A key unmet need in contemporary health care is the effective utilization 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 al1 have eloquently demonstrated a novel approach to leveraging routinely collected administrative datasets to identify patients with end-stage kidney disease (ESKD). The methodology demonstrated illustrates how existing datasets can be more effectively leveraged, thereby minimizing data waste.