Published online Jul 8, 2015. doi: 10.4254/wjh.v7.i13.1782
Peer-review started: March 21, 2015
First decision: April 27, 2015
Revised: May 9, 2015
Accepted: June 15, 2015
Article in press: June 16, 2015
Published online: July 8, 2015
AIM: To illustrate the application and utility of Geographic Information System (GIS) in exploring patterns of liver transplantation. Specifically, we aim to describe the geographic distribution of transplant registrations and identify disparities in access to liver transplantation across United Network of Organ Sharing (UNOS) region 1.
METHODS: Based on UNOS data, the number of listed transplant candidates by ZIP code from 2003 to 2012 for Region 1 was obtained. Choropleth (color-coded) maps were used to visualize the geographic distribution of transplant registrations across the region. Spatial interaction analysis was used to analyze the geographic pattern of total transplant registrations by ZIP code. Factors tested included ZIP code log population and log distance from each ZIP code to the nearest transplant center; ZIP code population density; distance from the nearest city over 50000; and dummy variables for state residence and location in the southern portion of the region.
RESULTS: Visualization of transplant registrations revealed geographic disparities in organ allocation across Region 1. The total number of registrations was highest in the southern portion of the region. Spatial interaction analysis, after adjusting for the size of the underlying population, revealed statistically significant clustering of high and low rates in several geographic areas could not be predicted based solely on distance to the transplant center or density of population.
CONCLUSION: GIS represents a new method to evaluate the access to liver transplantation within one region and can be used to identify the presence of disparities and reasons for their existence in order to alleviate them.
Core tip: Geographic Information System (GIS) studies the impact of geography on many problems through statistical modeling and analysis. It has been used to guide decisions in business, government, environment, but has yet to be adopted in healthcare. Based on the United Network of Organ Sharing database from 2003 to 2012 in one region, GIS revealed clustering of high and low rates of listing for liver transplantation in several geographic areas that could not have otherwise been predicted. This method can be adopted in different parts of the world and contribute to better allocation of resources to decrease the disparities in access to liver transplantation.