The impact of survey design modifications on health insurance coverage estimates in a National Longitudinal Health Care Survey

National health insurance coverage estimates for the overall population and specific population subgroups are critical to policymakers and others concerned with access to medical care and the cost and sources of payment for that care. The Medical Expenditure Panel Survey (MEPS) is one of the core health care surveys in the United States that serves as a primary source for these essential national health insurance coverage estimates. The survey is designed to provide annual national estimates of the health care use, medical expenditures, sources of payment and insurance coverage for the U.S. civilian non-institutionalized population. In 2007, the survey experienced two dominant survey design modifications: (1) a new sample design attributable to the sample redesign of the National Health Interview Survey, and (2) an upgrade to the CAPI platform for the survey instrument, moving from a DOS to a Windows based environment. This study examines the impact of these survey design modifications on the national estimates of insurance coverage. The overlapping panel design of the MEPS survey and its longitudinal features are particularly well suited to assess the impact of survey redesign modifications on estimates. Since two independent nationally representative samples are pooled to produce calendar year estimates, one has the capacity to compare estimates based on the “original survey design” in contrast to those derived from the “survey redesign.” This paper examines the correlates of nonresponse incorporated in the estimation techniques and adjustment methods employed in the survey, and the measures utilized for post-stratification overall and by panel. Particular attention is given to assessing the level of convergence in coverage estimates based on the alternative designs as well as the alignment of model based analyses that discern which factors are associated with health insurance classifications. The paper concludes with a discussion of strategies under consideration that may yield additional improvements in the accuracy for these critical policy relevant survey estimates.     

Patterns of Survey Attrition and Reluctant Response in the 1996 Medical Expenditure Panel Survey

In panel designs with multiple waves of data collection, the overall survey response rate is a multiplicative function of the wave specific response rates. The 1996 Medical Expenditure Panel Survey (MEPS) follows this model, requiring five rounds of data collection with the same panel of sampled households, to acquire data on health care use, expenditures, insurance coverage and sources of payment that cover two consecutive calendar years. Gaining an understanding of the factors that distinguish the cooperative respondents, the survey participants that require use of nonresponse conversion techniques to maintain their cooperation (reluctant respondents), and the initial participants that eventually drop out of the survey (part-year respondents) is essential from both an estimation and data collection perspective. To inform the specification of nonresponse adjustment strategies in MEPS to correct for survey attrition, this study attempts to identify the characteristics that distinguish survey participants across rounds from the part-year respondents. In addition, the study identifies factors that distinguish the cooperative respondents, the reluctant respondents and the part-year respondents, to better inform the MEPS data collection effort. The investigation also examines the implications of a data collection strategy that would not convert initial survey refusals by studying the effect, on survey estimates and their precision, of excluding reluctant survey respondents.Our findings revealed that reluctant respondents in the first round of the survey were significantly more likely to become non-respondents in the second round. In addition, the round two non-respondents were also more likely to be located in large metropolitan areas, to reside in the larger households with 5 or more members, to be elderly, and more likely to be either married or separated. Many of these characteristics were similar to those found to be at higher risk for nonresponse to the round one interview. Reluctant respondents as a whole appear to be a distinctly separate group, sharing one set of characteristics with the cooperative respondent group, another set with those who refused during the second round of the survey, and yet a third set of characteristics that are uniquely their own. If no effort had been made to convert reluctant participants, the precision of our survey estimates would have declined, but not substantially.     

