Preserving paediatric data beyond the point of care

When caring for critically ill babies and children, clinician learning typically begins with the continuous stream of physiological data generated at the bedside. Much of this valuable information has traditionally been difficult to preserve once care has been delivered, limiting opportunities for clinical improvement, research and future innovation.

To address this, Big Data for Small People is a Sydney Children’s Hospitals Network (SCHN) clinician-led, research-driven program that seeks to securely preserve high-fidelity physiological data beyond the bedside. To help translate research into practical clinical applications, Philips is collaborating on the program — a collaboration that brings together SCHN’s clinical and research expertise with Philips’ Acute Care Informatics capabilities.

The program includes an automated digital infrastructure that securely captures and preserves data that provides valuable insights into how a child’s condition changes over time; the program being designed to provide clinicians and researchers with richer, more complete clinical information to investigate significant events, better understand complex cases and identify opportunities to improve patient safety and outcomes.

Philips’ High-fidelity Data Export (HFDE) enterprise clinical software is designed to enable continuous physiological signals, including waveforms and device alarms, to be securely captured and preserved from paediatric intensive care units, neonatal intensive care units and operating theatres — a solution that is being used to help SCHN establish a longitudinal clinical record that supports research, clinical audit and quality improvement.

By preserving these data beyond the point of care, it is intended that clinicians and researchers will be able to better understand complex cases, review clinically significant events and identify opportunities to improve patient safety and outcomes. The initiative also establishes a foundation for future capabilities, Philips said, including advanced visualisation, automated analysis, machine learning and AI-enabled clinical decision support.

Top image caption: Healthcare professionals reviewing clinical information together at Sydney Children’s Hospital. Credit: Westmead Children’s Hospital