Improving quality of nursing homes (NHs) is a major social priority, yet few studies examine the role of facility characteristics for residents' quality of life (QOL). This study goes beyond cross-sectional analyses by examining the predictors of NH residents' QOL on the facility level over time. We used three data sources, namely resident interviews using a multidimensional measure of QOL collected in all Medicaid-certified NHs in Minnesota (N = 369), resident clinical data from the minimum data set, and facility-level characteristics. We examined change in six QOL domains from 2007 to 2010, using random coefficient models. Eighty-one facilities improved across most domains and 85 facilities declined. Size, staffing levels (especially activities staff), and resident case mix are some of the most salient predictors of QOL over time, but predictors differ by facility performance status. Understanding the predictors of facility QOL over time can help identify facility characteristics most appropriate for targeting with policy and programmatic interventions.

OBJECTIVES: This study examines the association of age and other sociodemographic variables with properties of personal networks; using samples of individuals residing in the rural western United States and the City of Los Angeles, we evaluate the degree to which these associations vary with geographical context. For both samples, we test the hypothesis that age is negatively associated with network size (i.e., degree) and positively associated with network multiplexity (the extent of overlap) on 6 different relations: core discussion members, social activity participants, emergency contacts, neighborhood safety contacts, job informants, and kin. We also examine the relationship between age and spatial proximity to alters. METHOD: Our data consist of a large-scale, spatially stratified egocentric network survey containing information about respondents and those to whom they are tied. We use Poisson regression to test our hypothesis regarding degree while adjusting for covariates, including education, gender, race, and self-reported sense of neighborhood belonging. We use multiple linear regression to test our hypotheses on multiplexity and distance to alters. RESULTS: For both rural and urban populations, we find a nonmonotone association between age and numbers of core discussants and emergency contacts, with rural populations also showing nonmonotone associations for social activity partners and kin. These nonmonotone relationships show a peak in expected degree at midlife, followed by an eventual decline. We find a decline in degree among the elderly for all relations in both populations. Age is positively associated with distance to nonhousehold alters for the rural population, although residential tenure is associated with shorter ego-alter distances in both rural and urban settings. Additionally, age is negatively associated with network multiplexity for both populations. DISCUSSION: Although personal network size ultimately declines with age, we find that increases for some relations extend well into late-midlife and most elders still maintain numerous contacts across diverse relations. The evidence we present suggests that older people tap into an wider variety of different network members for different types of relations than do younger people. This is true even for populations in rural settings, for whom immediate access to potential alters is more limited.

We examined whether and how lesbian, gay, and bisexual (LGB) adults between 40 and 65 years of age differ from heterosexual adults in long-term care (LTC) expectations. Our data were derived from the 2013 National Health Interview Survey. We used ordered logistic regression to compare the odds of expected future use of LTC among LGB (n=297) and heterosexual (n=13120) adults. We also used logistic regression models to assess the odds of expecting to use specific sources of care. All models controlled for key socioeconomic characteristics. Although LGB adults had greater expectations of needing LTC in the future than their heterosexual counterparts, that association was largely explained by sociodemographic and health differences. After control for these differentials, LGB adults were less likely to expect care from family and more likely to expect to use institutional care in old age. LGB adults may rely more heavily than heterosexual adults on formal systems of care. As the older population continues to diversify, nursing homes and assisted living facilities should work to ensure safety and culturally sensitive best practices for older LGB groups.

Most Americans know little about options for long-term services and supports and underestimate their likely future needs for such assistance. Using data from the 2012 National Health Interview Survey, we examined expectations about future use of long-term services and supports among adults ages 4065 and how these expectations varied by current living arrangement. We found differences by living arrangement in expectations about both future need for long-term services and supports and who would provide such care if needed. Respondents living with minor children were the least likely to expect to need long-term services and supports and to require paid care if the need arose. In contrast, respondents living alone were the most likely to expect that it was very likely that they would need long-term services and supports and to rely on paid care. Overall, we found a disconnect between expectations of use and likely future reality: 60 percent of respondents believed that they were unlikely to need long-term services and supports in the future, whereas the evidence suggests that nearly 70 percent of older adults will need them at some point. These findings both underscore the need for programs that encourage people to plan for long-term services and supports and indicate that information about living arrangements can be useful in developing and targeting such programs.

