Changi General Hospital is developing AI-based patient deterioration prediction algorithms.
The project is part of the hospital’s intelligent remote health monitoring system.
As part of its smart remote health monitoring system, Changi General Hospital in Singapore is currently developing and validating AI algorithms to predict the likelihood of patient deterioration.
WHAT IT CONCERNS
The hospital has collaborated with the ASTAR-spinoff medtech company Respiree to develop a remote patient monitoring (RPM) system. It is one of the projects that CGH, Respiree, and ASTAR are working on, with funding from the National Research Foundation Singapore totaling over $950,000.
The RPM system includes a sensor worn by patients to monitor their vital signs. It consists of a sensor patch and a finger oximeter that are connected to a central system or dashboard at the nurses’ workstation, allowing them to monitor patients’ conditions at any time. Currently, the system measures respiratory rate, oxygen saturation, and heart rate, and is able to flag any abnormal variations in these vital parameters.
The accuracy and usability of the wearable sensor have been validated in two studies involving hospitalized patients with respiratory diseases and COVID-19. The sensor’s performance for measuring respiratory rate has met the requirements of the Food and Drug Administration; temperature sensing capabilities will be added to the sensor shortly after its validation.
In addition to developing predictive algorithms, CGH aims to monitor patients’ vital signs at home after discharge to ensure continuity of care in the community setting.
WHY IT MATTERS
Monitoring vital signs can take up to three minutes per patient on an average 40-bed general ward. CGH intends to reduce this time by implementing an intelligent monitoring system that enables nurses to devote more time to patient care or other crucial duties. It was noted that this system has the potential to save “up to 12 hours” per day on vital signs monitoring.
In addition to optimizing time, the RPM system provides clinicians with early warning of potential patient deterioration, allowing for early intervention.
THE LARGER TREND
CGH has recently formed partnerships to develop innovative health technologies to enhance patient care and satisfaction. Last year, the hospital and the Singapore University of Technology and Design unveiled a sensor for real-time detection of bleeding from wound sites. The device, known as the Blood Warning Technology with Continuous Haemoglobin (BWatch) sensor, combines the properties of haemoglobin with a moisture-detecting sensor to distinguish blood from other bodily fluids in order to detect bleeding.
In 2020, CGH collaborated with Integrated Health Information System to develop an AI-powered engine that analyzes chest x-rays to determine the severity of pneumonia in COVID-19 patients.
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