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It might seem strange to ask whether increasing access to medical care can improve children's health. Yet Lindsey Leininger and Helen Levy begin by pointing out that access to care plays a smaller role than we might think, and that many other factors, such as those discussed elsewhere in this issue, strongly influence children's health. Nonetheless, they find that, on the whole, policies to improve access indeed improve children's health, with the caveat that context plays a big role-medical care "matters more at some times, or for some children, than others." Focusing on studies that can plausibly show a causal effect between policies to increase access and better health for children, and starting from an economic framework, they consider both the demand for and the supply of health care. On the demand side, they examine what happens when the government expands public insurance programs (such as Medicaid), or when parents are offered financial incentives to take their children to preventive appointments. On the supply side, they look at what happens when public insurance programs increase the payments that they offer to health-care providers, or when health-care providers are placed directly in schools where children spend their days. They also examine how the Affordable Care Act is likely to affect children's access to medical care. Leininger and Levy reach three main conclusions. First, despite tremendous progress in recent decades, not all children have insurance coverage, and immigrant children are especially vulnerable. Second, insurance coverage alone doesn't guarantee access to care, and insured children may still face barriers to getting the care they need. Finally, as this issue of Future of Children demonstrates, access to care is only one of the factors that policy makers should consider as they seek to make the nation's children healthier.

Objective This study measures the change in health care use after enrollment into a new public insurance program for low-income childless adults. Data Sources/Study Setting The data sources include claims from a large integrated health system in rural Wisconsin and Medicaid enrollment files, January 2007–September 2012. Study Design We employ a regression discontinuity design to measure the causal effect of public insurance enrollment on counts of outpatient, emergency department, and inpatient events for 2 years following enrollment for a sample of previously uninsured low-income adults in rural Wisconsin. Principal Findings Public insurance enrollment led to substantial increases in outpatient visits including preventive visits, but not mental health visits. Public insurance enrollment also led to increases in inpatient stays, but the study is inconclusive on whether it led to an increase in ED visits. Conclusions Public insurance expansions to childless adults have the potential to impact the use of health care. The large increase in Medicaid coverage and reduction in rates of uninsurance anticipated to result from the Affordable Care Act should increase the use of inpatient and outpatient services, but they will have an uncertain impact on the use of ED among rural populations.

Researchers have long been interested in the role that adverse economic conditions and experiences play in family processes and child behavior. Studies dating back to the Depression years of the 1930s have shown positive cor- relations among family economic distress and marital dissolution, family conflict, and child abuse and neglect (Conger, Conger, & Martin, 2010; Conger et al., 1990). A key theoretical concept reflected in these studies is that eco- nomic distress can be represented not only by objective measures of economic conditions but also by family members' subjective perceptions of economic experiences.Voydanoff (1990) articulated this perspective by arguing that family economic distress could be represented along four key dimensions: (a) employment instability, (b) employment uncertainty, (c) economic deprivation, and (d) economic strain. Employment instability and economic deprivation, she argued, are rela- tively objective factors indicating patterns of employment and changes in income over time. Economic deprivation, in her model, reflected families' income-to-needs ratio or poverty sta- tus. In contrast, employment uncertainty and economic strain are subjective indicators of an individual's perceived employment and financial situation. According to Voydanoff, economic strain is an evaluation of current financial status; it may reference perceived adequacy, financial concerns and worries, adjustments to changes in one's financial situation, or expectations about one's future financial situation (p. 1104).A widely used formulation of this concep- tual model was offered by Conger et al. (1990; see Figure 1, p. 646) and is referred to as the family stress model (see also Conger et al., 2010; Conger & Donnellan, 2007). The model predicts that adverse economic conditions such as low income, high debt levels, and employment instability generate economic strain or pressure reflecting subjective perceptions that one's cur- rent income is inadequate to meet one's needs. In this model, economic strain or pressure is a construct that reflects the types of frustrating experiences that are thought to increase parents' emotional distress and behavioral disturbances (Conger et al., 2010). Subsequent formulations of the model have proposed that parental emo- tional distress, marital discord, and relationship dissatisfaction spill over into parent-child rela- tionships, thereby increasing the risk for chil- dren's adjustment problems. Numerous studies across different economic periods and local con- texts have found support for this basic model (see Conger et al" 2010, for a review).A central tenet in the family stress model is that economic strain is related only indirectly to children's adjustment through its influence on the behavioral and emotional functioning of parents (Conger et al., 2010). However, other studies have shown that it is not necessary for parents' depressive symptoms or family conflict to rise in order for children to be adversely affected by their parents' experiences of eco- nomic strain. Children's adjustment can be directly affected by their observations of their parents' (or, indeed, their friends' and neigh- bors') economic strain (Ananat, Gassman-Pines, Francis, & Gibson-Davis, 2011; Barling, Dupre, & Hepburn, 1998; Barling, Zacharatos, & Hepburn, 1999; Hamilton, Noh, & Adlaf, 2009; Mistry, Benner, Tan, & Kim, 2009).The economic climate affecting the U.S. economy at the end of the past decade offers a new opportunity to extend and refine this theoretical model. First, as has been widely reported, this period saw record levels of employment instability (Greenstone & Looney, 2010), income losses (DeNavas-Walt, Proctor, & Smith, 2012), home mortgage foreclosure and delinquency (Mortgage Bankers Association, 2010), and food insecurity (Coleman-Jensen, Nord, Andrews, & Carlson, 2012). Given these stark figures, it is not surprising that large numbers of American families felt high levels of economic strain during the Great Recession (Gauthier & Furstenberg, 2010). …

