Artificial intelligence (AI) has become a ubiquitous buzzword over the past few years, disrupting industries and sparking innovation across sectors. The healthcare sector is certainly no exception to the AI disruption.
Although AI-powered tools are already transforming areas like diagnostics and treatment planning, its full potential has yet to be unlocked. Many also opined that AI has significant potential for future growth and evolution.
In the healthcare value chain—from pharmaceuticals and medical devices to service providers and insurance—the most profound effect of AI is evident in healthcare service delivery, particularly in clinical workflow optimisation and diagnostics, according to Vertex Growth Executive Director Nikodemus Jaya.
“The global shortage of healthcare professionals, further burdened by administrative and compliance tasks, creates a significant challenge in delivering quality care,” he said. “AI, in both is non-generative and generative forms, offers immense potential to unlock greater efficiency within the healthcare system. This translates to increased accessibility and affordability of high-quality care for patients.”
As mentioned in Vertex Holdings’ AI report “Transforming Healthcare: The role of Artificial Intelligence”, the Singapore-based VC firm expects there to be high rates of development and adoption in the sub-sectors of clinical workflow optimization and decision support, patient data analysis as well as operations management.
In an interview with TNGlobal, Vertex Growth Executive Director Nikodemus also discussed how AI will have an impact on the healthcare sector.
He shared his insights on what are the areas AI would transform the healthcare sector the most, among other issues.
He also shared his views on what kind of training healthcare workers would need to fully utilize the support from AI.
Vertex Growth Fund is dedicated to partnering with exceptional entrepreneurs and promising companies on the cusp of growth. It provides the expansion capital to realize the companies’ vision of creating a category champion that is enduring and transformational.
Vertex Growth is part of Vertex’s global network of venture capital funds comprised of affiliates in China, Israel, Southeast Asia and India, and the US.
Below are the edited excerpts of the interview:
In which way would AI transform the healthcare sector the most?
AI’s most significant impact in healthcare is its ability to process vast amounts of data, enhancing insights that can be applied across the business value chain to improve efficiency in cost-related functions and effectiveness in revenue-related functions.
In the healthcare value chain—from pharmaceuticals and medical devices to service providers and insurance—the most profound effect of AI is evident in healthcare service delivery, particularly in clinical workflow optimization and diagnostics.
The global shortage of healthcare professionals, further burdened by administrative and compliance tasks, creates a significant challenge in delivering quality care. AI, in both is non-generative and generative forms, offers immense potential to unlock greater efficiency within the healthcare system. This translates to increased accessibility and affordability of high-quality care for patients.
One example of this impact is clinical decision support systems powered by AI. These systems equip healthcare professionals with readily available patient data and preliminary insights, enabling them to make faster and more informed decisions.
For example, platforms like Navina, a portfolio company under Vertex’s family of funds, leverages AI to aggregate and analyze fragmented patient date from electronic health records (EHRs) and other sources to produce actionable patient portraits for faster and better treatment outcomes. Similarly, Nucleai, one of Vertex’s portfolio companies, uses AI-powered image analysis applications to assist pathologists in identifying optimal treatment plans for patients.
By alleviating administrative burdens and providing valuable insights, AI empowers healthcare professionals to focus on delivering personalized and effective care. This paves the way for a future where high-quality healthcare becomes more accessible and affordable for everyone.
For Asia Pacific, is there any particular segment that is more popular?
In the Asia Pacific, we find the focus remains on improving healthcare service accessibility. Technology, particularly mobile, is being used innovatively by companies like Speedoc, one of Vertex’s portfolio companies, to deliver health services remotely, offering consultations, chronic disease management, and even lab diagnostics. These services are primarily powered by software solutions, leveraging teleconferencing technologies and robust digital payment infrastructure.
However, a shift towards integrating AI into diagnostic tools is gaining traction, particularly in countries with more advanced digital healthcare systems. This signals a strategic move towards improving both efficiency and patient outcomes, suggesting a future where AI plays a more prominent role in shaping the region’s healthcare landscape.
