2 resultados para Small areas
em DigitalCommons@The Texas Medical Center
Resumo:
Screening for latent tuberculosis infection (LTBI) is an integral component of an effective tuberculosis control strategy, but one that is often relegated to the lowest priority. In a state with higher than national average rates of tuberculosis, due consideration should be given to LTBI screening. Recent large scale contact investigations in the middle school of Del Rio, Texas, raised questions about the status of school screening for LTBI. An evidence based approach was used to evaluate school screening in high risk areas of Texas. A review of the literature revealed that the current recommendations for LTBI screening in children is based on administration of a risk factor questionnaire that should be based on the four main risk factors for LTBI in children that have been identified. Six representative areas in Texas were identified for evaluation of the occurrence of contact investigations in schools for the period of 2006 to 2009 and any use of school screening programs. Of the five reporting areas that responded, only one utilized a school screening program; this reporting area had the lowest percentage of contact investigations occurring in schools. Contact investigations were most common in middle schools and least common in elementary schools. In metropolitan areas, colleges represented up to 42.9% of contact investigations. The number of contact investigations has increased from 2006 to 2008. This report represents a small sample, and further research into the frequency, distribution and risk for contact investigations in schools and the efficacy of screening programs should be done. ^
Resumo:
The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^