Market Competition and Density in Liver Transplantation: Relationship to Volume and Outcomes

Abstract

Background: Liver transplantation centers are unevenly distributed within the Donor Service Areas (DSAs) of the United States. This study assessed how market competition and liver transplantation center density are associated with liver transplantation volume within individual DSAs.

Study design: We conducted a retrospective cohort study of 53,156 adult liver transplants in 45 DSAs with 110 transplantation centers identified from the Scientific Registry of Transplant Recipients between 2003 and 2012. The following measures were derived annually for each DSA: market competition using the Herfindahl Hirschman Index, transplantation center density by the Average Nearest Neighbor method, liver quality by the Liver Donor Risk Index, and patient risk by the Model for End-Stage Liver Disease. A hierarchical mixed effects negative binomial regression model of the relationship between liver transplants and market factors was created annually. Patient and graft survival were investigated with a Cox proportional hazards model.

Results: Transplantation center density was associated with market competition (p < 0.0001), listings for organ transplantation (p < 0.0001), and Model for End-Stage Liver Disease at transplantation (p = 0.0005). More liver transplantation centers (incidence rate ratio [IRR] = 1.03; p = 0.04), greater market competition (IRR = 1.36; p = 0.02), increased listings (IRR = 1.14; p < 0.0001), more donors (IRR = 1.24; p < 0.0001), and higher Liver Donor Risk Index (IRR = 3.35; p < 0.0001) were associated with more transplants. No market variables were associated with increased mortality after transplantation.

Conclusions: After controlling for demographic and market factors, a greater concentration of centers was associated with more liver transplants without impacting overall survival. These results warrant additional investigation into the relationship between geospatial factors and liver transplantation volume with consideration for the optimization of scarce resources.