How is the adoption of AI in the healthcare sector in the Asia Pacific region?
The application of AI in the healthcare sector within Asia Pacific is still at its early stages but shows promise. For example, the use of generative AI for pre-consultation triage via chatbots indicates a growing interest in leveraging AI to streamline patient care and optimise healthcare workflows, even though full-scale adoption is gradual.
In your opinion, which subsector can or should further adopt AI technology?
We see enormous potential in the use of AI in countries with limited healthcare professionals, particularly in areas like public health education and service delivery. These countries, often lacking primary care or health information access, can benefit from GenAI’s ability to provide user-friendly yet confidential access to reliable health information that can be further acted upon by care-seekers.
Countries that adopt a public healthcare insurance scheme also see opportunities for AI integration, particularly in insurance claim processing. AI can be used to analyse data, offering insights into helping policymakers better structure the reimbursement system. AI can also be used to sort and prioritise claims, and further accelerate the overall process.
How do healthcare professionals adapt to new AI technologies, and what training is necessary?
There are a good number of AI-powered solutions now available to healthcare providers, especially around clinical workflow optimisation and diagnostic support as mentioned above.
The healthcare industry is usually more cautious in adopting new technology in clinical workflow, and understandably so, given the massive work burden presently in current healthcare systems. Any mishaps in the system would have significant consequences.
AI companies need to be aware of the requirements and standards of the healthcare industry when it comes to setting up the IT system and familiarise themselves with the healthcare tech ecosystem, which often involves specialized system integrators.
The onus is on technology companies to develop solutions that are relatively easy to implement, with intuitive user interface and seamlessly integrates into the current workflow.
Regular training equips healthcare professionals to adapt to new technologies. However, successful integration hinges on collaboration between technology providers, industry practitioners, and system integrators to ensure seamless workflow integration. We have seen successes on this front in mature markets such in the U.S. where companies like Datos Health, a Vertex portfolio company, work closely with healthcare providers to improve operation
efficiencies and enable remote treatment.
Are there concerns about data privacy and security when implementing AI in healthcare systems?
Data privacy and security are key concerns in all technology applications, but even more so in this situation given that personal healthcare data is concerned. Most countries have enacted health data protection regulation, requiring stringent control of handling and processing of such data. It is a given that any AI solution that seeks to use these datasets will need to comply with these regulations.
There are regulatory frameworks in place (e.g. HIPAA compliance standard) which provide compliance frameworks, coupled with cybersecurity standards such as the SOC2 certification.
That being said, there are areas for AI and GenAI applications such as scheduling and public health education that present fewer challenges due to their limited need for sensitive data access.
Can you discuss the potential societal implications of widespread AI adoption in healthcare?
AI has the potential to democratize access to healthcare, addressing both information and service disparities. However, it is not a panacea for systemic healthcare issues, much still needs to be done to improve healthcare service accessibility, both in terms of physical availability and affordability. Efforts are needed to incentivize and facilitate training to nurture talents to serve in the healthcare sector.
In terms of affordability – Within the Asia Pacific region, there are countries with lower income per capita. How is the cost of AI adoption? Is it affordable?
Indeed, we note that in the Asia Pacific region, there is a heavier focus on investment infrastructure and procurement of medical instruments and devices; with AI and software solutions not considered as essential items.
This reluctance to invest in AI and software solutions over traditional healthcare infrastructure underscores the need for customized, cost-effective AI applications that demonstrate tangible benefits. We find high potential for the implementation of AI in areas such as the enhancement of system-level efficiency and optimization of public healthcare spending.
*Vertex Growth views Artificial Intelligence (AI) technology as system(s) that involves machine learning process – i.e. algorithm that can detect patterns and learn to make predictions (and thus recommendations) by processing data rather than by receiving instructions.
As such solutions that primarily relies on ‘hard-coding’ programming – generally classified under software solution, should not be confused in AI.*
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