Health insurance coverage during a 24-month period: a comparison of estimates from two national health surveys

National estimates of the uninsured are available from multiple surveys and differ across surveys. Previous efforts to better understand reasons for differences among these estimates have primarily focused on annual estimates. This study compares national estimates of health insurance coverage over generally comparable 24-month time periods using two integrated Federal health-related surveys, the Medical Expenditure Panel Survey (MEPS) and the National Health Interview Survey (NHIS) for the years 2002–2003 and replicated analyses for 2001–2002. We examine survey participants insurance status in year 1 and year 2 based on the NHIS linked with the MEPS and also for MEPS year 1 and year 2 participants. We also examine characteristics associated with 24-month coverage status. National estimates of the percents continuously insured did not differ significantly between the two data sources. In contrast, the MEPS longitudinal estimate of the percent continuously uninsured was higher than the NHIS-MEPS linked estimate whereas the MEPS longitudinal estimate of the discontinuously insured was lower than that derived from the NHIS-MEPS linked data. Factors that help explain these differences include the non-equivalence of the time periods covered by the data sources, modest differences in the length of time covered by the MEPS and NHIS survey instruments, and length of recall. Regression analyses yielded highly consistent correlates of being continuously uninsured versus continuously insured for both data sources. Regression results for discontinuous versus continuous coverage were also generally similar for both data sources. Gaining a better understanding of the alignment in findings based on alternative data sources that support comparable analyses of health insurance coverage helps policymakers to make the most appropriate use of resultant estimates. The views expressed in this paper are those of the authors and no official endorsement by the Department of Health and Human Services or the Agency for Healthcare Research and Quality or the Centers for Disease Control and Prevention is intended or should be inferred.     

Affordability of the Health Expenditures of Insured Americans Before the Affordable Care Act

Central to the Affordable Care Act is the notion of affordability and the role of health insurance in making otherwise unaffordable health care affordable. We used data from the 1996 to 2008 versions of the Medical Expenditure Panel Survey to estimate the portion of overall health care expenditures by insured respondents that would otherwise have been beyond their disposable incomes and assets. We found that about one third of insured expenditures would have been unaffordable, with a much higher percentage among publicly insured individuals. This result suggests that one of the main functions of insurance is to cover expenses that insured individuals would not otherwise be able to afford.Central to the Affordable Care Act (ACA; Pub L No. 111–148) is the notion of affordability and the role of health insurance in making otherwise unaffordable health care affordable. Yet, to our knowledge, no reports in the health policy literature have estimated the extent to which insurance accomplishes this function. We used data from the 1996 to 2008 versions of the Medical Expenditure Panel Survey (MEPS) to estimate the portion of total health care expenditures by insured respondents that would have been beyond their disposable income and assets if they had been uninsured. We focused on the pre-ACA period because that period represents the political context in which the act was passed.The MEPS data include information on demographic characteristics, medical care expenditures, health insurance coverage, incomes, and assets among a representative sample of US households. The information used in our analysis was derived from the household component of the MEPS, which is limited to members of the civilian, noninstitutionalized population who were present in the household during the entire survey period. We employed the restricted-use version of the MEPS to gain access to information on respondents’ assets.     

Health status and the cost of expanding insurance coverage

This paper uses data on health spending and health status from the Medical Expenditure Panel Survey (MEPS) to estimate the differences in health spending across different types of insurance and across incomes that are attributable solely to health status differences. The results show that the uninsured are less costly than those on Medicaid, based on health status alone, but are more costly than those with employer-sponsored insurance. Adults and children with private nongroup coverage are also less expensive than average, because of better-than-average health. Finally, the data show that expenditures fall (health status improves) with income, regardless of type of coverage.     

The cost effectiveness of health insurance

BACKGROUND: Although studies have examined both the adverse consequences of lacking health insurance and the costs of insuring the uninsured, there are no estimates of the value of providing health insurance to those currently uninsured. OBJECTIVE: To examine the value associated with providing insurance to those currently uninsured through an incremental cost-effectiveness analysis. METHODS: People aged 25 to 64 in both the National Health Interview Survey (with 2-year mortality follow-up) and the Medical Expenditure Panel Survey were examined to estimate the contribution of sociodemographic, health, and health behavior characteristics on insured persons' quality-adjusted life years (QALYs) and healthcare costs. Parameter estimates from these regression models were used to predict QALYs and costs associated with insuring the uninsured, given their characteristics for 1996. Markov decision-analysis modeling was then employed to calculate incremental cost-effectiveness ratios. RESULTS: The incremental cost-effectiveness of insurance for the average 25-year-old adult (through age 64) is approximately $35,000 per QALY gained (range $21,000 to $48,000). The incremental cost-effectiveness ratio becomes more favorable as people approach age 65. CONCLUSIONS: The additional health care purchased with health insurance provides gains in quality-adjusted life at costs that compare favorably to those of other programs and medical interventions society now chooses to fund.     

