Research Summary
This study presents an open-source neonatal intensive care unit (NICU) data dictionary consisting of 1,555 standardized clinical fields designed to harmonize patient documentation, device integration, clinical workflows, and quality indicators. Evaluated across two NICUs, the framework improved data quality, standardized clinical definitions, and enabled meaningful comparisons of practice variations and clinical outcomes while supporting interoperability and future AI-driven clinical decision support.
Critical care units generate enormous volumes of clinical, laboratory, and medical device data, yet most electronic medical record systems store this information in proprietary formats that limit interoperability and clinical research. This paper introduces a comprehensive, open-source neonatal intensive care unit (NICU) data dictionary designed to standardize clinical workflows, patient documentation, quality indicators, and medical device integration.
The proposed framework contains 1,555 standardized clinical fields covering patient admission, assessments, nutrition, medications, laboratory investigations, procedures, physiological monitoring, discharge summaries, and quality indicators. The system integrates bedside medical devices, laboratory systems, and electronic medical records while maintaining standardized definitions based on international neonatal guidelines.
The framework was prospectively evaluated across two Level III NICUs involving 344 neonates and demonstrated high data completeness, accuracy, validity, and timeliness while identifying important practice variations associated with neonatal outcomes. The standardized data model establishes a foundation for interoperable neonatal databases, multicenter research, clinical benchmarking, and future artificial intelligence applications in neonatal intensive care.