Utilization of the Community Assessment for Public Health Emergency Response (CASPER) Method to Identify Health Disparities – Johnson County, KS

Tuesday, June 6, 2017: 10:30 AM
440, Boise Centre
Elizabeth Holzschuh , Johnson County Department of Health and Environment, Olathe, KS
Abby Crow , Johnson County Department of Health and Environment, Olathe, KS
Ashley Follett , Johnson County Department of Health and Environment, Olathe, KS
Megan Foreman , Johnson County Department of Health and Environment, Olathe, KS
Barbara Mitchell , Johnson County Department of Health and Environment, Olathe, KS

BACKGROUND: Johnson County is the wealthiest, most populous, and fastest growing county in Kansas and consistently ranked as one of the state’s healthiest counties. There have been large increases in both the Hispanic/Latino population and the number of individuals living in poverty. In order to determine the health status and needs of these individuals, the Johnson County Department of Health and Environment (JCDHE) utilized the Community Assessment for Public Health Emergency Response (CASPER) methodology to compare low poverty with high poverty zip codes, which corresponds with the location of the county’s Hispanic population.

METHODS: U.S census data were used to identify the number of individuals living in poverty by zip code. Zip codes with more than 1,500 people living in poverty were classified as high poverty and the remainder as low poverty. For each of these two geographic areas, 30 census blocks were randomly selected, per CASPER methodology, and interview teams surveyed seven random households on a variety of topics including health behaviors, built environment, and access to care. Data were weighted and analyzed using SAS 9.4, and 95% confidence intervals were calculated to determine significance. Secondary data from the American Community Survey and vital statistics were used to supplement this assessment.

RESULTS: Survey sampling success rate was over the 80% goal, and demographic data were comparable to the American Community Survey estimates, providing a high level of confidence in the results. Significant differences were seen between high poverty and low poverty zip codes in per capita income and the percent of individuals obtaining higher education, but no difference in the percent of individuals employed. Individuals in high poverty zip codes were less likely to be insured, and were more likely to report financial barriers in obtaining care, including the ability to afford prescriptions. There was a greater percentage of individuals who reported that crime in their neighborhoods made it unsafe to go on walks. Mortality rates for five of the top ten leading causes of death were greater in high poverty zip codes.

CONCLUSIONS:  Through the utilization of CASPER, combined with secondary data sources, JCDHE was able to assess the health and needs of the county in a novel way. Differences in health care access, community safety, and mortality rates exist between the two geographies. Through this examination, JCDHE has been able to talk about poverty and health disparities in a new way that is easily understood by elected officials and the community.