Uninsured rural families.

CONTEXT: Although research shows higher uninsured rates among rural versus urban individuals, prior studies are limited because they do not examine coverage across entire rural families. PURPOSE: This study uses the Medical Expenditure Panel Survey (MEPS) to compare rural and urban insurance coverage within families, to inform the design of coverage expansions that build on the current rural health insurance system. METHODS: We pooled the 2001 and 2002 MEPS Household Component survey, aggregated to the family level (excluding households with all members 65 and older). We examined (1) differences in urban, rural-adjacent, and rural nonadjacent family insurance coverage, and (2) the characteristics of rural families related to their patterns of coverage. FINDINGS: One out of 3 rural families has at least 1 uninsured member, a rate higher than for urban families-particularly in nonadjacent counties. Yet, three fourths of uninsured rural families have an insured member. For 42% of rural nonadjacent families, this is someone with public coverage (Medicaid/SCHIP or Medicare); urban families are more likely to have private health insurance or a private/public mix. CONCLUSIONS: Strategies to expand family coverage through employers may be less effective among rural nonadjacent than urban families. Instead, expansions of public coverage or tax credits enabling entire families to purchase an individual/self-employment plan would better ensure that rural nonadjacent families achieve full coverage. Subsidies or incentives would need to be generous enough to make coverage affordable for the 52% of uninsured rural nonadjacent families living below 200% of the federal poverty level.     

Public Health Insurance and Health Care Utilization for Children in Immigrant Families

Objectives To estimate the impacts of public health insurance coverage on health care utilization and unmet health care needs for children in immigrant families. Methods We use survey data from National Health Interview Survey (NHIS) (2001–2005) linked to data from Medical Expenditures Panel Survey (MEPS) (2003–2007) for children with siblings in families headed by at least one immigrant parent. We use logit models with family fixed effects. Results Compared to their siblings with public insurance, uninsured children in immigrant families have higher odds of having no usual source of care, having no health care visits in a 2 year period, having high Emergency Department reliance, and having unmet health care needs. We find no statistically significant difference in the odds of having annual well-child visits. Conclusions for practice Previous research may have underestimated the impact of public health insurance for children in immigrant families. Children in immigrant families would likely benefit considerably from expansions of public health insurance eligibility to cover all children, including children without citizenship. Immigrant families that include both insured and uninsured children may benefit from additional referral and outreach efforts from health care providers to ensure that uninsured children have the same access to health care as their publicly-insured siblings.     

The importance of public sector health care in an underserved population

California's employed Latinos are less likely to have private health insurance than most other segments of the US population and face a variety of other barriers to obtaining health care. To better understand the availability and adequacy of health services for these individuals, researchers analyzed data from a telephone survey of 1,000 randomly-selected, employed adults. Among all survey respondents, a significant percentage obtained their health care from sources fully or partially dependent on government financing. Among the uninsured (30.7 percent of the sample), a majority of those who had a regular source of care received services from publicly-supported providers. Dissatisfaction with care was infrequent (less than 5 percent of the total sample) and apparently no greater among those receiving care from public sources than among those served by private doctors. These findings underscore the importance of the public sector in providing health care for the underserved, the high quality of the services provided (or partially supported) by the public sector, and the seriousness of the consequences for the disadvantaged should public support for their healthcare diminish.     