Primary health care use among teenagers falls short of clinical recommendations and consistently lags behind that of younger children. Using the Medical Expenditure Panel Survey, the authors explore three explanations for this age-related gap: family composition, parental awareness of children’s health care needs, and the relative role of predisposing, enabling, and need-based factors for teens and younger children. Teenagers are 64% more likely to have no usual source of care and 25% more likely to have had no health care visit in the prior year relative to younger children. The gap narrows in families with children from both age-groups and among children with special health care needs. The largest disparity in primary care access exists between teens in families with no younger sibling(s) and younger children in families with no teen(s). A resolution to the age-related access gap will likely require understanding of, and intervention into, family-level determinants of poor access.

Low-income teenagers are more likely to lack health insurance than younger children. Using data from the 2006, 2007, and 2008 rounds of the National Health Interview Survey, we examine whether differences between teens and younger children in socioeconomic factors, public health insurance eligibility, and observable family characteristics explain this apparent age-related coverage gap. Somewhat surprisingly, they do not. We find a highly robust age-coverage gradient among poor and near-poor children. Our results suggest the need to examine teen-specific insurance enrollment dynamics, particularly in families with no younger siblings, to optimize the effect of the newly enacted Patient Protection and Affordable Care Act on teens' insurance coverage.

Wisconsin's BadgerCare Plus (BC+) program was designed to ensure access to health insurance coverage to virtually all Wisconsin children and to bolster coverage for parents and other caretaker adults. The program, launched in February 2008, expanded upon BadgerCare (Wisconsin's Children's Health Insurance Program) and Medicaid. BC+ combines its predecessor programs into one streamlined umbrella program and its introduction was characterized by the following reforms: an eligibility expansion augmented with an autoenrollment initiative; simplification of eligibility rules and enrollment and verification processes; and an aggressive marketing and outreach campaign. This paper provides estimates of the impact of the reform effort on program enrollment and the continuity of coverage. We find that the introduction of BC+ was associated with increases in enrollment and decreases in exit rates, suggesting that the Wisconsin experience may be instructive for other states interested in achieving similar aims.

Using data on approximately 2,000 low-income welfare recipients in a three-site random-assignment intervention conducted in the early 1990s (the NEWWS), we examine the role of cognitive and non-cognitive factors in moderating experimental impacts of an adult education training program for women who lacked a high school degree or GED at the time of random assignment. Both cognitive and noncognitive skills (in particular, locus of control) moderate treatment impacts. For the sample as a whole, assignment to an education-focused program had a statistically significant (albeit modest) 8 percentage point impact on the probability of degree receipt. For those with low cognitive skills, virtually all of these program impacts were eliminated. However, non-cognitive skills play a substantively important role such that women with high cognitive skills but low non-cognitive skills are only half as likely to earn a degree as their counterparts with high skills of both types. © 2008 by the Association for Public Policy Analysis and Management.

