Health-related quality of life in high-cost, high-need populations.

OBJECTIVES: To characterize patient-reported health and assess the psychometric performance of health-related quality of life (HRQOL) in high-cost, high-need (HCHN) populations. STUDY DESIGN: Retrospective longitudinal study examining health care utilization, expenditures, and patient-reported health comparing a baseline (year 1) and follow-up year (year 2). METHODS: The sample includes adults (n = 46,934) participating in the Medical Expenditure Panel Survey between 2011 and 2016. We estimated HRQOL for each sample member using the physical and mental health scales from the Medical Outcomes Study Short Form 12. We compared HRQOL stratified by HCHN, defined as patients whose baseline (year 1) demographics, utilization, and clinical characteristics predicted top decile health spending in year 2. Analyses assessed the validity, reliability, and responsiveness of physical and, separately, mental health scales. RESULTS: Among HCHN adults, the physical health scale exhibited robust measure validity, reliability, and responsiveness across all age groups; the mental health scale did not. Mean physical health was 1.25 SDs lower in HCHN vs other patients (37.9 vs 51.0 on a 0-100 scale increasing in self-perceived health; pooled SD, 10.5). Regressions indicated that a 0.5-SD increase in year 1 physical health among HCHN adults predicted a 5-percentage-point (10%) decrease in the probability of top decile health spending in year 2. In contrast to health care spending, HRQOL did not exhibit reversion to the mean in HCHN patients. CONCLUSIONS: Patient-reported health outcomes remain poor in HCHN populations, even after health care utilization recedes. HRQOL is a promising outcome measure for HCHN-focused payment and delivery interventions.

Predicting high-need cases among new Medicaid enrollees.

OBJECTIVES: 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. STUDY DESIGN: Retrospective cohort study. METHODS: 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. RESULTS: 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. CONCLUSIONS: Collecting self-reported health measures for a Medicaid expansion population can yield data of sufficient quality for predicting high-need cases.

The effects of expanding public insurance to rural low-income childless adults.

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.

Using self-reported health measures to predict high-need cases among Medicaid-eligible adults.

OBJECTIVE: To assess the ability of different self-reported health (SRH) measures to prospectively identify individuals with high future health care needs among adults eligible for Medicaid. DATA SOURCES: The 1997-2008 rounds of the National Health Interview Survey linked to the 1998-2009 rounds of the Medical Expenditure Panel Survey (n = 6,725). STUDY DESIGN: Multivariate logistic regression models are fitted for the following outcomes: having an inpatient visit; membership in the top decile of emergency room utilization; and membership in the top cost decile. We examine the incremental predictive ability of six different SRH domains (health conditions, mental health, access to care, health behaviors, health-related quality of life [HRQOL], and prior utilization) over a baseline model with sociodemographic characteristics. Models are evaluated using the c-statistic, integrated discrimination improvement, sensitivity, specificity, and predictive values. PRINCIPAL FINDINGS: Self-reports of prior utilization provide the greatest predictive improvement, followed by information on health conditions and HRQOL. Models including these three domains meet the standard threshold of acceptability (c-statistics range from 0.703 to 0.751). CONCLUSIONS: SRH measures provide a promising way to prospectively profile Medicaid-eligible adults by likely health care needs.

Understanding the gap in primary care access and use between teens and younger children.

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.

Why are low-income teens more likely to lack health insurance than their younger peers?

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 reform: impact on low-income families' enrollment and retention in public coverage.

OBJECTIVES: To examine the impact of a Wisconsin health care reform enacted in early 2008 on public insurance enrollment and retention. DATA SOURCES: Administrative data covering the period January 2007 to November 2009. STUDY DESIGN: We calculate unadjusted enrollment trends and exit rates stratified by age, income group, and enrollment mode. Kaplan-Meier curves and Cox proportional hazards models are estimated to assess the impact of the reform on program exits. PRINCIPAL FINDINGS: Overall enrollment increased by approximately one-third and exit rates decreased by approximately one-fifth. The majority of new enrollment came from the previously income eligible. CONCLUSIONS: Wisconsin's enactment of eligibility expansions coupled with administrative simplification and targeted marketing and outreach efforts were successful in enrolling and retaining low-income children and families in public coverage.

Medicaid expansions and the insurance coverage of poor teenagers.

This article employs a comparison group research design to examine the effects of the Medicaid expansions of the late 1990s on the insurance coverage of poor teenagers. Results suggest that the expansions were associated with a decrease in the likelihood of poor teens experiencing uninsured spells over the course of a calendar year, as measured by spending any part of the prior year uninsured and spending over half of the prior year uninsured. While the expansions were successful in increasing coverage among poor adolescents, they fell far short of facilitating near-universal coverage for this population.

Low-income mothers' social support and children's injuries.

This study examined the association between low-income mothers' perceived social support and the prevalence of their children's medically treated accidents and injuries. Data were drawn from the National Evaluation of Welfare-to-Work Strategies (NEWWS), an experimental evaluation of 11 welfare-to-work programs in seven U.S. cities. In regression models, maternal social support was significantly associated with the likelihood that children experienced an accident or injury between the ages of 8 and 10 such that children of mothers with very limited support were at the highest risk. This association was robust to the inclusion of a wide range of controls, including a prior measure of accident and injury occurrence. A primary finding was that only children whose mothers had the lowest levels of social support, characterized here as socially isolated, suffered significantly higher rates of injury. This suggests that social isolation presents a meaningful threat to child safety and may play an important role in the etiology of child injury among low-income families.

Partial-year insurance coverage and the health care utilization of children.

A large literature examines the effects of health insurance on the health care utilization of children; however, most existing studies conceptualize coverage as a point-in-time measure rather than as a dynamic phenomenon. The major contribution of this article is its provision of estimates on the relationship between the duration of coverage over the course of a calendar year and health care utilization among children. Using child-level fixed-effects regression, we find that an incremental uninsured month is associated with a 0.7 percentage point decline in the probability of receiving a visit over the course of a year and a 3% decrease in the number of visits received. Children with intrayear coverage losses are more likely than those with continuous coverage to lose their usual source of care, which serves as a potential mechanism through which short gaps in coverage may lead to longer-term decrements in utilization.

Reexamining the effects of family structure on children's access to care: the single-father family.

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.