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Assessing LSAMs ability to account for changes in organ donation and transplant center behavior.
Liver Transplantation 2024 April 30
BACKGROUND: The Liver Simulated Allocation Model (LSAM) is used to evaluate proposed organ allocation policies. Although LSAM has been shown to predict the directionality of changes in transplants and non-used organs, the magnitude is often overestimated. One reason is that policymakers and researchers using LSAM assume static levels of organ donation and center behavior because of challenges with predicting future behavior.
METHODS: We sought to assess the ability of LSAM to account for changes in organ donation and organ acceptance behavior using LSAM 2019. We ran 1-year simulations with the default model, and then ran simulations changing donor arrival rates (i.e., organ donation) and center acceptance behavior.
RESULTS: Changing the donor arrival rate was associated with a progressive simulated increase in transplants, with corresponding simulated decreases in waitlist deaths. Changing parameters related to organ acceptance was associated with important changes in transplants, non-used organs, and waitlist deaths in the expected direction in data simulations, although to a much lesser degree than changing the donor arrival rate. Increasing the donor arrival rate was associated with a marked decrease in the travel distance of donor livers in simulations.
CONCLUSION: We demonstrate that LSAM can account for changes in organ donation and organ acceptance in a manner aligned with historical precedent that can inform future policy analyses. As SRTR develops new simulation programs, the importance of considering changes in donation and center practice is critical to accurately estimate the impact of new allocation policies.
METHODS: We sought to assess the ability of LSAM to account for changes in organ donation and organ acceptance behavior using LSAM 2019. We ran 1-year simulations with the default model, and then ran simulations changing donor arrival rates (i.e., organ donation) and center acceptance behavior.
RESULTS: Changing the donor arrival rate was associated with a progressive simulated increase in transplants, with corresponding simulated decreases in waitlist deaths. Changing parameters related to organ acceptance was associated with important changes in transplants, non-used organs, and waitlist deaths in the expected direction in data simulations, although to a much lesser degree than changing the donor arrival rate. Increasing the donor arrival rate was associated with a marked decrease in the travel distance of donor livers in simulations.
CONCLUSION: We demonstrate that LSAM can account for changes in organ donation and organ acceptance in a manner aligned with historical precedent that can inform future policy analyses. As SRTR develops new simulation programs, the importance of considering changes in donation and center practice is critical to accurately estimate the impact of new allocation policies.
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