Citation

Hardt NS, Muhamed S, Das R, Estrella R, Roth J. Perm. J. 2013; 17(1): 4-9.

Affiliation

Director of Health Disparities and Service Learning Programs, a Professor of Obstetrics and Gynecology, and a Professor of Pathology in the College of Medicine at the University of Florida in Gainesville. E-mail: hardt@ufl.edu .

Copyright

(Copyright © 2013, Kaiser Permanente)

DOI

10.7812/TPP/12-090

PMID

23596361

Abstract

Challenges to health care access in the US are forcing local policymakers and service delivery systems to find novel ways to address the shortage of primary care clinicians. The uninsured and underinsured face the greatest obstacles in accessing services. Geographic information systems mapping software was used to illustrate health disparities in Alachua County, FL; galvanize a community response; and direct reallocation of resources. The University of Florida Family Data Center created "hot spot" density maps of important health and social indicators to highlight the location of disparities at the neighborhood level. Maps were produced for Medicaid births, teen births, low birth weight, domestic violence incidents, child maltreatment reports, unexcused school absences, and juvenile justice referrals. Maps were widely shared with community partners, including local elected officials, law enforcement, educators, child welfare agencies, health care providers, and service organizations. This data sharing resulted in advocacy efforts to bring resources to the greatest-need neighborhoods in the county. Novel public-private partnerships were forged between the local library district, children and family service providers, and university administrators. Two major changes are detailed: a family resource center built in the neighborhood of greatest need and a mobile clinic staffed by physicians, nurses, physician assistants, health educators, and student and faculty volunteers. Density maps have several advantages. They require minimal explanation. Anyone familiar with local geographic features can quickly identify locations displaying health disparities. Personalizing health disparities by locating them geographically allows a community to translate data to action to improve health care access.

Language: en