BACKGROUND: To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single goodness-of-fit (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. METHODS: We demonstrate the Pareto frontier approach in the calibration of 2 models: a simple, illustrative Markov model and a previously published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to 2 possible weighted-sum GOF scoring systems, and we compare the health economic conclusions arising from these different definitions of best-fitting. RESULTS: For the simple model, outcomes evaluated over the best-fitting input sets according to the 2 weighted-sum GOF schemes were virtually nonoverlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95% CI 72,500-87,600] v. $139,700 [95% CI 79,900-182,800] per quality-adjusted life-year [QALY] gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95% CI 64,900-156,200] per QALY gained). The TAVR model yielded similar results. CONCLUSIONS: Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets.

Close to two-thirds of all US nursing home residents have some type of cognitive impairment such as Alzheimer's disease, and the quality of care and quality of life of these people has long been called into question. In this overview we first clarify the ongoing importance of nursing home care for people with Alzheimer's, even as policy makers "rebalance" long-term supports and services with home and community-based programs. We next identify the components of optimal care for people with Alzheimer's in nursing homes, and we highlight care innovations already in use. Finally, we summarize policy-relevant challenges to implementing best practices and innovations and explore potential policy solutions. Federal and state policy makers have a critical role to play in ensuring that nursing home residents with Alzheimer's disease have access to the appropriate, high-quality care that they and their families expect.

BACKGROUND: The Affordable Care Act provides for the expansion of Medicaid, which may result in as many as 16 million people gaining health insurance coverage. Yet it is unclear to what extent this coverage expansion will meaningfully increase access to health care. OBJECTIVE: The objective of the study was to identify barriers that may persist even after individuals are moved to insurance and to explore racial/ethnic variation in problems accessing health care services. RESEARCH DESIGN: Data are from a 2008 cross-sectional mixed-mode survey (mail with telephone follow-up in 4 languages), which is unique in measuring a comprehensive set of barriers and in focusing on several select understudied ethnic groups. We examine racial/ethnic variation in cost and coverage, access, and provider-related barriers. The study adhered to a community-based participatory research process. SUBJECTS: Surveys were obtained from a stratified random sample of adults enrolled in Minnesota Health Care Programs who self-report ethnicity as white, African American, American Indian, Hispanic, Hmong, or Somali (n=1731). RESULTS: All enrollees reported barriers to getting needed care; enrollees from minority cultural groups (Hmong and American Indian in particular) were more likely to experience problems than whites. Barriers associated with cost and coverage were the most prevalent, with 72% of enrollees reporting 1 or more of these problems. Approximately 63% of enrollees reported 1 or more access barriers. Provider-related barriers were the least prevalent (about 29%) yet revealed the most pervasive disparities. CONCLUSIONS: Many challenges to care persist for publicly insured adults, particularly minority racial and ethnic groups. The ACA expansion of Medicaid, although necessary, is not sufficient for achieving improved and equitable access to care.

Research Objective: To investigate: (1.) How the risk of delayed medical care varies by household composition and (2.) Whether the relationship between household composition and delayed care differs by disability status. Study Design: Data are from the Integrated Health Interview Series (IHIS). Disability was defined by the presence of an activity limitation. Household composition is was constructed as living: with a spouse, alone, or with others. Respondents were asked whether they delayed care in the past year for several reasons, including: cost, difficulty making a timely appointment, limited office hours, difficulty getting through by phone, lack of transportation, or too long of a wait in the office. We used logistic regression to assess the odds of each type of delayed care, with sub-group analyses by disability status, controlling for demographic characteristics. Population Studied: Non-institutionalized adults aged 65 and older who answered questions on reasons for delayed medical care (n=17,663). Principal Findings: Fifteen percent of those living alone and with others delayed care for any reason vs. 10% of those living with a spouse. Older adults with disabilities had higher rates of delayed care than those without disabilities (18% vs. 10%). In multivariate models, having a disability was associated with higher odds of each type of delayed care. In sub-group analyses, living alone and living with others were associated with higher odds of delayed care due to cost or lack of transportation, compared with older adults living with a spouse, regardless of disability status. However, older adults without disabilities living alone had lower odds of delayed care due to difficulty getting a timely appointment, limited office hours, or long waits in the doctor's office if they lived alone, compared with those living with a spouse. Conclusions: Risk of delayed care is associated with both household composition and disability status. In particular, the risk of delayed care due to cost or lack of transportation is higher for older adults living alone or with others, compared with those living with a spouse. These relationships differ by disability status, however, and older adults living alone without a disability actually face lower odds of several types of delayed care compared with their counterparts living with a spouse. Implications for Policy, Delivery or Practice: Patterns of living arrangements for older adults have changed in recent decades, with a decline in institutionalization and an increase in multigenerational households. Such arrangements are impacted by disability, with older adults acting as caregivers (e.g., for spouses or grandchildren) and receiving care themselves (e.g., from spouses and adult children). Despite evidence of these changing patterns and complex roles, there is limited research on how household composition affects health services use. Delayed medical care can lead to poor health outcomes and increased risk of hospitalization or nursing home use, especially for older adults with complex medical conditions. Identifying who is at greatest risk of delayed care by household composition and disability status can help to target interventions, including home and community-based care and medical transportation.

