A machine-learning approach to estimating public intentions to become a living kidney donor in England: Evidence from repeated cross-sectional survey data

ABSTRACT:

Background

Living kidney organ donors offer a cost-effective alternative to deceased organ donation. They enable patients with life-threatening conditions to receive grafts that would otherwise not be available, thereby creating space for other patients waiting for organs and contributing to reducing overall waiting times for organs. There is an emerging consensus that an increase in living donation could contribute even more than deceased donation to reducing inequalities in organ donation between different population sub-groups in England. Increasing living donation is thus a priority for National Health Service Blood and Transplant (NHSBT) in the United Kingdom.

Methods

Using the random forest model, a machine learning (ML) approach, this study analyzed eight waves of

SUBMITTER: Boadu P 

PROVIDER: S-EPMC9846224 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature