Optimizing Live Kidney Donor Workup: A Decision Analysis Approach.

Abstract

Screening potential live kidney donors is an intense process for both candidates and the healthcare system. It is conventionally implemented using a standard generic protocol. Efficiencies in this process could potentially be achieved using personalized protocols that are optimized for a given candidate. Aim: To create personalized protocols (by age, sex, and paired exchange status) and evaluate them relative to the standard generic protocol. Two personalized protocols were created. One sequenced tests according to probability (high to low) of excluding a given candidate. The other sequenced tests according to the expected cost (low to high) per exclusion. Test costs and exclusion probabilities were extracted predominantly from Australian sources. These were integrated into a decision analysis incorporating Markov processes. This estimated the expected financial cost and expected number of tests performed to exclude an ineligible candidate in the standard generic and personalized protocols. The standard generic protocol consistently ranked poorest in terms of expected costs and expected tests per exclusion across all ages, sexes, and paired exchange status. Compared with the most efficient personalized protocol, the standard generic protocol was on average A$1767.49 more expensive and required 3.53 more tests. Personalized protocols enhance the ability of a kidney transplant unit to effectively exclude live kidney donor candidates more quickly and cost effectively compared with the conventional standard generic protocol.