The Preston Medical Library in Knoxville, Tennessee has been incorporating GIS into its databases to identify areas of disparity between disabilities and socioeconomic factors using their Consumer and Patient Health Information Service (CAPHIS). Individuals call into CAPHIS when they require health information and the library staff facilitates by mailing brochures on the requested topic based on the literacy level of the caller. Notably, there seemed to be a correlation between socioeconomic status and limited literacy about health.
CAPHIS traditionally asks for the caller’s zipcode and some of their basic health information, but since most of the data is considered private, CAPHIS was limited to zipcode and a general idea of health as the data sets.To explore this, the Preston Medical Library used the GIS data gathered from the caller’s information to make six different maps. They used the zipcode and rate of calls from callers to propose a general map and concentration of areas where the conversations originated. Though their maps did not support their initial idea of a correlation, the maps were able to show where the prevalence of disease was higher and which diseases seemed to be spread in certain areas. Additionally, by combining the rate of call data with the disease spread, they were able to identify where there was a higher chance of disease and low call rate, indicating that the people there are not utilizing health data or are unaware of the service.
Because of this research, there has been some outreach programming by the government to have more specifically planned outreach programs. By examining GIS data before headquartering an outreach base, a location best suited for the expected clientele can be found. One of the biggest complaints about many outreach programs is that they are too far away from those who would benefit from them, so using GIS as an application to plan these developments will make them more successful and foresee where other potential outbreaks of disease will arise.
http://web.ebscohost.com/ehost/pdfviewer/pdfviewer?sid=3bcb0c18-0c14-4cbe-a91b-88759a77c0a0%40sessionmgr13&vid=4&hid=21
Socha, Y. M., Oelschlegel, S., Vaughn, C. J., & Earl, M. (2012). Improving an outreach service by analyzing the relationship of health information disparities to socioeconomic indicators using geographic information systems. Journal Of The Medical Library Association, 100(3), 222-225. doi:http://dx.doi.Org/10.3163/1536-5050.100.3.014
This is a good example of how when doing an GIS data analysis that expected outcomes may not come out. The researchers were expecting to see a correlation between socioeconomic status and limited literacy about health. They did not find this, but they did find that they can use the information mapped to the spread of disease and find area underserved. This is invaluable information and the secondary findings of the research had more value than the original research goals.
ReplyDeleteThis is really cool and I can see how this sort of research would really help the efficiency and effectiveness of such programs. I imagine programs like this are typically underfunded, so anything they can do make the largest impact is great. It can probably be easily adapted to fit all sorts of programs, including those in environmental studies, politics, etc.
ReplyDelete