OBJECTIVES: This study aims to propose a new geographic administrative organization of Colombian municipalities for health-care management purposes. Rather than responding to arbitrary political boundaries, this division should answer to health needs and capacities, in order to facilitate the development of targeted policies to reach universal coverage and improve access to health services. METHODS: To achieve this, a big database was created: it contains information about different health-affecting topics: economic development, socio-cultural background, public and transportation services, environmental conditions and health indicators, supply and demand. These topics were measured with over 70 variables. After that, using a principal-component analysis, one or two indicators were created per topic. These indicators were used to build clusters that latter allowed the development of sanitary regions. Afterwards, another study was made in which people were tracked from their residence to the places where they received health services. Then, the country was divided into regions reflecting those migration flows. Finally, the study mingles both information -the clusters and migration networks- to determine a sanitary geography of Colombia. RESULTS: Using the methodology, this study proposes six clustering methodologies that are statistically significant and consistent with the reality of Colombia. Also, many networks were proposed, but 5 of them represented the national situation closely. Combining these alternatives, the study achieves its goal and creates a satisfactory segmentation of the country that is valuable for public policy.  CONCLUSIONS: The proposed categories serve well the needs that originated this study and are an appropriate framework for health-care management purposes. In fact, the Colombian Ministry of Health has used it as an input for telemedicine and first infancy projects and health-care reform. Its main conclusion is that health cannot be worked using political divisions. It is fundamental to use supply, demand and context criteria to determine regions useful for policymakers.