Clinical Team's Needs to Inform an Early Warning System for High-Risk Neonatal Conditions

High-risk newborns often present with clinical deterioration that is difficult to detect. In neonatal intensive care units (NICUs), conventional physiological monitoring and manual clinical assessments are associated with substantial operational burdens and high false alarm rates. With the surge in clinical data, frontline physicians and nurses need to screen for effective information to assist in decision making. Therefore, there is an urgent need to explore the requirements for data screening and automated information support in the early warning system for newborns.

This study aimed to explore the clinical demand for an intelligent early warning system and identify the primary obstacles clinical team face in the early recognition of condition changes among high-risk neonates. These findings provide a reference for improving clinical strategies and system designs.

A descriptive, qualitative research approach was used. Semi-structured interviews were conducted with 13 NICU healthcare professionals. Data were systematically analyzed using a directed content analysis method.

The interview content was synthesized into 3 primary themes and 8 subthemes: (1) high-risk factor profiling and early warning signals, (2) obstacles and challenges in identifying early disease changes, and (3) expectations regarding the functionalities of an information-intelligent system.

Nursing and hospital management should collaboratively advance staff training, information system upgrades, and clinical workflow optimization. Training should focus on enhancing staff's ability to identify risks, the system must ensure efficient information flow and timely alerts, and workflow optimization is crucial to ensure a rapid clinical response after risk identification.