Special Projects Fund

Project Title

Enhancing Rural Health Surveillance by Using Geospatial Analysis to Identify Local Disease Hot Spots

Grant Amount

$300,000

Priority Area

Special Projects Fund

Date Awarded

October 24, 2016

Region

Hudson Valley

NYC

Status

Closed

Website

http://www.gishealth.org

Without the necessary resources to perform sophisticated health surveillance, Sullivan County Public Health Services is limited in its ability to target and prioritize initiatives to help improve health outcomes for the county’s residents, of whom more than 80% live in rural regions.

Accurately capturing and estimating health surveillance data to pinpoint the health needs of residents is often too costly or labor intensive for most rural health departments. To address this issue, New York University School of Medicine’s (NYU) Health Geographics Research Initiative has developed a method for using data to create highly detailed and localized maps of disease burden. In 2016, NYSHealth awarded a grant to NYU to work with Sullivan County Public Health Services on developing and validating its method to enhance rural health surveillance.

Under this grant, NYU partnered with Sullivan County Public Health Services to demonstrate NYU’s health surveillance method for identifying local hot spots of disease burden. Specifically, NYU conducted a countywide health survey in Sullivan County—the largest ever performed in the county’s history. NYU used emergency claims data from the New York State Department of Health, existing geographic health data from Sullivan County, and address data for county residents to conduct a geospatial analysis and create detailed maps of specific health issues pertinent to Sullivan County Public Health Services. Sullivan County Public Health Services used the maps to inform its health priority setting and intervention planning. NYU disseminated the study results to the general population in Sullivan County and published its findings in peer-reviewed journals, and worked with other rural health networks to demonstrate the value of this work and encourage those networks to replicate it.