A System for Workforce Sizing Optimization to Enhance Service Capacity in Primary Healthcare Units - Santos, Mateus; Tenório, Gabriela; Barros, Bruno J. S.; Nogueira, Bruno; Nascimento, Dimas Cassimiro; Pinheiro, Rian G. S. (Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI), 2026)
Research Context: The Brazilian Unified Health System faces overload due to high demand for emergency services. Primary Health Care (PHC) plays a central role in mitigating this issue but suffers from the uneven distribution of human resources. Scientific and/or Practical Problem: The lack of optimized strategies for professional allocation generates imbalances among PHC units, resulting in service deficits in some regions and underutilization in others. Proposed Solution and/or Analysis: This study proposes a decision support system that uses open health data and mathematical optimization models to reallocate professionals across primary healthcare units. The system is formulated as an Integer Linear Programming (ILP) problem, aiming to maximize the minimum Service Capacity Margin (MCA), which reflects the balance between supply and demand. Related IS Theory: The research draws on Information Systems theories focused on decision support, such as Decision Support Systems (DSS) Theory, and mathematical modeling approaches in organizational contexts. Research Method: An ILP model (MAX-MCA) was developed to allocate professionals by category in Primary Health Care units. Demand was estimated from sociodemographic data, distributed using Voronoi diagrams, and adjusted based on actual service production from public records. Supply was calculated from the weekly working hours of professionals and average productivity standards defined by the respective professional councils. Summary of Results: Experiments were conducted in the municipalities of Ribeirão Preto and Guarulhos. In both scenarios, the model eliminated deficits and increased MCA across all analyzed categories, demonstrating more balanced and efficient utilization of human resources. Contributions and Impact to IS area: This work illustrates how optimization models integrated with Information Systems can support decision-making, promoting greater equity and efficiency in resource allocation. The study contributes to advancing operational research applications in health management.