Behind Singapore’s widespread adoption of AI in public health

Singapore is one of the largest users of AI in healthcare in the world, especially in areas such as disease detection and improving patient outcomes.

What drives this important achievement is effective collaboration among healthcare stakeholders, especially between providers and the Ministry of Health, whose vision of an interconnected healthcare system, based on digital technologies, is being implemented by the national health technology agency, Synapxe.

Andy Ta, Director of Data Analytics and AI (DNA) and Chief Data Officer at Synapxe, spoke with Healthcare IT news on how the organization is pursuing AI integrations in public health settings, highlighting two new AI projects: AI Medical Imaging Platform for Singapore’s Public Healthcare (AimSG) and Assisted Chronic Disease Explanation using AI (ACE-AI).

He shared what drives them to innovate further, especially in AI, and its immediate yet careful applications to solve healthcare issues of national importance.

Ta also spoke about health technology trends in the new year, sharing where he thinks generative AI, whose popularity skyrocketed last year, will bring the most benefit to healthcare.

Q. In addition to its 15th anniversary celebration, Synapxe announced two major AI initiatives/projects: ACE-AI and AimSG. Where are you now with both projects?

A. At Synapxe, we are guided by the Health IT Master Plan (HITMAP) to establish common data analytics capabilities to unlock insights about our population to enable early disease detection and more personalized patient care. As a national health technology agency, Synapxe has launched several AI-driven initiatives that aim to create intelligent technology solutions that help improve the lives of millions of people every day, everywhere. This year we are excited to roll out two such initiatives, which were announced during our 15th anniversary celebration.

GoalSG was launched as a new platform to enable public healthcare institutions to seamlessly integrate validated and credible AI imaging solutions into their existing clinical workflow, improving diagnostic capabilities and increasing efficiency. This vendor-neutral platform, developed by Synapxe, SingHealth and NTT Data, can support imaging AI models from different sources for different imaging modalities, which was not possible before. AI imaging models automate the analysis of medical images with speed and accuracy, enabling more efficient triage of patients with urgent care needs and helping radiologists generate radiology reports more efficiently and accurately. This not only helps improve the quality of doctors’ diagnoses, but can also reduce unnecessary tests and procedures. This platform was recently piloted at Changi General Hospital (CGH) and Singapore General Hospital, and we are monitoring its progress before potentially deploying it at other healthcare facilities.

As part of Healthier SG and to support GPs in discovering personalized insights about their patients’ health, Synapxe developed the country’s first Assisted Chronic Disease Explanation using AI (ACE-AI). ACE-AI aims to be a digital assistant for doctors in managing chronic diseases for patients. It uses neural networks and explainable AI techniques to identify risk factors and automate risk calculations to detect early signs and risks of chronic diseases over the next three years. This helps doctors manage chronic diseases of their patients. ACE-AI is currently being tested with selected 20 general practitioners.

Q: How is Synapxe working as a “connector” with stakeholders to drive AI adoption amid security/privacy concerns, skills shortages/digital literacy, and other issues? What is your strategy to promote AI adoption in public healthcare?

A. Synapxe connects people and systems to enable a healthier Singapore. We collaborate and support MOH in delivering national healthcare policies and outcomes, including the IT Master Plan and Public Healthcare Architecture, enabling technological innovation and the development of healthcare professionals.

AI is rapidly being adopted across industries, especially healthcare. It is crucial to consider an institution’s burden, capacity and users (physicians, healthcare providers and patients) when implementing AI. While still an emerging technology, AI has the potential to automate many tasks to improve efficiency and cost savings for businesses. As we are still on the cusp of developing and understanding its full capabilities, this also poses a challenge of AI talent shortage. At Synapxe, we bridge the knowledge gap by mobilizing talent through collaboration with industry partners, and by actively involving our employees and potential employees in our digitalization journey by enabling them to try out new technologies. These are in line with our vision and objective to adopt various technologies, including AI.

Q. How does innovation factor into your current AI projects and others in the pipeline?

A. Product innovations at Synapxe are guided by our long-term national healthcare strategy and national headwinds.

Adversity can be a powerful catalyst for innovation and creative thinking. A great example to share was the launch of the Community-acquired pneumonia and COVID-19 artificial intelligence predictive engine (CAPE), which was co-developed with the team at CGH during the COVID-19 pandemic. CAPE is an AI tool that can predict the severity of pneumonia in patients, including COVID-19 patients, based on a chest X-ray. This is one of the ongoing projects that will allow doctors to quickly predict the expected severity of pneumonia in a patient and provide healthcare interventions efficiently. Today, pneumonia is one of the leading causes of death worldwide and the leading cause of worsening of COVID-19.

Another ongoing project being implemented is the Active surveillance system for adverse reactions to medicines and vaccines (ASAR) by Synapxe and the Health Sciences Authority of Singapore (HSA). In efforts to improve HSA’s adverse event monitoring program, ASAR was launched as the first nationwide application to analyze structured healthcare data and unstructured clinical notes from all public acute hospitals to detect and validate drug safety signals to improve public health in to protect Singapore.

Q. What is the status of AI adoption in Singapore’s healthcare landscape? What has changed in the way it is received/implemented in clinics/hospitals?

A. AI is increasingly being used across the healthcare continuum – from administration to clinical decision support, to increase system efficiency and improve patient outcomes. Given its ability to streamline processes and increase efficiency, we expect this to become increasingly common in the coming years as technology advances.

Singapore is known to have one of the highest AI adoption rates in global markets, with the technology being integrated locally into many different medical practices to improve disease detection and patient outcomes. Although it has many applications, the adoption of AI in healthcare has been described as a game changer, particularly its ability to detect abnormalities in medical imaging such as chest X-rays, mammograms and CT scans of the brain.

At Synapxe, we are already integrating AI into a number of different initiatives, including AimSG and ACE.AI, as mentioned above, with many more in the pipeline.

Despite the positive evolution in attitudes towards AI technology, there are still some concerns, including the medical and legal implications of taking over certain roles traditionally performed by humans, as well as other risks and ethical concerns associated with the implementation of AI.

Q. What AI healthcare trends do you see continuing in the new year and beyond? What about the new trends that can be expected in 2024?

A. In 2024, we will see greater adoption of technology, especially in the field of AI. Combined with predictive analytics, we have begun to enable early detection of health risks and trend analysis to maintain the health and well-being of the population.

Companies across a wide range of industries are also looking at improved efficiency and cost savings through AI. Currently, many users and companies generate the first set of results, but generative AI has the potential to automate many tasks and be a helpful concierge to a human problem, for example personalizing medications for individuals based on their genetic makeup.