Online Program

Informing Community Health Planning by Enabling Decision Makers to Identify Health Disparities and Social Determinants with More Geographic Specificity

Tuesday, November 3, 2015

Karen Frederickson Comer, MLA, The Polis Center, Indiana University, Indianapolis, IN
Brian Dixon, PhD, Dept of Epidemiology, Richard M. Fairbanks School of Public Health, Indianapolis
Joseph Gibson, MPH, PhD, Marion County Public Health Department, Indianapolis, IN
Frank Zou, PhD, Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA
Marc Rosenman, MD, Department of Pediatrics, Indiana University School of Medicine & Regenstrief Institute, Indianapolis, IN
Health departments are in need of more geographically-specific indicators for their community health improvement planning efforts.  By supplying community health indicators at sub-county levels, we can improve the ability of public health professionals to identify and address local health disparities.  Furthermore, by facilitating the integration of health outcome indicators with indicators related to healthcare access and the socioeconomic environment, we can improve their ability to pursue multi-sector solutions to community health problems.

 Through a Robert Wood Johnson Foundation grant, the Richard M. Fairbanks School of Public Health, the Polis Center, the Marion County Public Health Department, Indiana University, and the Regenstrief Institute are using electronic health records (EHRs) to develop community health measures at geographic levels smaller than county (e.g., block group, census tract, neighborhood, and school corporation).  Multiple chronic disease indicators (e.g., prevalence of diabetes, prevalence of asthma, prevalence of depression) were identified by local health departments as high priority for prototype implementation.  Prototype indicators have been developed and integrated with socioeconomic indicators (e.g., race/ethnicity, age, poverty, income, housing) within a web-based, exploratory spatial data analysis (ESDA) tool that allows geographic associations to be identified via interactive scatterplots and linked maps. 

 Health departments are assisting in the validation of the prototype health indicators and evaluation of the usefulness of the ESDA implementation for identifying health disparities, targeting unmet community health needs, and considering social determinants of health.   Preliminary findings indicate that this approach is promising for the generation of more actionable information for community health planning. 

Learning Areas:

Communication and informatics
Program planning

Learning Objectives:
Describe the benefits of using more geographically granular data for community health improvement planning. Identify limitations in applying EHR data to measure community health. List information requirements for identifying geographic sub-populations relevant to community health planning.

Keyword(s): Health Disparities/Inequities, Geographic Information Systems (GIS)

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been a co-investigator and project director on multiple federally funded grants focusing on geospatially-enabling clinical records and integrating them with social indicators for improved public health practice. Since 1996, I have developed and led collaborations with communities at the local and national level to apply spatial information and community-based data to enhance their capacity for improvement.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.