Eliminating disparities in health and health care is a long-standing objective of the US government. Racial and ethnic differences in insurance coverage pose a major obstacle to achieving this objective. With important coverage provisions of the Affordable Care Act beginning to take effect, we propose a new way of conceptualizing and quantifying the racial and ethnic disadvantages of uninsurance over the course of a lifetime. Using a life expectancy approach, we estimate the number of years whites, blacks, and Hispanics can expect to live in insurance "double jeopardy": being uninsured while also in lesser health and, therefore, at higher risk of needing medical care. Our measures indicate that compared to whites, Hispanics and blacks are more likely not only to be uninsured at any point throughout most of their lives, but also to spend more years uninsured and spend more of these uninsured years at high risk of needing medical care. These life expectancy measures--designed for ease of use by policy makers, researchers, and the general public--have the potential to reframe the discussion of disparities and monitor progress toward their elimination.

Race, place, and obesity: the complex relationships among community racial/ethnic composition, individual race/ethnicity, and obesity in the United States.

OBJECTIVES: We explored the association between community racial/ethnic composition and obesity risk. METHODS: In this cross-sectional study, we used nationally representative data from the Medical Expenditure Panel Survey linked to geographic data from the US Decennial Census and Census Business Pattern data. RESULTS: Living in communities with a high Hispanic concentration (≥ 25%) was associated with a 0.55 and 0.42 increase in body mass index (BMI; defined as weight in kilograms divided by the square of height in meters) and 21% and 23% higher odds for obesity for Hispanics and non-Hispanic Whites, respectively. Living in a community with a high non-Hispanic Asian concentration (≥ 25%) was associated with a 0.68 decrease in BMI and 28% lower odds for obesity for non-Hispanic Whites. We controlled for individual- and community-level social, economic, and demographic variables. CONCLUSIONS: Community racial/ethnic composition is an important correlate of obesity risk, but the relationship differs greatly by individual race/ethnicity. To better understand the obesity epidemic and related racial/ethnic disparities, more must be learned about community-level risk factors, especially how built environment and social norms operate within communities and across racial/ethnic groups.

Community and individual race/ethnicity and home health care use among elderly persons in the United States.

OBJECTIVE: To investigate whether the interaction between individual race/ethnicity and community racial/ethnic composition is associated with health-related home care use among elderly persons in the United States. DATA SOURCES: A nationally representative sample of community-dwelling elders aged 65+ from the 2000 to 2006 Medical Expenditure Panel Survey (N=23,792) linked to block group-level racial/ethnic information from the 2000 Decennial Census. DESIGN: We estimated the likelihood of informal and formal home health care use for four racial/ethnic elderly groups (non-Hispanic [NH] whites, NH-blacks, NH-Asians, and Hispanics) living in communities with different racial/ethnic compositions. PRINCIPAL FINDINGS: NH-Asian and Hispanic elders living in block groups with ≥25 percent of residents being NH-Asian or Hispanic, respectively, were more likely to use informal home health care than their counterparts in other block groups. No such effect was apparent for formal home health care. CONCLUSIONS: NH-Asian and Hispanic elders are more likely to use informal home care if they live in communities with a higher proportion of residents who share their race/ethnicity. A better understanding of how informal care is provided in different communities may inform policy makers concerned with promoting informal home care, supporting informal caregivers, or providing formal home care as a substitute or supplement to informal care.

Unhealthy and uninsured: exploring racial differences in health and health insurance coverage using a life table approach.

Millions of people in the United States do not have health insurance, and wide racial and ethnic disparities exist in coverage. Current research provides a limited description of this problem, focusing on the number or proportion of individuals without insurance at a single time point or for a short period. Moreover, the literature provides no sense of the joint risk of being uninsured and in need of medical care. In this article, we use a life table approach to calculate health- and insurance-specific life expectancies for whites and blacks, thereby providing estimates of the duration of exposure to different insurance and health states over a typical lifetime. We find that, on average, Americans can expect to spend well over a decade without health insurance during a typical lifetime and that 40% of these years are spent in less-healthy categories. Findings also reveal a significant racial gap: despite their shorter overall life expectancy, blacks have a longer uninsured life expectancy than whites, and this racial gap consists entirely of less-healthy years. Racial disparities in insurance coverage are thus likely more severe than indicated by previous research.

Explaining racial and ethnic differences in antidepressant use among adolescents.