Insurance Instability and Its Impact on Care of Young Adult Survivors of Pediatric Cancer: A Project Forward Study

By 2020, there will be more than 500,000 childhood cancer survivors (CCS) in the United States. CCS experience disparities in economic, social, and health-related quality of life outcomes, and these disparities are magnified for CCS who are uninsured. Access to long-term follow-up (LTFU) care for surveillance, preventive care, and treatment of late effects for survivors are vital to improve long-term outcomes. Inadequate insurance coverage, high out-of-pocket costs, and lack of perceived need for care have been shown to affect access to LTFU care among CCS. The objectives of this study were to (1) assess insurance instability longitudinally and describe patient factors that correlate with instability and (2) examine whether insurance instability and financial or patient factors influence access to LTFU care. Project Forward was a population-based, observational study of CCS in Los Angeles County using California Cancer Registry (CCR) data to identify participants who completed a survey. Change in insurance coverage was assessed at diagnosis using CCR data and at survey and its impact on LTFU care. Those who experienced any change in insurance coverage (“insurance instability”) were set equal to one. Multivariable logistic regression models incorporating survey nonresponse weights were used to estimate the change in the marginal predicted probabilities of insurance instability and LTFU care, adjusted for demographic, socioeconomic, and clinical covariates and clustered by treating hospital. Study participants were diagnosed with cancer between the ages of 0 and 19 while living in Los Angeles County between 1996 and 2010 and were older than 21 at the time of survey, from 2015 to 2017 (N = 1106). Almost half (48%; N = 529) of participants experienced insurance instability from diagnosis to survivorship, while 577 did not. After adjusting for demographic, socioeconomic, and clinical covariates, the multivariable model predicting insurance instability indicated that being uninsured at diagnosis or at survey increased the probability of instability by 37% (P < .001) and 58% (P < .001), respectively, in comparison with those with private insurance. The multivariable model predicting LTFU care indicated that those who experienced insurance instability decreased the probability of LTFU care by 5% (P < .05), in comparison with those who did not experience instability. When compared to those with private insurance coverage at diagnosis, participants who were covered by Medicaid, Medicare, or Indian Health Service plans at diagnosis were more likely to participate in LTFU care by 5% (P < .05); however, those who were uninsured at the time of the survey were less likely to participate in LTFU care by 10% (P < .05). CCS who were uninsured at diagnosis or survivorship were more likely to experience insurance instability. Insurance instability and being uninsured during survivorship were negatively associated with access to LTFU care; however, those with public insurance coverage at diagnosis were positively associated with access to LTFU care. Reducing insurance instability for CCS will improve access to LTFU care. This insight is key to improving health, reducing unnecessary and inappropriate health care use, and decreasing costs, while promoting services that can preserve and improve health for CCS. The study was funded by the National Institutes of Health.     

Does the US health care safety net discourage private insurance coverage?

The large and growing uninsured population poses an alarming threat to the US health care system, and is a major target of the Obama health reform. This paper investigates analytically and empirically the degree to which the absence of health insurance in the US reflects the availability of the health care safety net, such as the guaranteed or charitable care provided by emergency rooms, community health centers and physicians. Our theoretical model demonstrates that the safety net can be a real alternative to health insurance, thus discouraging private insurance purchase in the market setting. In particular, when the community premium rate fails to reflect the value of such resources, not purchasing insurance becomes a rational decision for a sizeable portion of the population. The calibrated simulation based on US statistics indicates about 15.75 % of the uninsured population, or 7.2 million people in US, are attributable to the existing safety net system. Further empirical analysis using nationally representative data shows consistently that the presence of local safety net resources may reduce the probability of individual insurance purchase by as much as 45.9 %.     

Association of Insurance Status with Patient Health at New Orleans Student-Run Free Clinics

Since the closure of Charity Hospital after Hurricane Katrina, New Orleans Student-Run Free Clinics have helped fill the resulting void in healthcare access for the underserved New Orleans population. To better understand the health insurance status and health outcomes of this patient population, 1036 patient records from seven New Orleans Student-Run Free Clinics were collected and analyzed between February 2017 and March 2020. Insurance status was significantly associated with gender, race, homelessness, and prior incarceration, but not with education. Substance use rehabilitation centers had low uninsured rates, while homeless shelters had higher uninsured rates. Patients on Non-Medicaid insurance were most likely to be prescribed a medication for diabetes (p?=?.01), hypertension (p?=?.21), and psychiatric conditions (p?=?.04), followed by those on Medicaid, and then those who were uninsured. This study demonstrates the benefits of health insurance and provides important data that can inform future health insurance enrollment efforts and health policy.

