PreSAGE: A Smart Bed-Exit Prediction and Prevention System based on Thermal Sensing
Care Process & Redesign
Technology
HIMSS-Elsevier Digital Healthcare Awards
National Healthcare Group
31 December 2019
To study the feasibility of using thermal imaging for automated fall prediction and prevention for high fall-risk patients. PreSAGE successfully demonstrated feasibility, safety, and accuracy for fall prevention using AI and thermal imaging.
Year Submitted: 2019
Published Date: 31 December 2019
Tags: Care Process ＆ Redesign, Technology, Quality Improvement, Design Thinking, Value Based Care, Safe Care, Risk Management, Preventive Approach, Digital Health, Sensors, Data Management, Data Analytics, Digitalisation, Automation, Machine Learning, Artificial Intelligence
About this Content
Aims
To study the feasibility of using thermal imaging for automated fall prediction and prevention for high fall-risk patients.
Background
Falls often cause major injuries, increasing hospital costs and length of stay. 65% of inpatient falls at TTSH occur at bedside, and 50% are unwitnessed, reducing opportunities for prevention.
Methods
Deployed thermal imaging in single-bedded rooms for 13 months. Trained AI models to identify bed-exit scenarios and patient movements. Integrated alarms and a front-end interface for validation. Conducted a three-phase observational study with 80 patients.
Results
System achieved 99.7% sensitivity and 100% specificity. The only miss occurred due to surveillance disarming. Thermal imaging effectively predicted and prevented bed-exits.
Conclusion
PreSAGE successfully demonstrated feasibility, safety, and accuracy for fall prevention using AI and thermal imaging.
Lessons Learnt
Stakeholder engagement, clear timelines, and IT project management are critical for digital projects. Human-centric design ensures alignment with clinical needs.
Additional Information
Winner of the Asia Pacific HIMSS-Elsevier Digital Healthcare Award 2019.
Keywords
Care Redesign, Automation, IT & Robotics, Machine Learning, Artificial Intelligence, Fall Prevention, Thermal Sensing, Smart Bed, Nursing
Innovators' Details
Innovators' Details
Healthcare Cluster(s) | National Healthcare Group |
Organization(s) Involved | Tan Tock Seng Hospital |
Platform(s) | HIMSS-Elsevier Digital Healthcare Awards |
Healthcare Professional Group(s) | Allied Health, Healthcare Administration, Nursing |
Applicable Specialty or Discipline | Geriatric Medicine |
Project Lead(s) | Tan Tzuu Ling (Clinical PI), Shen Nansheng (Technical PI) |
Project Member(s) | Julien Tan Cheun Woei |
Connect with this contributor!
Leong Hui Ling - hui_ling_leong@ttsh.com.sg
Wendy -
Project Attachment
351_TTSH_HIMSS_2019_PreSAGE_A_Smart_Bed_Exit_Prediction_and_Prevention_System_combine.pdf