Robert M Cannon1, Ariann Nassel2, Jeffery T Walker3, Saulat S Sheikh1, Babak J Orandi1, Malay B Shah4, Raymond J Lynch5, David S Goldberg6, Jayme E Locke1. 1. Division of Transplantation, Department of Surgery, University of Alabama at Birmingham, Birmingham, AL. 2. University of Alabama at Birmingham, Lister Hill Center for Health Policy, Birmingham, AL. 3. University of Alabama at Birmingham, Center for the Study of Community Health, Birmingham, AL. 4. Division of Transplantation, Department of Surgery, University of Kentucky, Lexington, KY. 5. Division of Transplantation, Department of Surgery, Emory University, Atlanta, GA. 6. Division of Digestive Health and Liver Disease, Department of Medicine, University of Miami, Miami, FL.
Abstract
BACKGROUND: Much of our understanding regarding geographic issues in transplantation is based on statistical techniques that do not formally account for geography and is based on obsolete boundaries such as donation service area. METHODS: We applied spatial epidemiological techniques to analyze liver-related mortality and access to liver transplant services at the county level using data from the Centers for Disease Control and Prevention and Scientific Registry of Transplant Recipients from 2010 to 2018. RESULTS: There was a significant negative spatial correlation between transplant rates and liver-related mortality at the county level (Moran's I, -0.319; P = 0.001). Significant clusters were identified with high transplant rates and low liver-related mortality. Counties in geographic clusters with high ratios of liver transplants to liver-related deaths had more liver transplant centers within 150 nautical miles (6.7 versus 3.6 centers; P < 0.001) compared with all other counties, as did counties in geographic clusters with high ratios of waitlist additions to liver-related deaths (8.5 versus 2.5 centers; P < 0.001). The spatial correlation between waitlist mortality and overall liver-related mortality was positive (Moran's I, 0.060; P = 0.001) but weaker. Several areas with high waitlist mortality had some of the lowest overall liver-related mortality in the country. CONCLUSIONS: These data suggest that high waitlist mortality and allocation model for end-stage liver disease do not necessarily correlate with decreased access to transplant, whereas local transplant center density is associated with better access to waitlisting and transplant.
BACKGROUND: Much of our understanding regarding geographic issues in transplantation is based on statistical techniques that do not formally account for geography and is based on obsolete boundaries such as donation service area. METHODS: We applied spatial epidemiological techniques to analyze liver-related mortality and access to liver transplant services at the county level using data from the Centers for Disease Control and Prevention and Scientific Registry of Transplant Recipients from 2010 to 2018. RESULTS: There was a significant negative spatial correlation between transplant rates and liver-related mortality at the county level (Moran's I, -0.319; P = 0.001). Significant clusters were identified with high transplant rates and low liver-related mortality. Counties in geographic clusters with high ratios of liver transplants to liver-related deaths had more liver transplant centers within 150 nautical miles (6.7 versus 3.6 centers; P < 0.001) compared with all other counties, as did counties in geographic clusters with high ratios of waitlist additions to liver-related deaths (8.5 versus 2.5 centers; P < 0.001). The spatial correlation between waitlist mortality and overall liver-related mortality was positive (Moran's I, 0.060; P = 0.001) but weaker. Several areas with high waitlist mortality had some of the lowest overall liver-related mortality in the country. CONCLUSIONS: These data suggest that high waitlist mortality and allocation model for end-stage liver disease do not necessarily correlate with decreased access to transplant, whereas local transplant center density is associated with better access to waitlisting and transplant.
Authors: Robert M Cannon; Christopher M Jones; Eric G Davis; Glen A Franklin; Meera Gupta; Malay B Shah Journal: Am J Transplant Date: 2019-05-08 Impact factor: 8.086
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