Automated Patient Monitoring and Decision Support in Intensive Care Units (ICUs)

Abstract

Intensive Care Units (ICUs) manage critically ill patients through continuous monitoring and life-sustaining interventions. Traditional monitoring systems, while essential, often suffer from data silos, alarm fatigue, and limited integration, hindering timely clinical decisions. In the recent past, the development of automation, biosensors, Internet of Things (IoT) systems, and artificial intelligence (AI) has revolutionized the care received in the ICU because patients and the ICU now have real-time data gathering, predictive analytics, and proactive intervention opportunities. Thus, the chapter discusses the history of automated monitoring and decision support in ICUs, their advantages, and disadvantages, and the future of the field, which is intelligent and patient-oriented care. Monitoring can be automated to decrease errors, streamline workflows, and improve patient safety, whereas Clinical Decision Support Systems (CDSS) offer evidence-based prescriptions and predictive analytics in complex clinical situations, such as sepsis and ventilator bundles. ICU operations are even more reinforced by the use of technological enablers such as big data analytics, cloud and edge computing, and robotics. Despite existing challenges, such as interoperability, data quality, and ethical concerns, the external factors that are increasing in popularity in critical care include these innovations.