Singapore is one of the major adopters of AI in healthcare in the world, particularly in areas such as disease detection and improving patient outcomes.
What drives this significant feat is an effective collaboration among healthcare stakeholders, especially between providers and the Ministry of Health, whose vision of an interconnected health system predicated by digital technologies is carried out by its 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 organisation pursues AI integrations across public health facilities, spotlighting 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 further innovate, especially in AI, and its immediate yet careful applications to solve healthcare issues of national concern.
Ta also spoke of health technology trends in the new year, and shared where he thinks generative AI, which popularity boomed last year, will provide the most benefit to healthcare.
Q. Alongside 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 set up common data analytics capabilities to unlock insights about our population to enable early detection of diseases and more personalised patient care. As the national health tech agency, Synapxe has rolled out various AI-driven initiatives that aim to create intelligent technological solutions that help improve the lives of millions every day, everywhere. This year, we are excited to be rolling out two such initiatives, which were announced at our 15th-anniversary celebration.
AimSG was launched as a new platform to empower public healthcare institutions to integrate validated and credible AI imaging solutions into their existing clinical workflow seamlessly, enhancing 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 various imaging modalities which previously was not possible. AI imaging models automate the analysis of medical images with speed and accuracy, enabling more efficient triaging of patients with urgent care needs, and helping radiologists to generate radiology reports more efficiently and with accuracy. This not only helps to improve the quality of clinician diagnoses, but it 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 potential implementation at other healthcare institutions.
As part of Healthier SG and to support general practitioners (GPs) in discovering personalised insights on their patients’ health, Synapxe developed the nation’s first Assisted Chronic Disease Explanation using AI (ACE-AI). ACE-AI aims to be a digital assistant to doctors in chronic disease management for patients. It leverages 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 assists doctors with chronic disease management of their patients. ACE-AI is currently piloted at select 20 GPs.
Q. As a “connector,” how is Synapxe working with stakeholders to push AI adoption amid concerns over safety/privacy, lack of skills/digital literacy, and other issues? What is your strategy for promoting AI adoption in public healthcare?
A. Synapxe connects people and systems to power a healthier Singapore. We partner and support MOH in realising national healthcare policies and outcomes including the public healthcare IT masterplan and architecture, enabling technology innovation and the development of health tech professionals.
AI has been rapidly adopted across industries, especially in healthcare. It is critical to consider an institution’s load, capacity, and users – clinicians, healthcare providers, and patients – in the implementation of AI. Though still a nascent technology, AI has the potential to automate many tasks to improve efficiencies and cost savings for businesses. As we are still at the cusp of developing and understanding its full capabilities, it also presents a challenge of AI talent shortage. At Synapxe, we bridge the knowledge gap by mobilising talent through collaborations with industry partners, and actively engaging our employees and prospective hires on our digitalisation journey by empowering them to try out new technologies. These are in line with our vision and goal of adopting different technologies including AI.
Q. How does innovation play a part in your ongoing AI projects and others in the pipeline?
A. Product innovations at Synapxe are guided by our national long-term healthcare strategy and through national adversity.
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 developed with the team at CGH during the COVID-19 pandemic. CAPE is an AI-enabled tool that can predict the severity of pneumonia in patients, including COVID-19 patients, based on a chest X-ray image. This is one of the ongoing projects which allows clinicians to quickly predict a patient’s expected severity of pneumonia and efficiently provide care interventions. Today, pneumonia is one of the leading causes of death worldwide and the main cause of deterioration in COVID-19.
Another ongoing project 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 enhance the adverse event monitoring programme by HSA, ASAR was launched as the first nationwide application that analyses structured healthcare data and unstructured clinical notes from all public acute hospitals to detect and validate drug safety signals to protect public health in Singapore.
Q. What is the state of AI adoption in Singapore’s healthcare landscape? What has changed with the way it is being received/implemented across clinics/hospitals?
A. AI is increasingly being used throughout the healthcare continuum – from administration to clinical decision support, to increase system efficiency and improve patient outcomes. Given its ability to streamline processes and boost efficiencies, we expect it to become more commonplace in the years to come with the advancement of technology.
Singapore is known to have one of the highest AI adoption rates amongst markets globally with the technology being integrated into many different medical practices locally to improve disease detection and patient outcomes. While it has many applications, the adoption of AI in healthcare has been described as a game-changer, in particular 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 across a number of different initiatives, including AimSG and ACE.AI, as mentioned above, and many more in the pipeline.
Despite the positive evolution in attitudes towards AI technology, there are still some concerns which include medical and legal implications of AI taking over certain roles traditionally performed by humans, as well as other risks and ethical concerns that come with implementing AI.
Q. What trends in healthcare AI do you see continuing in the new year and the years to come? What about new trends to be expected in 2024?
A. In 2024, we will see greater adoption of technology especially in AI. Combined with predictive analytics, we have started enabling the early detection of health risks and trend analysis to preserve the health and wellbeing of the population.
Businesses across a diverse set of industries are also looking towards improved efficiencies and cost savings through AI. Currently, many users and businesses are generating the first iteration of outcomes, but generative AI has the potential to automate many tasks and be a helpful concierge to a human problem, for example, personalising medication for individuals based on their genetic makeup.
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