Every school district has authority to determine how it will assign public school students to its schools. The principal assignment mechanism used by most school districts is to draw lines that comprise attendance zones. These zones designate the public school in which children should enroll given where they live. Some districts create sprawling, truly irregular attendance zones that pull children from far-flung neighbourhoods; others create compact zones that resemble regular-looking squares. Still, no one knows if and how many irregularly-shaped zones exist and whether they integrate or segregate students by race. This research addresses educational gerrymandering in three ways. First, it describes measures of four attendance zone properties: (1) shape; (2) internal racial diversity; (3) the distribution of racial groups across small areas within them; (4) the degree to which they exclude members of nearby racial groups in order to isolate the members of other racial groups. Second, it documents the correlations among these measures. The third and last contribution is to classify attendance zones into categories with the aim of identifying zones that represent the typical cases of shape irregularity and racial balance. To meet these goals, over 13,169 attendance zones embedded in 307 of the largest school districts are analyzed. Results indicate that educational gerrymandering is infrequent and when zones are shaped irregularly, they are almost always racially balanced.

BACKGROUND: Dual eligible Medicare and Medicaid beneficiaries consume disproportionate shares of both programs. OBJECTIVES: To compare Medicare and Medicaid expenditures of elderly dual eligible beneficiaries with non-dual eligible beneficiaries based on their long-term care (LTC) use. RESEARCH DESIGN: Secondary analysis of linked MAX and Medicare data in seven states. SUBJECTS: Dual eligible adults (65+) receiving LTC in institutions, in the community, or not at all; and Medicare non-dual eligibles. MEASURES: Medicaid acute medical and LTC expenditures per beneficiary year, Medicare expenditures. RESULTS: Among dual eligibles and non-dual eligibles, the average number of diseases and case mix scores are higher for LTC users. Adjusting for case mix virtually eliminates the difference for medical costs, but not for LTC expenditures. Adjusting for LTC status reduces the difference in LTC costs, but increases the difference in medical costs. CONCLUSIONS: Efforts to control costs for dual eligibles should target those in LTC while better coordinating medical and LTC expenditures.

Areal interpolation transforms data for a variable of interest from a set of source zones to estimate the same variable's distribution over a set of target zones. One common practice has been to guide interpolation by using ancillary control zones that are related to the variable of interest's spatial distribution. This guidance typically involves using source zone data to estimate the density of the variable of interest within each control zone. This article introduces a novel approach to density estimation, the geographically weighted expectation-maximization (GWEM) algorithm, which combines features of two previously used techniques, the expectation-maximization (EM) algorithm and geographically weighted regression. The EM algorithm provides a framework for incorporating proper constraints on data distributions, and using geographical weighting allows estimated control-zone density ratios to vary spatially. We assess the accuracy of GWEM by applying it with land-use/land-cover ancillary data to population counts from a nationwide sample of 1980 United States census tract pairs. We find that GWEM generally is more accurate in this setting than several previously studied methods. Because target-density weighting (TDW)-using 1970 tract densities to guide interpolation-outperforms GWEM in many cases, we also consider two GWEM-TDW hybrid approaches, and find them to improve estimates substantially.