2 resultados para Geodesic net

em DigitalCommons@The Texas Medical Center


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Introduction. It has been well established that poor uninsured children lack access to dental care and have greater dental needs than their insured counterparts. ^ Objective. To assess the capacity of Bexar County's dental safety net to treat children. To assess the dental needs of Bexar County children ages 0-18 who are uninsured or are Medicaid or SCHIP recipients. ^ Methods. Information was requested from dental safety net clinics that treat children ages 0-18. Data from the census, NHANES and other sources was used to estimate the dental needs. ^ Results. The capacity of the current safety net to treat children is 33,537 patient encounters per year. The dental needs of the community are 227,124 patient encounters per year. ^ Conclusion. The results of the study indicate that Bexar County is not prepared to treat the dental needs of the underserved children in San Antonio.^

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The aim of this study was to examine the association between determinants of access to healthcare and preventable hospitalizations, based on Davidson et al.'s framework for evaluating the effects of individual and community determinants on access to healthcare. The study population consisted of the low income, non-elderly, hospitalized adults residing in Harris County, Texas in 2004. The objectives of this study were to examine the proportion of the variance in preventable hospitalizations at the ZIP-code level, to analyze the association between the proximity to the nearest safety net clinic and preventable hospitalizations, to examine how the safety net capacity relates to preventable hospitalizations, to compare the relative strength of the associations of health insurance and the proximity to the nearest safety net clinic with preventable hospitalizations, and to estimate and compare the costs of preventable hospitalizations in Harris County with the average cost in the literature. The data were collected from Texas Health Care Information Collection (2004), Census 2000, and Project Safety Net (2004). A total of 61,841 eligible individuals were included in the final data analysis. A random-intercept multi-level model was constructed with two different levels of data: the individual level and the ZIP-code level. The results of this study suggest that ZIP-code characteristics explain about two percent of the variance in preventable hospitalizations and safety net capacity was marginally significantly associated with preventable hospitalizations (p= 0.062). Proximity to the nearest safety net clinic was not related to preventable hospitalizations; however, health insurance was significantly associated with a decreased risk of preventable hospitalization. The average direct cost was $6,466 per preventable hospitalization, which is significantly different from reports in the literature. ^