Objective. To examine the effects of family structure, focusing on the single-father family, on children's access to medical care. Data Source. The 1999 and 2002 rounds of the National Survey of America's Families (NSAF) including 62,193 children ages 0–17 years. Study Design. We employ a nationally representative sample of children residing in two-parent families, single-mother families, and single-father families. Multivariate logistic regression is used to examine the relationship between family structure and measures of access to care. We estimate stratified models on children below 200 percent of the federal poverty threshold and those above. Data Collection/Extraction Method. We combine data from the Focal Child and Adult Pair modules of the 1999 and 2002 waves of the NSAF. Principal Findings. Children who reside in single-father families exhibit poorer access to health care than children in other family structures. The stratified models suggest that, unlike residing in a single-mother family, the effects of residence in a single-father family do not vary by poverty status. Conclusions. Children in single-father families may be more vulnerable to health shocks than their peers in other family structures.

We designed a parent-directed home-visiting intervention targeting socioeconomic status (SES) disparities in children's early language environments. A randomized controlled trial was used to evaluate whether the intervention improved parents' knowledge of child language development and increased the amount and diversity of parent talk. Twenty-three mother–child dyads (12 experimental, 11 control, aged 1;5–3;0) participated in eight weekly hour-long home-visits. In the experimental group, but not the control group, parent knowledge of language development increased significantly one week and four months after the intervention. In lab-based observations, parent word types and tokens and child word types increased significantly one week, but not four months, post-intervention. In home-based observations, adult word tokens, conversational turn counts, and child vocalization counts increased significantly during the intervention, but not post-intervention. The results demonstrate the malleability of child-directed language behaviors and knowledge of child language development among low-SES parents.

To assess the ability of a short, self-reported health needs assessment (HNA) collected at the time of Medicaid enrollment to predict subsequent utilization and costs.Retrospective cohort study.We analyzed individual-level data that included self-reported HNAs, medical care encounter records, and administrative eligibility records for 34,087 childless adult Medicaid enrollees in Wisconsin, covering the period 2009-2010. High need was operationalized using the following outcome variables measured over the first year of program enrollment: having an inpatient admission; membership in the top decile of emergency department (ED) utilization; and membership in the top cost decile. We assessed the ability of the HNA to predict high-need cases using several complementary methods: the C-statistic; integrated discrimination improvement; and sensitivity, specificity, and positive predictive value resulting from multivariate logistic regression estimates.Using the HNA along with sociodemographic measures met the Hosmer-Lemeshow criterion for adequate predictive performance for the high ED and high cost outcomes (C-statistics of 0.74 and 0.72, respectively). The HNA was associated with large improvements in predictive performance over sociodemographic measures alone for all 3 dependent variables (integrated discrimination improvement of 182%, 413%, and 300% for ED, cost, and inpatient variables, respectively). The HNA also led to considerable improvements in sensitivity and positive predictive value with no resulting decreases in specificity or negative predictive value.Collecting self-reported health measures for a Medicaid expansion population can yield data of sufficient quality for predicting high-need cases.

Medicaid agencies are increasingly adopting care coordination and management strategies for their high-need beneficiaries, often with the twin goals of enhancing quality of care and reducing costs (Verdier, Byrd, and Stone 2009; Kim et al. 2013). This trend is likely to accelerate as states implement the Affordable Care Act's (ACA) new options to coordinate the care of chronically ill Medicaid beneficiaries (Kaiser Family Foundation 2011) and, in at least 28 states, expand Medicaid coverage to a larger population (Advisory Board 2013). To target high-need individuals, care management initiatives typically apply a case-finding approach that uses predictive models to stratify patients along likely future health care utilization (Knutson, Bella, and Llanos 2009; Verdier, Byrd, and Stone 2009). There is a mismatch, however, between the data requirements of these models, which rely on historical medical claims, and the data available to Medicaid programs for both new and “churning” beneficiaries, of whom states expect increasing numbers under the ACA (Knutson, Bella, and Llanos 2009). This article proposes and tests a practical alternative to a claims-based algorithm for identifying high-need Medicaid beneficiaries, one that relies upon well-validated self-reported health (SRH) measures that states or managed care organizations (MCOs) may potentially collect during the initial application and enrollment process.

