Introduction: The Réunion Registry of Congenital Malformations (Remacor) monitors these conditions for public health and research purposes. This monitoring involves the comprehensive collection of cases and the temporal analysis of their occurrence. To enable spatial analysis and the detection of health signals, Remacor retroactively geocoded the data and implemented spatial surveillance; the methodological choices are presented here. Materials and methods: Each case is geolocated based on the mother’s address. Birth-related prevalence rates are then calculated by aggregating cases according to different administrative scales. The choice of scale is determined using a Poisson test, which estimates the minimum number of births required to perform the analysis in a statistically significant manner, followed by a trade-off between the statistical significance of the information, data completeness, and spatial resolution. Results: It was possible to geolocate 95% of the cases. Various methods for detecting clusters of cases were used to identify the most affected areas. Finally, the clusters detected at different scales were intersected to calculate an index of presence at 1, 2, or 3 scales. Discussion and conclusion: The spatialized database now enables Remacor to account for the spatial heterogeneity in the distribution of the most common congenital malformations to inform public health stakeholders.