     

Health insurance coverage and self‐employment

BackgroundSelf‐employed workers are 10% of the US labor force, with growth projected over the next decade. Whether existing policy mechanisms are sufficient to ensure health insurance coverage for self‐employed workers, who do not have access to employer‐sponsored coverage, is unclear.ObjectiveTo determine whether self‐employment is associated with lack of health insurance coverage.Data SourcesSecondary analysis of Medical Expenditure Panel Survey (MEPS) data collected 2014‐2017.Study DesignParticipants were working age (18‐64 years), employed, civilian noninstitutionalized US adults with two years of Medical Expenditure Panel Survey (MEPS) participation in 2014‐2017. We compared those who were employees vs those who were self‐employed. Key outcomes were self‐report of health insurance coverage, and of delaying needed medical care.Data Extraction MethodsLongitudinal design among individuals who were employees during study year 1, comparing health insurance coverage among those who did vs did not transition to self‐employment in year 2.Principal Findings16 335 individuals, representing 121 473 345 working‐age adults, met inclusion criteria; of these, 147, representing 1 097 582 individuals, transitioned to self‐employment. In unadjusted analyses, 25.7% of those who became self‐employed were uninsured in year 2, vs 8.1% of those who remained employees (P < .0001). In adjusted models, self‐employment was associated with greater risk of being uninsured (26.1% vs 8.0%, risk difference 18.0%, 95% confidence interval [CI] 9.2% to 26.9%, P = .0001). A time‐by‐employment type product term suggests that 10.0 percentage points (95%CI 0.3 to 19.7 percentage points, P = .04) of the risk difference may be attributable to the change to self‐employment. Self‐employment was also associated with delaying needed medical care (12.0% vs 3.1%, risk difference: 8.9%, 95% CI 3.1% to 14.6%, P = .003).ConclusionsOne in four self‐employed workers lack health insurance coverage. Given the rise in self‐employment, it is imperative to identify ways to improve health care insurance access for self‐employed working‐age US adults.     

Uninsured Veterans Who Will Need to Obtain Insurance Coverage Under the Patient Protection and Affordable Care Act

