Publications by authors named "James B Kirby"

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.

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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.

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Introduction: In the U.S., rural residents have poorer health than urban residents and this disadvantage is growing.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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We investigate the extent to which antidepressant use among adolescents varies across racial and ethnic subgroups. Using a representative sample of U.S.

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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.

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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.

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Background: A growing number of Latinos are moving to nonmetro areas, but little research has examined how this trend might affect the Latino-disadvantage in access to healthcare.

Objective: We investigate health care access disparities between non-Latino whites and Latinos of Mexican origin, and whether the disparities differ between metro and nonmetro areas.

Methods: A series of logistic regression models provide insight on whether individuals have a usual source of care and whether they have had any physician visits in the past year.

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Many Americans do not have access to adequate medical care. Previous research on this problem focuses primarily on individual-level determinants of access such as income and insurance coverage. The role of community-level factors in helping or hindering individuals in obtaining needed medical care, however, has not received much attention.

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Objectives: The substantial racial and ethnic disparities in access to and use of health services are well documented. A number of studies highlight factors such as health insurance coverage and socioeconomic differences that explain some of the differences between groups, but much remains unexplained. We build on this previous research by incorporating additional factors such as attitudes about health care and neighborhood characteristics, as well as separately analyzing different Hispanic subgroups.

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