Background Prior studies have shown that racial/ethnic minorities have lower Consumer Assessments of Healthcare Providers and Systems (CAHPS®) scores. Perceived discrimination may mediate the relationship between race/ethnicity and patient experiences with care. Objective To examine the relationship between perceived discrimination based on race/ethnicity and Medicaid insurance and CAHPS® reports and ratings of care. Methods The study analyzed 2007 survey data from 1,509 Florida Medicaid beneficiaries. CAHPS® reports (getting needed care, timeliness of care, communication with doctor, and health plan customer service) and ratings (personal doctor, specialist care, overall health care, and health plan) of care were the primary outcome variables. Patient perceptions of discrimination based on their race/ethnicity and having Medicaid insurance were the primary independent variables. Regression analysis modeled the effect of perceptions of discrimination on CAHPS® reports and ratings controlling for age, gender, education, self-rated health status, race/ethnicity, survey language, and fee-for-service enrollment. Standard errors were corrected for correlation within plans. Results Medicaid beneficiaries reporting discrimination based on race/ethnicity had lower CAHPS® scores, ranging from 15 points lower (on a 0–100 scale) for getting needed care to 6 points lower for specialist rating, compared to those who never experienced discrimination. Similar results were obtained for perceived discrimination based on Medicaid insurance. Conclusions Perceptions of discrimination based on race/ethnicity and Medicaid insurance are prevalent and are associated with substantially lower CAHPS® reports and ratings of care. Practices must develop and implement strategies to reduce perceived discrimination among patients.
ABSTRACT. Purpose. Great variations exist in child health outcomes among states in the United States, with southern states consistently ranked among the lowest in the country. Investigation of the geographical distribution of children's health status and the regional factors contributing to these outcomes has been neglected. We attempted to identify the degree to which region of residence may be linked to health outcomes for children with the specific aim of determining whether living in the southern region of the United States is adversely associated with children's health status.Methods. A child health index (CHI) that ranked each state in the United States was computed by using statespecific composite scores generated from outcome measures for a number of indicators of child health. Five indicators for physical health were chosen (percent low birth weight infants, infant mortality rate, child death rate, teen death rate, and teen birth rates) based on their historic and routine use to define health outcomes in children. Indicators were calculated as rates or percentages. Standard scores were calculated for each state for each health indicator by subtracting the mean of the measures for all states from the observed measure for each state. Indicators related to social and economic status were considered to be variables that impact physical health, as opposed to indicators of physical health, and therefore were not used to generate the composite child health score. These variables were subsequently examined in this study as potential confounding variables. Mapping was used to redefine regional groupings of states, and parametric tests (2-sample t test, analysis of means, and analysis-of-variance F tests) were used to compare the means of the CHI scores for the regional groupings and test for statistical significance. Multipleregression analysis computed the relationship of region, social and economic indicators, and race to the CHI. Simple linear-regression analyses were used to assess the individual effect of each indicator.Results. A geographic region of contiguous states, characterized by their poor child health outcomes relative to other states and regions of the United States, exists within the "Deep South" (Mississippi, Louisiana, Arkansas, Tennessee, Alabama, Georgia, North Carolina, South Carolina, and Florida). This Deep-South region is statistically different in CHI scores from the US Census Bureau-defined grouping of states in the South. The mean of CHI scores for the Deep-South region was >1 SD below the mean of CHI scores for all states. In contrast, the CHI score means for each of the other 3 regions were all above the overall mean of CHI scores for all states. Regression analysis showed that living in the DeepSouth region is a stronger predictor of poor child health outcomes than other consistently collected and reported variables commonly used to predict children's health.Conclusions. The findings of this study indicate that region of residence in the United States is statistically related to imp...
The purpose of this study was to evaluate the outcomes of the social determinants component of a multiple determinants model of pre- and inter-conception care. Health department vital statistics and infectious disease data on birth and factors influencing birth outcomes were analyzed for participants in a program designed to mitigate the effects of social class and stress in contrast to a matched comparison group and other relevant populations. The program showed promising results related to reducing infant mortality and reducing other high-risk factors for poor birth outcomes, including low birth weight and sexually transmitted disease. Social determinant interventions, designed to mitigate the impact of social class and stress, should be considered with efforts to reduce infant mortality, particularly the disparities associated with infant mortality. Additional research should be conducted to refine replicable social determinant focused interventions and confirm and generalize these results.
The perinatal periods of risk (PPOR) methods provide a framework and tools to guide large urban communities in investigating their feto-infant mortality problem. The PPOR methods have 11 defined steps divided into three analytic parts: (1) Analytic Preparation; (2) Phase 1 Analysis-identifying the opportunity gaps or populations and risk periods with largest excess mortality; and (3) Phase 2 Analyses-investigating these opportunity gaps. This article focuses on the Phase 2 analytic methods, which systematically investigate the opportunity gaps to discover which risk and preventive factors are likely to have the largest effect on improving a community's feto-infant mortality rate and to provide additional information to better direct community prevention planning. This article describes the last three PPOR epidemiologic steps for investigating identified opportunity gaps: identifying the mechanism for excess mortality; estimating the prevalence of risk and preventive factors; and estimating the impact of these factors. While the three steps provide a common strategy, the specific analytic details are tailored for each of the four perinatal risk periods. This article describes the importance, prerequisites, alternative approaches, and challenges of the Phase 2 methods. Community examples of the methods also are provided.
Introduction Youth Risk Behavior Survey (YRBS) data have rarely been analyzed at the subcounty level. The purpose of this study was to explore the feasibility of such analysis and its potential to inform local policy and resource allocation.
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