The Patient Protection and Affordable Care Act (ACA) relies heavily on the expansion of Medicaid eligibility to cover uninsured populations. In February 2008, Wisconsin expanded and reformed its Medicaid/CHIP program and, as part of program implementation, automatically enrolled a set of newly eligible parents and children. This process of “auto-enrollment” targeted newly eligible parents and older children whose children/siblings were already enrolled in the state's Medicaid/CHIP program. Auto-enrollment brought over 44,000 individuals into the program, representing more than 60% of all enrollees in the first month of the reformed program. Individuals who were auto-enrolled were modestly more likely to leave the program relative to other individuals who enrolled in February 2008, unless their incomes were high enough to be required to pay premiums; these auto-enrollees were much more likely to exit relative to other enrollees subject to premium payments. The higher exit rates exhibited by non-premium paying auto-enrollees were likely due to the fact that over 40% of auto-enrollees were covered by a private insurance policy in the month of their enrollment, compared to approximately 30% for regular enrollees. A national simulation of an auto-enrollment process similar to Wisconsin's, including the expansion of adult Medicaid eligibility to 133% of the federal poverty level under the ACA, suggests that 2.5 million of the 5.6 million newly eligible parents could be auto-enrolled, and approximately 25% of this population would be privately insured. These results suggest that auto-enrollment may be appropriate for other states, especially in their efforts to enroll eligible populations who are not subject to premium requirements.

As states consider expanding Medicaid to low-income childless adults under the Affordable Care Act, their decisions will depend, in part, on how such coverage may affect the use of medical care. In 2009 Wisconsin created a new public insurance program for low-income uninsured childless adults. We analyzed administrative claims data spanning 2008 and 2009 using a case-crossover study design on a population of 9,619 Wisconsin residents with very low incomes who were automatically enrolled in this program in January 2009. In the twelve months following enrollment in public insurance, outpatient visits for the study population increased 29 percent, and emergency department visits increased 46 percent. Inpatient hospitalizations declined 59 percent, and preventable hospitalizations fell 48 percent. These results demonstrate that public insurance coverage expansions to childless adults have the potential to improve health and reduce costs by increasing access to outpatient care and reducing hospitalizations.

CME Educational Objectives 1. Provide a definition of access to care and its correlates in the pediatric population. 2. Discuss recent policy initiatives that have targeted improving access to quality health care for children. 3. Recommend policy changes that improve pediatric access to care and promote the health of children. Research consistently demonstrates the centrality of having access to medical care in the production of good health. 1–4 Illustratively, the important role that access to care plays in promoting pediatric health is echoed throughout the articles in this issue. Whether fighting communicable disease, providing behavioral health services to at-risk adolescents, or managing chronic physical conditions (such as asthma), achieving key pediatric health goals is crucially dependent upon the presence and accessibility of high-quality health care services.

To examine the effects of family structure, focusing on the single-father family, on children's access to medical care.The 1999 and 2002 rounds of the National Survey of America's Families (NSAF) including 62,193 children ages 0-17 years.We employ a nationally representative sample of children residing in two-parent families, single-mother families, and single-father families. Multivariate logistic regression is used to examine the relationship between family structure and measures of access to care. We estimate stratified models on children below 200 percent of the federal poverty threshold and those above.We combine data from the Focal Child and Adult Pair modules of the 1999 and 2002 waves of the NSAF.Children who reside in single-father families exhibit poorer access to health care than children in other family structures. The stratified models suggest that, unlike residing in a single-mother family, the effects of residence in a single-father family do not vary by poverty status.Children in single-father families may be more vulnerable to health shocks than their peers in other family structures.

We use administrative data from Wisconsin to determine the fraction of new Medicaid enrollees who have private health insurance at the time of enrollment in the program. Through the linkage of several administrative data sources not previously used for research, we are able to observe coverage status directly for a large fraction of enrollees and indirectly for the remainder. We provide strict bounds for the percentages in each status and find that the percentage of new enrollees with private insurance coverage at the time of enrollment lies between 16 percent and 29 percent, and the percentage that dropped private coverage in favor of public insurance lies between 4 percent and 18 percent. Our point estimates indicate that, among all new enrollees, 21 percent had private health insurance at the time of enrollment and that 10 percent dropped this coverage. Our results show substantially lower rates than previous studies of crowd-out following public health insurance expansions and significant rates of dual coverage, whereby new enrollees into public insurance retain their previously held private insurance coverage.