Singapore’s Changi General Hospital is currently developing and validating an AI algorithm to predict a patient’s likely deterioration as part of a smart remote health monitoring system.
about it
The hospital is working with A*STAR medtech spin-off Respiree to develop a remote patient monitoring (RPM) system. It is one of the projects CGH, Respiree and A*STAR are working on, and he has received S$1.35 million (over $950,000) in funding from the National Research Foundation of Singapore.
The RPM system features wearable sensors that track the patient’s vital signs. It consists of sensor patches and finger oximeters linked to a central system or dashboard at the nurse’s workstation, allowing the nurse to view and check the patient’s status at any time. The system now has the ability to measure respiratory rate, oxygen saturation, heart rate, and flag abnormal fluctuations in vital parameters.
The accuracy and ease of use of wearable sensors has been validated in two studies of respiratory disease and COVID-19 ward patients. Respiratory rate performance meets US Food and Drug Administration standards. Shortly after validation, temperature sensing capability will be added to the sensor.
Apart from developing predictive algorithms, CGH is also looking at monitoring patient’s vital signs at home after discharge to enable continuity of care in a community setting.
why it matters
In a typical 40-bed general ward, monitoring vital signs can take up to 3 minutes per patient. CGH plans to reduce that time by implementing a smart monitoring system that allows nurses to spend more time on care and focus on other important tasks. The system could save “up to 12 hours” of time spent on daily vital sign monitoring, he said.
In addition to optimizing time, the RPM system provides early warning of potential patient deterioration, enabling clinicians to implement early intervention.
the bigger trend
CGH recently collaborated to develop innovative health technologies to improve patient care and experience. Last year, the hospital, in collaboration with the Singapore University of Technology and Design, unveiled a sensor that detects bleeding from wound sites in real time. called continuous hemoglobin blood warning technology (B watch) sensor, the device combines the properties of hemoglobin with a moisture detection sensor to distinguish blood from other bodily fluids and detect bleeding.
In 2020, CGH partnered with Integrated Health Information System to AI prediction engine Determine the severity of pneumonia in COVID-19 patients based on chest radiographs.
