Optimized Proposed Location of Primary Healthcare Units: A Case Study in Alegre, Espírito Santo, Brazil - Almeida, Dalvan Ribeiro de; Bissoli, Dayan de Castro (Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI); 2026: Anais do XXII Simpósio Brasileiro de Sistemas de InformaçãoDO - 10.5753/sbsi.2026.248334, 2026)
Research Context: This study proposed the optimization of the location of Primary Healthcare Units (UBS) in the municipality of Alegre-ES, using high-resolution population density data and real road network data. The research integrated Geographic Information Systems (GIS) and combinatorial optimization techniques to support local planning in public health. Scientific and/or Practical Problem: The current distribution of UBS shows inequalities in access, resulting in longer distances traveled by the population, which compromises coverage, equity, and efficiency of basic healthcare delivery. Proposed Solution and/or Analysis: The p-median model was applied, solved with CPLEX, to identify optimal locations for UBS, considering real urban road distances. Scenarios comparing the current situation and optimized relocations were evaluated using distance metrics. Related IS Theory: The theoretical foundation involves decision support systems in Information Systems, location models, and the integration of large geospatial datasets for public policy formulation. Research Method: The methodology included extraction and aggregation of population data from the Brazil: High Resolution Population Density — Meta dataset, calculation of distances via OpenStreetMap, modeling the pmedian problem with CPLEX, and statistical and cartographic analysis of the results. Summary of Results: The results demonstrated that the relocation of Primary Health Care Units would reduce the average distance traveled by the population in all scenarios. In the best-case scenario, the reduction would reach 40,02%, potentially increasing coverage and promoting greater equity in access to healthcare services. Contributions and Impact to IS area: The study contributed a reproducible pipeline integrating Big Geodata, OpenStreetMap, and exact optimization, strengthening the interface between Information Systems, public health, and urban planning, providing valuable tools for municipal managers.