simKAP: simulation framework for kidney allocation process with decision making models


  • Yunwei Zhang The University of Sydney
  • Anne Hu the University of Sydney
  • Yingxin Lin the University of Sydney
  • Yue Cao the University of Sydney
  • Jean Yang the University of Sydney
  • Germaine Wong the University of Sydney
  • Samuel Muller Macquarie University


Background: Organ shortage is a major barrier in transplantation and rules guarding organ allocation decisions should be robust, transparent, ethical and fair. Whilst numerous allocation strategies have been proposed, it is often unrealistic to evaluate all of them in real-life settings. Hence, the capability of conducting simulations prior to deployment is important. 

Aims: We aim to develop a flexible simulation framework for the Kidney Allocation Process (simKAP) that considers both the dynamic changes of the candidate waiting lists and a joint decision making process between the candidates and clinicians for deceased donor kidney transplantation.


Methods: There are three main phases in simKAP: (i) generating a list of transplant candidates with a dynamic Poisson process; (ii) defining the allocation rules; and (iii) modelling donor kidney acceptance that reflects a joint decision-making process. We evaluate our framework using both descriptive and quantitative measurements for allocation characteristics.

Results: Our findings indicate that the complete model with dynamic waiting-list modelling and shared decision making on organ acceptance shows the best agreement between actual and simulated data in almost all scenarios. Additionally, we demonstrate the flexibility and capacity of simKAP to deliver a quality assessment framework for allocation design by generating hypothetical risk-based allocation strategies.

Conclusions: To our knowledge, simKAP is the first kidney transplant allocation simulation process that provides end-to-end modelling from the arrival of recipients to the shared decision making. The importance of simKAP lies in its ability for policymakers in any transplant community to evaluate any proposed allocation algorithm using in-silico simulation.





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