Development and Technical Validation of a Novel Digital Decision Support System for Automated CONUT Scoring and Anemia Risk Screening in Outpatient Care

Anemia represents a critical global public health challenge with high prevalence among women of reproductive age and children under five years. Despite its impact, early detection in outpatient settings remains limited due to the scarcity of objective tools that systematically integrate nutritional and hematological parameters for screening purposes. While the Controlling Nutritional Status (CONUT) index is a validated predictor of clinical outcomes, its application is often restricted to hospital settings and relies on manual calculation, which is prone to error and hinders adoption in primary care. In this study, we introduce CONUT-Digital, a novel digital tool designed not only to automate CONUT calculations but to explicitly integrate an automated anemia risk assessment directly into the nutritional screening workflow, addressing a critical gap in digital health tools for primary care. A retrospective study was conducted to validate the system using 60 real, anonymized clinical records selected to cover the full spectrum of nutritional risk categories. The CONUT-Digital system was compared against manual reference methods, demonstrating 100% agreement in total scores and nutritional classification while successfully processing multiple lymphocyte input formats. These results confirm that digitalization through this tool standardizes the assessment process, minimizes human error, and functions as a strategic screening mechanism to facilitate early detection of anemia risk. By linking routine biochemical parameters to automated clinical risk stratification, CONUT-Digital provides a robust support system for prioritizing nutritional interventions and strengthening public health management.