The HealthGap study aimed to understand cardiovascular risk among Indigenous Australians in Victoria using linked administrative data. A key challenge was differing spatial coverages of sources: state-level data for risk factors but cardiovascular outcomes for three hospitals. Catchments were defined based on hospital postcodes to estimate denominator populations for risk modelling: first- and second-order neighbours, and spatial distribution of outcomes (‘spatial event distribution’). Catchment coverage was assessed through proportions of patients presenting to study hospitals from catchment postcodes. The spatial event distribution performed best, capturing 82% events overall (first-order:40%; second-order:64%) and 65% Indigenous (27% and 45%). No approach excluded proximal non-study hospitals. Spatial event distributions could help define denominator populations when geographic information on outcome data is available but may not avoid potential misclassification. •Data linkage helps understand health risk in hard-to-reach populations.•Geospatial methods can be used to define at-risk populations in linked data studies.•Study aimed to identify geographical catchments for cardiovascular patients at three hospitals.•Generalisable geographical catchments (first- and second-order neighbours) were limited.•Catchments based on spatial distribution of cardiovascular events were preferred.