Semantic management and interoperability of heterogeneous data in Intensive Care Units 12 8

Abstract

Efficient data management in Intensive Care Units (ICUs) represents a critical challenge for clinical decision-making and the competitiveness of modern healthcare systems. Despite the massive volume of information generated by the Internet of Medical Things (IoMT), the persistence of heterogeneous and unstructured formats fragments clinical knowledge and prevents a unified, real-time interpretation. The objective of this study is to develop a semantic interoperability framework based on dynamic ontologies to harmonize and integrate complex clinical data in critical care environments. Theoretically, the research is grounded in medical computer science, organizational knowledge management, and healthcare data governance theories. Methodologically, a quantitative and applied approach was adopted, employing ontological engineering techniques and automated data flow modeling (ETL). For validation, real clinical records were processed, structuring interdependent medical variables through semantic conceptual maps. The results demonstrate that the proposed framework accurately unifies disparate clinical terminology, eliminating redundancies and optimizing informational response times in the ICU. It is concluded that the implementation of this semantic management transcends the purely technological realm; it constitutes an essential strategic innovation in the knowledge economy that transforms fragmented data into intelligent clinical assets, thereby elevating patient safety and the operational efficiency of hospital organizations.