Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

Abstract #108348

Patricia Gail Bray, PhD¹, Thomas F. Reynolds, MS¹, Carla M. Cooper, PhD¹, Kim Lopez, MPH², and Ilana Reisz, PhD(c)². (1) Community Health Assessment, St. Luke's Episcopal Health Charities, 3100 Main Street, Suite 800, Houston, TX 77002, (2) St. Luke's Episcopal Health Charities, 3100 Main St., Suite 800, Houston, TX 77002, 832-355-7229, ireisz@sleh.com

St. Luke's Episcopal Health Charities, a public charity, and The University of Texas School of Public Health, developed a web-based Community Health Information System that includes fourteen years of population data, vital statistics, education data and data regarding over 12,000 health and human service agencies. One new feature of the CHIS is a web-based interactive mapping component, identifying who and where the 1.1 million uninsured live in Harris County.

Texas leads the nation in the number of uninsured and Houston leads the state in the number of uninsured, estimated to be almost one-third of the population. Due to the unprecedented number of uninsured in Houston and Texas, the local Chamber of Commerce spearheaded a countywide public health planning effort. Our role was to develop a synthetic estimation of identifying the uninsured at a sub-county level of analysis. The data source used was the 2003 Current Population Survey from the U.S. Census Bureau.

Once we calculated the uninsured at the census tract level, then we geocoded the estimates, mapped them to print on static maps, and set up an interactive web-based system so that users could see the different rates by poverty level, race/ethnicity, age and political jurisdiction. The findings from this project now serve as the baseline for the newly created Public Health Advisory Council, charged with enhancing the public health infrastructure for the entire area.

Learning Objectives:

• 1. Learn how we replicated a synthetic estimation study to estimate the uninsured.
• 2. Observe how we used GIS to map the estimated uninsured in a large metropolitan area.
• 3. Explore how to integrate data into large scale planning efforts.

Keywords: Underserved Populations, Health Care Restructuring

Related Web page: www.slehc.org

Presenting author's disclosure statement:

I wish to disclose that I have NO financial interests or other relationship with the manufactures of commercial products, suppliers of commercial services or commercial supporters.