Get to know Steve Sedlock, Executive Director of GeoHealth Innovations ? this week?s ConnectVA User Spotlight.
Tell us a little bit about yourself and your work.
Since I can remember, I have always been fascinated with geography and maps. My educational training has reflected this fascination, with an undergraduate degree in Geography from Virginia Tech, and a master?s degree in Urban and Regional Planning from Virginia Commonwealth University. Where things are, and why, are always at the forefront of my thinking. My professional career has been focused on the application of geographic information systems (GIS) technology across many industry sectors and fields of study. Since 1999, I have focused on GIS applications in the health and healthcare industry.
In leading GeoHealth Innovations since its birth in 2009, the company has focused on creating tools and analysis that incorporate the variable of place into the health equation. Where you live and work is as important as any other factor when it comes to understanding your health.
How does your organization help other non-profits?
Specifically, one of our most important initiatives at GeoHealth Innovations is the Virginia Atlas of Community Health: From INSIGHT to ACTION. With our partners at Community Health Solutions, the Atlas provides data and mapping to gain insight into the health of communities and regions. This insight is then turned into action through the Atlas knowledge base of industry perspectives and action guides. Our user community includes many non-profits and quasi-governmental entities, including free clinics, community service boards, health foundations, philanthropic organizations, associations, and many others.
What is coming on the horizon that excites you?
As we continue to introduce GIS as an analysis tool for health, I am excited about the technology?s predictive modeling capability. For example, a community or region may be working toward reducing diabetes incidence. GIS analysis has the ability to (1) look at the contributing social and environmental variables, (2) determine which variables are influencing the prevalence of diabetes, and (3) visualize how changes in those variables affect that prevalence.