Year: 2013
Type: article
Abstract: Severe geographic disparities exist in liver transplantation; for patients with comparable disease severity, 90-day transplant rates range from 18% to 86% and death rates range from 14% to 82% across donation service areas (DSAs). Broader sharing has been proposed to resolve geographic inequity; however, we hypothesized that the efficacy of broader sharing depends on the geographic partitions used. To determine the potential impact of redistricting on geographic disparity in disease severity at transplantation, we combined existing DSAs into novel regions using mathematical redistricting optimization. Optimized maps and current maps were evaluated using the Liver Simulated Allocation Model. Primary analysis was based on 6700 deceased donors, 28 063 liver transplant candidates, and 242 727 Model of End-Stage Liver Disease (MELD) changes in 2010. Fully regional sharing within the current regional map would paradoxically worsen geographic disparity (variance in MELD at transplantation increases from 11.2 to 13.5, p = 0.021), although it would decrease waitlist deaths (from 1368 to 1329, p = 0.002). In contrast, regional sharing within an optimized map would significantly reduce geographic disparity (to 7.0, p = 0.002) while achieving a larger decrease in waitlist deaths (to 1307, p = 0.002). Redistricting optimization, but not broader sharing alone, would reduce geographic disparity in allocation of livers for transplant across the United States.
DOI: 10.1111/ajt.12301
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,300
Funders: U.S. Department of Health and Human Services, University of Minnesota, Johns Hopkins University, Minneapolis Medical Research Foundation, National Institutes of Health, Health Resources and Services Administration, U.S. Public Health Service, Johns Hopkins Bloomberg School of Public Health, National Institute of Diabetes and Digestive and Kidney Diseases
OpenAlex ID: W2097027573