Singapore AI push targets clinician admin burden

Healthcare providers say automation must address fragmented workflows whilst preserving safety, clinician trust, and patient care.

Singapore healthcare providers are expanding artificial intelligence beyond digitisation as they seek to reduce administrative work without compromising clinical safety or patient experience.

Healthcare has adopted electronic records, portals, claims, and scheduling systems, but these systems have not always worked together, said Dr. Anindita Santosa, Co-Founder and CEO of AIGP Health. This left healthcare workers effectively connecting fragmented processes themselves.

Dr. Ling Zheng Jye, Chief Medical Information Officer at the National University Hospital (NUH) Singapore, said complex healthcare workflows also made automation harder to implement than in other industries.

NUH is now seeking to expand AI across its workforce. More than 47% of staff have been trained in tools including Copilot and Microsoft Power Automate, whilst about 2,100 employees used them in the previous month.

Regulation, meanwhile, is not necessarily the main constraint. Santosa said the Health Sciences Authority sandbox primarily covers AI functioning as a medical device rather than administrative automation.

“I don't think the sandbox is the bottleneck for most administrative automation,” she said, pointing instead to interoperability, procurement, workflow fit, clinician trust, and change management.

Ling said clear governance can enable adoption by giving healthcare workers and patients greater confidence whilst providers address cybersecurity, privacy and operational readiness.

AI could also reduce waiting times, although Santosa cautioned against applying a universal reduction target. Delays can occur throughout scheduling, registration, financing checks, investigations, pharmacy, referrals, and discharge.

Rather than simply making doctors work faster, automation could streamline processes surrounding clinicians. AI can support demand prediction, scheduling, triage, record summarisation, and documentation.

Ling said AI scribes and digital follow-ups are already changing workflows at NUH. The broader objective is to direct patients to appropriate care channels and allow providers to serve more patients effectively with the same workforce, potentially reducing queues as a consequence.