A Synergistic Bridge Between Human–Computer Interaction and Data Management Within CDSS

Clinical Decision Support Systems (CDSSs) have become indispensable in medical decision-making. The heterogeneity and vast volume of medical data require firm attention to data management and integration strategies. On the other hand, CDSS functionality must be enhanced through improved human–computer interaction (HCI) principles. This study investigates the bidirectional relationship between data management practices (specifically data entry management, data transformation, and data integration) and HCI principles within CDSSs. Through a novel framework and practical case studies, we demonstrate how high-quality data entry, driven by controlled workflows and automated technologies, is crucial for system usability and reliability. We explore the transformative positive impact of robust data management techniques, including standardization, normalization, and advanced integration solutions, on the HCI elements and overall system performance. Conversely, we illustrate how effective HCI design improves data quality by reducing cognitive load, minimizing errors, and fostering user engagement. The findings reveal a synergistic relationship between HCI and data science, providing actionable insights for designing intuitive and efficient CDSSs. This research bridges the gap between technical and human-centric approaches, advancing CDSS usability, decision accuracy, and clinician trust for better patient outcomes.