A key unmet need in contemporary healthcare is the effective utilisation of large-scale health data through advanced software and machine learning, not only to enhance patient care delivery but also to inform strategic health service planning. Gao et al. have eloquently demonstrated a novel approach to leveraging routinely collected administrative datasets to identify patients with end-stage kidney disease (ESKD).1 This methodology demonstrated illustrates how existing datasets can be more effectively leveraged, thereby minimising data waste.