An interview with San Zaw, Vice President Solution Consulting APJ of TIBCO’s solution consulting business in Asia on artificial intelligence in healthcare.
Over the past few years, Artificial Intelligence (AI) and related technologies have grown increasingly sophisticated and are therefore adopted by most businesses to predict outcomes and solve complex data-driven challenges. In the field of heathcare, these technologies also have the potential to transform patient care by improving diagnostic efficiency and minimising medical errors by extracting valuable insights from data and quickly enabling healthcare professionals and patients alike to make high-stakes decisions.
Here, we speak to Mr San Zaw, Vice President Solution Consulting APJ of TIBCO’s solution consulting business in Asia, on how AI is benefitting the healthcare landscape, the challenges of applying AI in these settings, and how TIBCO is collaborating to expand these technologies across Asia.
What is the current situation in hospitals in Singapore and how will AI enable these organisations to be more effective and efficient?
The COVID-19 pandemic has proven to be an important test-bed for AI,1 with applications harnessing the technology’s predictive capabilities to visualise heatmaps and models that forecast which communities are most at-risk of the virus.
In Singapore, AI and genomics2 helped the Ministry of Health better understand the spread of infections by identifying symptoms of respiratory conditions, picking out key phrases from staff-prepared notes at emergency clinics.
These use cases highlight AI’s increasingly influential role in healthcare as medical practitioners strive for insights to make life-saving decisions. AI can ease the burden on health workers by identifying gaps and freeing up resources for huge medical datasets to be analysed effectively.
As a result, not only does healthcare provision become smoother, it also ensures lowered costs.
This is of strategic importance to the Singaporean government, with Health Minister Ong Ye Kung noting that national healthcare expenditure has more than doubled from S$10 billion in 2010 to S$21 billion in 2018 and is expected to triple to S$59 billion by 2030. AI can play a significant role in addressing this exponential rise by driving cost-saving efficiencies through increased diagnostic accuracy and earlier detection, boosting the speed of life-saving decision making and the reduction of repetitive day to day tasks.
What are some of the common challenges faced by healthcare organisations to maximise the benefits of AI?
With the increasing adoption of digital technologies, the role of AI in healthcare is ever-evolving, which requires professionals and service providers to rely on data to inform high-stakes decision making.
However, many healthcare providers are accessing varied data sets, making it a challenge to extract valuable insights from, thus preventing the effective use of said information. For instance, with data silos in diagnostic testing, tests could be delayed and risk lives.
Poor data quality and lack of efficient data analytics processes result in underutilisation of data and lack of interoperability, which hinders organisations’ ability to extract the most value from assets and technology investments. For instance, with data silos in diagnostic testing, results may not reach the right medical professional on time, putting lives at risk. This underscores the need for agility to be prioritised in the modernisation of data platforms.
Just as data is the lifeblood of business, so it is for ensuring the full power of AI is harnessed today.
As the demands of AI and its abilities continuously grow, it is imperative that clinical AI models be trained with adequate “noise”-free data.
Besides ensuring the quality of data and its accessibility across the organisation, it is also vital that healthcare providers are equipped to ensure best practices when handling sensitive information as it is crucial for maintaining public trust.
What are some best practices in data governance and security organisations need to be mindful of?
There is no sidestepping the fact that data governance is a priority for many organisations due to the pressures of regulatory compliance, operational improvements, report quality, and customer experience. Fortunately, healthcare organisations have been prioritising data governance as part of their initiatives.
The challenge at hand is on data trust and data sharing to achieve better outcomes for patient care quality across a given healthcare remit (e.g., national level). Particular attention needs to be given to the governance of master data (shared data), reference data (codes, hierarchies, classifications, etc.) and metadata (data context and lineage).
It is critical for data governance to be an organisation-wide initiative and not something confined to a particular department or function. Having a continuous data governance process that ties in data quality, classification, tagging, mastering, and distribution in a collaborative approach – involving both data professionals and healthcare stakeholders/practitioners – is critical for success.
How has the partnership between TIBCO and NUHS helped patients and healthcare professionals?
Through a partnership with TIBCO, Singapore’s National University Health System (NUHS) deployed multiple AI and automation tools as microservices on its ENDEAVOUR AI platform. These AI tools incorporate multi-domain patient information, such as demographics, text, images, laboratory data, and medications prescribed to provide a synthesis of a patient’s condition. This translates into significant cost savings, from a patient’s care at admission, to predicting a patient’s length of stay, therefore optimising bed occupancy and other medical resources.
Employing TIBCO technology, the ENDEAVOUR AI platform from NUHS is able to support the integration of real-time medical data from Electronic Medical Record (EMR) systems. This integrates multiple complex AI tools to provide aggregated predictions and visualisation of insights, enhancing patient care and services. In collaboration with NUHS, TIBCO technology enables the unique platform to stream data in real-time, feeding live data into AI models that produce actionable insights.
The AI tool can also instantly identify risk factors for breast cancer, offering early detection and referrals for mammograms.
Moving forward, how will these technologies reach other key parts of Asia, especially developing countries? Are there any organisations that TIBCO is looking to collaborate with to improve patient outcomes within this region?
By 2027, the Asia Pacific’s healthcare AI market is predicted3 to hit nearly US$18 billion. In fact, AI is already playing a role in the enhanced resource control1 of healthcare workers and facilities, thereby increasing patient care capacity.
However, there is still a wealth of untapped potential to be leveraged from AI, ranging from more compelling visual analytics and reporting capabilities, to freeing software engineers from going through the whole software development cycle when creating new dashboards for customers, which significantly shortens turnaround times.
TIBCO is also working with healthcare organisations in the region, such as Care Logistics. Our collaboration improved real-time visibility for the company via configurable, dynamic, and semi-public dashboards, fuelling data-driven insights with ease and security. With TIBCO’s added functionality, Care Logistics developers were empowered to streamline display creation without having to build views from scratch. This enormous advantage delivered customisable, easy-to-maintain analytics dashboards much faster than before. TIBCO is committed to empowering health systems throughout the region as they strive to provide fast, secure, dynamic and more informed value-based care.
- Poojari, A. (2020, July 29). 5 ways AI is helping in the COVID-19 fight. Infocomm Media Development Authority. Retrieved from https://www.imda.gov.sg/news-and-events/impact-news/2020/07/5-ways-AI-is-helping-in-the-COVID-19-fight
- Nolan, S. (2021, December 7). How AI and genomics boosted Singapore’s COVID-19 response. GovInsider. Retrieved from https://govinsider.asia/insights/how-ai-and-genomics-boosted-singapores-covid-19-response-sutowo-wong/
- Asia Pacific Artificial Intelligence in healthcare market forecast to 2027 - covid-19 impact and regional analysis by component, application, end user. Research and Markets - The World’s Largest Market Research Store. (n.d.). Retrieved from https://www.researchandmarkets.com/reports/5316788/asia-pacific-artificial-intelligence-in
About the Interviewee
San Zaw heads TIBCO’s solution consulting business in Asia. San is a practitioner in Contextual Mobility and Digital Services, and works with Asia’s leading Financial Services Institutions and Communications Service Providers on game-changing solutions and delivering differentiated customer experiences.
San brings along more than 20 years of experience in the field of InfoComm Technology and built a track record in solving complex business challenges for enterprises ranging from Transportation & Logistics, Healthcare, Gaming, to Defense and Statutory bodies.