Objectives. We examined the number and clinical needs of uninsured veterans, including those who will be eligible for the Medicaid expansion and health insurance exchanges in 2014.Methods. We analyzed weighted data for 8710 veterans from the 2010 National Survey of Veterans, classifying it by veterans’ age, income, household size, and insurance status.Results. Of 22 million veterans, about 7%, or more than 1.5 million, were uninsured and will need to obtain coverage by enrolling in US Department of Veterans Affairs (VA) care or the Medicaid expansion or by participating in the health insurance exchanges. Of those uninsured, 55%, or more than 800 000, are likely eligible for the Medicaid expansion if states implement it. Compared with veterans with any health coverage, those who were uninsured were younger and more likely to be single, Black, and low income and to have been deployed to Iraq and Afghanistan.Conclusions. The Patient Protection and Affordable Care Act is likely to have a considerable impact on uninsured veterans, which may have implications for the VA, the Medicaid expansion, and the health insurance exchanges.The Patient Protection and Affordable Care Act (ACA)1 represents one of the most significant overhauls of the US health care system and is expected to affect millions of uninsured people across the country. Military veterans constitute a particularly important segment of the population because of their service to the country, access to US Department of Veterans Affairs (VA) health care, and other special benefits after their service. However, little has been written on the potential impact of the ACA on the health and health care of veterans.2 Although the VA operates an integrated national health care system that offers free or low-cost services to eligible veterans, many veterans are not enrolled in VA health care, and some are ineligible. Enrollment in VA health care satisfies the ACA’s requirement for insurance coverage, but eligibility for VA health care is determined on the basis of a complex system of priorities, mostly based on service-connected disability, income, and age, and it generally requires a military service discharge that is other than dishonorable (i.e., honorable, general).One study estimated that only 13% (3.6 million) of veterans report receiving some or all of their health care at the VA, and the vast majority (> 20 million) receive no health care from the VA.3 Most veterans thus rely on non-VA health care and are covered by various private or other public forms of health insurance, including Medicare and Medicaid. A small, albeit important, minority of veterans have no health insurance coverage. Estimates based on data from 1987 to 2004 showed that 7.7% of veterans were uninsured (including having no VA coverage), which equates to nearly 1.8 million veterans and represents 4.7% of all uninsured US residents.4Lack of health insurance coverage is an important problem because it can hinder access to effective health care, including needed medical visits, preventive care, and other services, and it can ultimately lead to poor health, premature mortality, and high medical costs.5,6 Being uninsured is a growing problem in the United States that the ACA addresses by requiring virtually all legal US residents to have health insurance. The ACA includes various provisions to help US residents, including veterans, accomplish this.One major provision that is optional for states to implement is the expansion of Medicaid coverage to all individuals aged 18 to 65 years with incomes at or below 138% of the federal poverty level. Although not all states will implement this expansion, and the number of participating states is currently unknown, many poor, uninsured adults will be able to obtain Medicaid coverage in states that implement the Medicaid expansion. Uninsured adults who have incomes above the Medicaid expansion limit or who live in states that do not implement the Medicaid expansion will have to purchase health insurance and may participate in the health insurance exchanges.A second major provision of the ACA is the creation of health insurance exchanges in each state whereby individuals may purchase competitive health insurance plans that are eligible for federal subsidies, but those subsidies are only available to those with income above the federal poverty level. Both of these major ACA provisions are planned for implementation in 2014 and will introduce a variety of coverage options for US residents, including veterans.There has been little study of uninsured veterans and no study of the potential impact of the ACA on veterans in general. Moreover, most data that exist on veterans are based on VA data, which only contain information about veterans who use VA health services and do not include information about those who are uninsured or not covered by VA health care. However, 1 population-based study7 has provided some evidence that a substantial number of veterans are uninsured (particularly those younger than 65 years) and that many uninsured veterans are in poor health, often forego needed health care because of costs, and have equal or worse access to health care than other uninsured adults in the general population. As the country moves toward a new era of health care with the ACA and continues to engage in conflicts in the Middle East, the impact of the ACA on the health care of veterans needs to be considered.We used a recent nationally representative survey of veterans to (1) describe the proportion and characteristics of veterans who are currently uninsured because they will likely be required to obtain coverage under the ACA; (2) determine, among those who are uninsured, who will likely be eligible for the Medicaid expansion; and (3) compare the sociodemographic and health characteristics of those who are uninsured and likely eligible for Medicaid expansion (LEME), those who are uninsured and not LEME, and those who currently have health insurance coverage. The results provide information about the number and health characteristics of veterans who will likely be affected by different provisions of the ACA and inform planning efforts for the VA and states that implement the Medicaid expansion and health insurance exchanges.     

Alcohol,drug abuse,and mental health care for uninsured and insured adults

OBJECTIVE: To compare adults with different insurance coverage in care for alcohol, drug abuse, and mental health (ADM) problems. DATA SOURCES/STUDY SETTING: From a national telephone survey of 9,585 respondents. DESIGN: Follow-up of adult participants in the Community Tracking Study. DATA COLLECTION: Self-report survey of insurance plan (Medicare, Medicaid, unmanaged, fully, or partially managed private, or uninsured), ADM need, use of ADM services and treatments, and satisfaction with care in the last 12 months. PRINCIPAL METHODS: Logistic and linear regressions were used to compare persons by insurance type in ADM use. PRINCIPAL FINDINGS: The likelihood of ADM care was highest under Medicaid and lowest for the uninsured and those under Medicare. Perceived unmet need was highest for the uninsured and lowest under Medicare. Persons in fully rather than partially managed private plans tend to be more likely to have ADM care and ADM treatments given need. Satisfaction with care was high in public plans and low for the uninsured. CONCLUSIONS: The uninsured have the most problems with access to and quality of ADM care, relative to the somewhat comparable Medicaid population. Persons in fully managed plans had better rather than worse access and quality compared to partially managed plans, but findings are exploratory. Despite low ADM use, those with Medicare tend to be satisfied. Across plans, unmet need for ADM care was high, suggesting changes are needed in policy and practice.     

