CLINICAL DECISION SUPPORT SYSTEMS IN NEPHROLOGY: CURRENT APPLICATIONS, CHALLENGES AND PERSPECTIVES FOR CLINICAL PRACTICE

Abstract

Introduction: The digital transformation of healthcare services has expanded the use of clinical decision support systems as tools capable of integrating clinical information and assisting healthcare professionals in evidence-based decision-making. In nephrology, the complexity of managing patients with chronic kidney disease and those undergoing hemodialysis makes these technologies particularly relevant. Objectives: To analyze the current applications of clinical decision support systems in nephrology, as well as their benefits, implementation challenges, and future perspectives. Results: The literature demonstrates that these tools contribute to the early identification of chronic kidney disease, risk stratification, therapeutic optimization, complication monitoring, and quality indicator assessment in hemodialysis. Furthermore, artificial intelligence-based systems show potential for predicting relevant clinical outcomes and supporting earlier and more individualized interventions. Discussion: Despite the observed benefits, challenges related to data quality, system interoperability, technological infrastructure, alert fatigue, and professional adherence still limit their large-scale implementation. In the Brazilian context, these difficulties may be intensified by healthcare service heterogeneity and fragmented information systems. Final Considerations: Clinical decision support systems represent promising tools for nephrology practice, contributing to safer, more standardized, and data-driven care. Their consolidation will depend on the integration of technological innovation, scientific validation, and adaptation to the needs of different healthcare settings.