Changi General Hospital in Singapore is now developing and validating AI algorithms to predict the likelihood of patient deterioration as part of its smart remote health monitoring system.
WHAT IT’S ABOUT
The hospital has been collaborating with A*STAR medtech spinoff Respiree to develop a remote patient monitoring (RPM) system. It is one of the projects that CGH, Respiree and A*STAR are working on, backed with SG$1.35 million (over $950,000) in funding from the National Research Foundation Singapore.
The RPM system features a wearable sensor that tracks patients’ vital signs. It comprises a sensor patch and a finger oximeter linked to a central system or dashboard at the nurses’ workstation where they can view and check patients’ conditions at any time. The system currently measures respiratory rate, oxygen saturation and heart rate, and has the capability to flag any abnormal variation in vital parameters.
The wearable sensor’s accuracy and usability have been validated in two studies involving warded patients with respiratory diseases and COVID-19. Its performance for respiratory rate measurement has met the standard of the United States Food and Drug Administration; a temperature sensing capability will be added to the sensor soon following its validation.
Aside from developing predictive algorithms, CGH is also looking to monitor the vital signs of patients post-discharge at their homes to enable the continuity of care in the community setting.
WHY IT MATTERS
Vital signs monitoring can take up to three minutes per patient in a typical 40-bed general ward. CGH intends to reduce that time by introducing a smart monitoring system that allows nurses to spend more time on care or focus on other critical duties. This system, it noted, has the potential to save “up to 12 hours” of time spent on daily vital signs monitoring.
Aside from optimising time, the RPM system also provides early warning of potential patient deterioration, which then allows clinicians to carry out an early intervention.
THE LARGER TREND
CGH has made recent collaborations to develop innovative health technologies to improve patient care and experience. Together with the Singapore University of Technology and Design, the hospital unveiled last year a sensor for detecting bleeding from wound sites in real time. Called the Blood Warning Technology with Continuous Haemoglobin (BWatch) sensor, the device combines the properties of haemoglobin with a moisture-detecting sensor to differentiate blood from other bodily fluids to detect bleeding.
In 2020, CGH tied up with Integrated Health Information System to develop an AI predictive engine that determines the severity of pneumonia in COVID-19 patients based on chest x-ray images.