SINGAPORE – Every minute is precious to nurses, said senior staff nurse Lee Jie Yin.
This is why she welcomes the use of artificial intelligence (AI) technology that senses when patients leave their bed, as it saves her valuable time.
Before the introduction of this technology in 2022, Ms Lee, 23, had to manually set up a fall sensor mat on each patient’s bed. These sensor mats are provided to patients with a fall risk.
Setting up the mats takes time, and they are not the most accurate sensors, said Ms Lee, who works at Tan Tock Seng Hospital (TTSH).
“This new technology saves me up to 10 minutes per patient in terms of setting up, which frees me to attend to other patients’ needs,” she said, adding that she also no longer has to do daily inventory checks on the mats.
Called PreSAGE, the AI system is designed to predict when a patient might leave their bed, using thermography – a technology that uses infrared cameras to detect heat patterns and create images – and video analysis.
Each sensor monitors one patient, and is attached to the wall above the television in the patient’s room, which has a full view of the room. It is programmed to recognise “boundaries”, or an area that the patient should be in to be considered safe.
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Each sensor monitors one patient. ST PHOTO: NG SOR LUAN
When the patient leaves the bed, the sensor detects that the patient is no longer on the bed, and possibly in an unsafe situation, and triggers an alarm.
The alarm will sound outside their room, accompanied by a flashing blue light.
Nurses will then rush to the room within one minute.
The alarm will deactivate when a second person is detected in the sensor’s field of view, which is an indication that there is someone assisting the patient.
Other features include a system dashboard that can be accessed from any computer, and allows nurses to monitor the patient and control the boundaries of the sensor.
It also includes active monitoring when a patient is left alone in the room, which assists nurses during busy periods, Ms Lee said.
“The technology provides us early warning signs as a prediction system, and it can actually tell us that the patient needs help before anything serious happens to them,” she added.
The system, which does not require patient-nurse contact, also informs nurses when a patient is resting, so that they do not disturb the patient.
PreSAGE is used in 26 wards, or 84 per cent of TTSH’s single and isolation room wards, and the hospital plans to roll it out to all such wards by the end of March.
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The hospital is also testing how the system works in a room with multiple patients.
Ms Lee, who has been a nurse for more than two years, said that she was trained to use PreSAGE when she joined TTSH.
“I was especially excited to learn about this new technology, as I look forward to anything that can help us nurses reduce our workload and increase our efficiency.”
She added that it also helped that the technology was user-friendly, which saved her time during the training.
However, the technology does have its limitations.
For example, it may not be able to detect the heat patterns of a patient with low temperature who may need assistance, Ms Lee explained.
She hopes that the technology is installed in every ward in the hospital, as she finds it a valuable tool for her day-to-day work.
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