SGH Annual Scientific Meeting: Smart Data, Shared Purpose, Seamless Care

Singapore, 17 April 2026 – As healthcare systems embrace and harness the power of big data and digital innovation now more than ever, it becomes more and more crucial that digital systems are both efficient and deeply humane. 

This edition of Singapore General Hospital’s (SGH) Annual Scientific Meeting (ASM), held over two days on 17 and 18 April 2026, tackles just this issue. Themed “Smart Data, Shared Purpose, Seamless Care”, it reflects the Hospital’s collective vision for the future of healthcare, balancing between technology and teamwork, and ensuring that every innovation ultimately serves to improve patient outcomes, experience, and value in care. 

The Guest-of-Honour at the event was Tan Kiat How, Senior Minister of State, Ministry of Digital Development and Information & Ministry of Health, who delivered the opening speech on Friday, 17 April 2026, at 10.00am at The Ngee Ann Kongsi Auditorium, Academia, SGH Campus. He also officiated the launch of the SingHealth Duke-NUS Allergic Diseases Centre. 

Associate Professor Too Chow Wei, Senior Consultant, Department of Vascular and Interventional Radiology, SGH, and ASM Organising Chairperson said, “This Meeting celebrates the collaborative spirit that drives today’s healthcare innovation. It is encouraging to see how disciplines and institutions unite to reimagine what is possible for patient care. The most meaningful breakthroughs emerge when we fuse diverse expertise with shared purpose, and we’re excited to see the changes and transformations in healthcare delivery for patients.”

SGH Annual Scientific Meeting 

The SGH ASM also attracted over 160 abstract submissions from SGH and across the Campus in 15 award categories. Some noteworthy abstracts across various domains areas such as medical, nursing, diagnostics and allied health include: 

1. Prescription automation frees up nursing time for peritoneal dialysis patients 
SGH nurses created an AI-enabled solution by feeding validated clinical data and designing specialised workflows that allowed an institutional PAIR chatbot to automate peritoneal dialysis prescription processing. The nursing-led AI initiative reduced processing time by 75% per patient, saving approximately 156 nursing hours annually. This freed up nursing capacity for direct patient care and while reducing transcription errors and enhancing patient safety. 

2. Smart monitoring system for patients with axial spondyloarthritis
Axial spondyloarthritis (axSpA) is a type of inflammatory arthritis that requires frequent monitoring for flare-ups and medication side effects. A team from SGH Rheumatology & Immunology created an automated system enabled by robotic process automation (RPA) to monitor axSpA patients remotely using validated patient reported outcome measures (PROMS) and lab results to determine which patients need follow-up appointments. The algorithm achieved 100% accuracy in sorting patients into appropriate care categories and may reduce clinic visits and wait times for patients. 

3. Predicting the risk of diabetic foot with corneal nerve images
Patients with diabetes are at risk of developing diabetic foot and eye complications. Researchers from Singapore Eye Research Institute developed an AI model that can predict the risk of developing diabetic foot just by looking at images of corneal nerves, which are finer and more sensitive than foot nerves. When combined with blood sugar levels and kidney function markers from blood test results, the model accuracy was about 94% accuracy, offering a new screening approach for diabetic complications. 

4. Making therapeutic drug monitoring more sustainable with waste plasma
SGH researchers developed a method to recycle leftover blood plasma from routine blood tests for use in antibiotic therapeutic drug monitoring (TDM), which ensures patients receive optimal medication doses while they undergo treatment. Instead of using expensive commercial plasma, the team repurposed discarded plasma by removing residual drugs stemming from 22 different medications routinely tested in specialist consultation. This resulted in producing “in-house carbon-stripped plasma” that performed just as accurately as commercial plasma for four commonly used antibiotics and can potentially save an estimated S$50,000 and reduce CO2 emissions by 324kg annually. 

5. X-Ray@Anywhere 
A team from SGH evaluated a portable X-ray machine for use in future community imaging. The portable system can potentially reduce the need for conventional department-based extremities imaging (e.g. hand, wrist, foot, ankle) imaging by nearly 70%, while achieving image quality comparable to standard hospital systems for chest, spine, and abdominal examination. In addition, the device enabled an overall shorter procedure time, improving workflow efficiency. Overall, the findings support the feasibility of future community-based imaging models, as this technology could reduce hospital congestion while enabling flexible care models beyond hospital walls.