Newswise — New research from Cleveland Clinic and Case Western Reserve University about a model simulating interactions of lung organ donors and candidates over time to project outcomes has recently been published in the Journal of Heart and Lung Transplantation. Study authors are available for interviews about this newly published work.
As I'm sure you know, organ allocation policies determine how donor organs are distributed among patients awaiting transplant on the US transplant waiting lists. Periodic changes to these rules occur to decrease waitlist mortality, improve equity in access to transplant, and to reduce disparities.
Before implementing any policy, simulations are carried out for these hypothetical allocation strategies to determine which yields the most desirable outcomes. The new model described in this study, funded by NIH, resolves many of the issues in existing simulation models.
It uses synthetic populations reflecting current populations and doesn’t use populations from the past who are inherently different. This makes for more realistic forecasts so policymakers can be more certain of what will happen with less unintended consequences.
The agent-based simulation approach allows for studying relationships between “actors” in transplant – for example how a candidate’s survival may vary between transplant centers and no longer assuming that all candidates have the same access to transplant regardless of transplant center.
The modular framework allows more directed study and improvements to research in transplant outcomes.
This new way of simulating outcomes before new policies are adopted can not only be used for the lung transplant population but all other organ transplants.
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