Predicting Patient Deterioration

Using Continuous Monitoring and Concepts from the Field of Sports

Introduction
• Patients frequently demonstrate clinical signs of deterioration hours before a major event (transfers to intensive care unit or death).

• Continuous monitoring1 may improve patient outcomes and reduce costs.

• With EarlySense™ contact-free piezoelectric sensor, we were able to gather continuous measurement of heart rate, respiration rate, and body motion.

• The goal of this study was to test whether machine learning models based on features from continuous monitoring data and sports concepts can improve established Early Warning Scores such as MEWS2 (based on respiratory rate, heart rate, BP, urine output, temperature, and neurological signs)

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