We investigate the extent to which antidepressant use among adolescents varies across racial and ethnic subgroups. Using a representative sample of U.S. adolescents, we find that non-Hispanic White adolescents are over twice as likely as Hispanic adolescents, and over five times as likely as non-Hispanic Black adolescents to use antidepressants. Results from a decomposition analysis indicate that racial/ethnic differences in characteristics, including household income, parental education, health insurance, and having a usual source of care explain between one half and two thirds of the gap in antidepressant use between Hispanics and non-Hispanic Whites. In contrast, none of the gap between Whites and Blacks in antidepressant use is explained by differences in observed characteristics. Further analysis suggests that there are large racial/ethnic differences in the extent to which behavioral and mental health problems prompt antidepressant use and that this may, in part, account for the large differences across race/ethnicity observed in our study.

The relationship between living arrangement and preventive care use among community-dwelling elderly persons.

OBJECTIVES: We sought to examine the relationship between living arrangements and obtaining preventive care among the elderly population. METHODS: We obtained data on 13,038 community-dwelling elderly persons from the 2002 to 2005 Medical Expenditure Panel Survey and used multivariate logistic regression models to estimate the likelihood of preventive care use among elderly persons in 4 living arrangements: living alone (38%), living with one's spouse only (52%), living with one's spouse and with one's adult offspring (5%), and living with one's adult offspring only (5%). Preventive care services included influenza vaccination, physical and dental checkup, and screenings for hypertension, cholesterol, and colorectal cancer. RESULTS: After we controlled for age, gender, race, education, income, health insurance, comorbidities, self-reported health, physical function status, and residence location, we found that elderly persons living with a spouse only were more likely than were those living alone to obtain all preventive care services, except for hypertension screening. However, those living with their adult offspring were not more likely to obtain recommended preventive care compared with those living alone. These results did not change when the employment status and functional status of adult offspring were considered. CONCLUSIONS: Interventions to improve preventive care use should target not only those elderly persons who live alone but also those living with adult offspring.

Using Instrumental Variable (IV) Tests to Evaluate Model Specification in Latent Variable Structural Equation Models.

Structural Equation Modeling with latent variables (SEM) is a powerful tool for social and behavioral scientists, combining many of the strengths of psychometrics and econometrics into a single framework. The most common estimator for SEM is the full-information maximum likelihood estimator (ML), but there is continuing interest in limited information estimators because of their distributional robustness and their greater resistance to structural specification errors. However, the literature discussing model fit for limited information estimators for latent variable models is sparse compared to that for full information estimators. We address this shortcoming by providing several specification tests based on the 2SLS estimator for latent variable structural equation models developed by Bollen (1996). We explain how these tests can be used to not only identify a misspecified model, but to help diagnose the source of misspecification within a model. We present and discuss results from a Monte Carlo experiment designed to evaluate the finite sample properties of these tests. Our findings suggest that the 2SLS tests successfully identify most misspecified models, even those with modest misspecification, and that they provide researchers with information that can help diagnose the source of misspecification.

Explaining racial and ethnic differences in children's use of stimulant medications.

OBJECTIVES: To document and explain racial/ethnic differences in the use of stimulant drugs among US children. DATA AND METHODS: We use a nationally representative sample of children ages 5-17 years old from the Medical Expenditure Panel Survey (MEPS) for the years 2000-2002. We estimate race-specific means and regressions to highlight differences across groups in individual/family characteristics that may affect stimulant use and differences in responses to these characteristics. Then, we use Oaxaca-Blinder decomposition methods to quantify the portion of differential use explained by differences in individual/family characteristics. Finally, we use pooled regressions with race/ethnicity interactions to formally test the hypothesis that responses to perceived mental health and behavioral problems vary across groups. RESULTS: White children are about twice as likely to use stimulants as either Hispanic or Black children. Differences in individual/family characteristics account for about 25% of the difference between whites and Hispanics, but for none of the difference between whites and blacks. Pooled regressions show that racial/ethnic gaps in stimulant use persist among children with otherwise similar reported mental health conditions. CONCLUSIONS: Our finding that the majority of racial/ethnic differences in children's stimulant use is explained by differences in responses to individual/family characteristics highlights the importance of further research to examine the reasons for these differences. It is striking that children with otherwise similar reports of mental health problems have such different outcomes in terms of stimulant use. Potential explanations range from discrimination to cultural differences by race/ethnicity or community.