A Knowledge Representation Framework for Rare Diseases Governance within the Brazilian Healthcare System

Rare diseases (RDs), despite their low individual prevalence, collectively affect a significant portion of the population due to their wide variety and diversity. The management of RDs poses substantial informational, clinical, and managerial challenges, requiring coordinated action from multidisciplinary healthcare teams to ensure comprehensive and universal care, as mandated by Brazilian legislation. However, the knowledge necessary to support these complex processes is often fragmented or lacking. In this context, structured knowledge sharing is essential to promote integration among healthcare units, which act as interconnected nodes within a public health network. Knowledge representation techniques play a crucial role by identifying workflows, mapping knowledge gaps, externalizing tacit knowledge, and facilitating the dissemination of best practices. These approaches have the potential to enhance health planning and service efficiency. This study proposes the application of knowledge representation methods to improve the management and governance of RD services in the Brazilian public healthcare system. We employ validated strategies, including a knowledge management model adapted for public administration, process modeling and mapping methods, vocabulary standardization, and semantic ontology design. A reasoning tool was then applied to verify the consistency of the representations defined in the ontology. This contribution supports better decision-making, more effective resource allocation, improved service delivery, and stronger governance in high-complexity healthcare environments.