Clinical Decision Support for Primary Care

SIMFONI is developing AI-enabled clinical decision support tools to assist clinicians in delivering timely, personalised, and evidence-based care for cardiometabolic conditions - diabetes, hypertension, and hyperlipidaemia - which together represent one of the largest chronic disease burdens in Singapore’s primary care system.

These tools use a layered approach that combines proven clinical methods with advanced AI. Established risk prediction models identify patients who may need early intervention. Singapore’s national clinical guidelines (ACE Clinical Guidelines) are built directly into the system, providing a rules-based foundation for safe recommendations. Foundation models then reason across the full picture - patient history, current presentation, and clinical context - to surface additional care considerations that a busy clinician might otherwise need to look up separately. Each layer reinforces the others: the AI does not operate in isolation, but builds on top of guidelines and validated risk models.

In primary care, our work focuses on the most common chronic conditions seen in Singapore, supporting care delivery across polyclinics and private general practitioner settings in alignment with Healthier SG. All recommendations are grounded in national guidelines and presented as decision support - the clinician always remains in control.