Recent Health Insurance Trends for US Families: Children Gain While Parents Lose

In the past decade, political and economic changes in the United States (US) have affected health insurance coverage for children and their parents. Most likely these policies have differentially affected coverage patterns for children (versus parents) and for low-income (versus high-income) families. We aimed to examine—qualitatively and quantitatively—the impact of changing health insurance coverage on US families. Primary data from interviews with Oregon families (2008–2010) were analyzed using an iterative process. Qualitative findings guided quantitative analyses of secondary data from the nationally-representative Medical Expenditure Panel Survey (MEPS) (1998–2009); we used Joinpoint Regression to assess average annual percent changes (AAPC) in health insurance trends, examining child and parent status and type of coverage stratified by income. Interviewees reported that although children gained coverage, parents lost coverage. MEPS analyses confirmed this trend; the percentage of children uninsured all year decreased from 9.6 % in 1998 to 6.1 % in 2009; AAPC = ?3.1 % (95 % confidence interval [CI] from ?5.1 to ?1.0), while the percentage of parents uninsured all year rose from 13.6 % in 1998 to 17.1 % in 2009, AAPC = 2.7 % (95 % CI 1.8–3.7). Low-income families experienced the most significant changes in coverage. Between 1998 and 2009, as US children gained health insurance, their parents lost coverage. Children’s health is adversely affected when parents are uninsured. Investigation beyond children’s coverage rates is needed to understand how health insurance policies and changing health insurance coverage trends are impacting children’s health.     

Insurance, acculturation, and health service utilization among Korean-Americans

This study describes the pattern and predictors of ambulatory care utilization among Korean Americans (KAs) living in Los Angeles. Data were gathered via a mail survey. Analysis employed a two-part model: logit model for factors affecting any health care use and truncated negative binomial model for frequency of use given one visit. Use of ambulatory care among KAs was low (2.80 visits during prior 12 months), compared to their counterparts in South Korea and the U.S. population. Variables associated with higher utilization included old age, health needs, and health insurance. Income had a positive effect on health care utilization decisions among the uninsured. Acculturation appeared to be neither a strong nor consistent predictor of ambulatory care utilization among KAs. Of particular concern is the finding that KAs suffer from inadequate access to care due to lack of employment-based health insurance.     

Estimates of health insurance coverage: comparing state surveys with the current population survey

The Census Bureau produces annual state-level estimates of health insurance coverage using the Current Population Survey (CPS) Annual Social and Economic Supplement. Many states also conduct their own population surveys of health insurance status; in most cases, the state survey estimates of uninsurance are lower than the estimates produced by the CPS. This discrepancy fuels debate about the true count of uninsured Americans and changes in that number over time. This paper compares state survey and CPS estimates of uninsurance, highlights key reasons for these differences, and discusses the policy implications of this persistent discrepancy.     

Insurance coverage and access: implications for health policy.

Data are presented from a recent survey of the United States population comparing the characteristics and levels of access to medical care of persons under 65 years who have group or individual private health insurance, public health insurance, or no third-party coverage. The uninsured group appeared to fall between the privately insured and publicly insured groups on measures of social and economic status. Persons with publicly subsidized forms of insurance coverage utilized services at the highest rates, and uninsured persons used them at the lowest rates. Neither of these groups was as satisfied with the convenience or the quality of the care it obtained as the privately insured group. Implications of these findings for national health insurance and other health policy initiatives are discussed.