Faculty Bibliography

Under Share 35, deceased donor (DD) livers are offered regionally to candidates with Model for End-Stage Liver Disease (MELD) scores ≥35 before being offered locally to candidates with MELD scores <35. Using Scientific Registry of Transplant Recipients data from June 2013 to June 2015, we identified 1768 DD livers exported to regional candidates with MELD scores ≥35 who were transplanted at a median MELD score of 39 (interquartile range [IQR] 37-40) with 30-day posttransplant survival of 96%. In total, 1764 (99.8%) exports had an ABO-compatible candidate in the recovering organ procurement organization (OPO), representing 1219 unique reprioritized candidates who would have had priority over the regional candidate under pre-Share 35 allocation. Reprioritized candidates had a median waitlist MELD score of 31 (IQR 27-34) when the liver was exported. Overall, 291 (24%) reprioritized candidates had a comparable MELD score (within 3 points of the regional recipient), and 209 (72%) were eventually transplanted in 11 days (IQR 3-38 days) using a local (50%), regional (50%) or national (<1%) liver; 60 (21%) died, 13 (4.5%) remained on the waitlist and nine (3.1%) were removed for other reasons. Of those eventually transplanted, MELD score did not increase in 57%; it increased by 1-3 points in 37% and by ≥4 points in 5.7% after the export. In three cases, OPOs exchanged regional exports within a 24-h window. The majority of comparable reprioritized candidates were not disadvantaged; however, 21% died after an export.

Redistricting, which means sharing organs in novel districts developed through mathematical optimization, has been proposed to reduce pervasive geographic disparities in access to liver transplantation. The economic impact of redistricting was evaluated with two distinct data sources, Medicare claims and the University HealthSystem Consortium (UHC). We estimated total Medicare payments under (i) the current allocation system (Share 35), (ii) full regional sharing, (iii) an eight-district plan, and (iv) a four-district plan for a simulated population of patients listed for liver transplant over 5 years, using the liver simulated allocation model. The model predicted 5-year transplant volumes (Share 35, 29,267; regional sharing, 29,005; eight districts, 29,034; four districts, 28,265) and a reduction in overall mortality, including listed and posttransplant patients, of up to 676 lives. Compared with current allocation, the eight-district plan was estimated to reduce payments for pretransplant care ($1638 million to $1506 million, p < 0.001), transplant episode ($5607 million to $5569 million, p < 0.03) and posttransplant care ($479 million to $488 million, p < 0.001). The eight-district plan was estimated to increase per-patient transportation costs for organs ($8988 to $11,874 per patient, p < 0.001) and UHC estimated hospital costs ($4699 per case). In summary, redistricting appears to be potentially cost saving for the health care system but will increase the cost of performing liver transplants for some transplant centers.

Concerns have been raised that optimized redistricting of liver allocation areas might have the unintended result of shifting livers from better-performing to poorer-performing organ procurement organizations (OPOs). We used liver simulated allocation modeling to simulate a 5-year period of liver sharing within either 4 or 8 optimized districts. We investigated whether each OPO's net liver import under redistricting would be correlated with 2 OPO performance metrics (observed to expected liver yield and liver donor conversion ratio), along with 2 other potential correlates (eligible deaths and incident listings above a Model for End-Stage Liver Disease score of 15). We found no evidence that livers would flow from better-performing OPOs to poorer-performing OPOs in either redistricting scenario. Instead, under these optimized redistricting plans, our simulations suggest that livers would flow from OPOs with more-than-expected eligible deaths toward those with fewer-than-expected eligible deaths and that livers would flow from OPOs with fewer-than-expected incident listings to those with more-than-expected incident listings; the latter is a pattern that is already established in the current allocation system. Redistricting liver distribution to reduce geographic inequity is expected to align liver allocation across the country with the distribution of supply and demand rather than transferring livers from better-performing OPOs to poorer-performing OPOs.