This was a project the was completed in the Spring of 2012 in my advanced principles of GIS class. The purpose of this project was to identify areas on the Hawaiian island of Oahu that had limited/no access to proper healthcare. More specifically, areas with high Native Hawaiian and Pacific Islander population were also mapped and identified in order to determine whether or not the healthcare deserts were found in the same areas as the aforementioned populations.
In order to determine the "health care deserts" a variety of network analyst techniques were used. The first was a Service Area Network Analysis. To perform this analysis I first determined how large of an area each hospital/clinic should cover by taking the total area of the island and then dividing that by the number of facilities. This provided me with a reasonable assessment of how big of an area each facility should cover. This was step one in determining the healthcare deserts.
I then used another analysis to determine the areas of the island that had a distinctive lack of infrastructure, and thus poor access to healthcare facilities. To perform this analysis I started by geocoding all the healthcare facilities on the island. I then ran the create centroid tool on my census block data layer in order to create a usable reference point to be used in the network analysis. The closest facility analysis was then run and the centroids were connected with the facilities that they were closest to spatially. I then graphed the amount of centroids that each hospital connected to, and found a great disparity in the amount of blocks served. As one would expect, some of the larger hospitals in higher population areas serviced more census blocks, but 2 clinics did not service a single block.
Perhaps studies such as this could be used in the future to determine how to re-allocate medical resources or propose new infrastructure adjustments that would allow for greater accessibility to medical facilities. I believe this study could be replicated for many of the biggest cities across the United States and similar outcomes could be achieved.
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