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Introducing the eagerly awaited launch of Asian Hospital & Healthcare Magazine Issue 64, 2024. Every issue of AHHM magazine stands as a robust reservoir of information and wisdom, brimming with original and pure content. Crafted by top minds in the hospital and healthcare industry, the magazine delivers timely business insights and features articles on the latest advancements in technology.
Asian Hospital & Healthcare Management offers comprehensive exploration and insightful analysis of industry dynamics and emerging trends in technologies, covering various fields such as medical science, diagnostics, and beyond authored by top experts.
In the cover story ‘Burning Down the Barriers to DataDriven Healthcare in Asia’ of Asian Hospital & Healthcare Management, Dr Russell Leftwich, Senior Clinical Advisor, InterSystems discusses the imperative need to move away from traditional healthcare paradigms due to demographic changes, technological progress, and growing healthcare demands. Leveraging data-driven models and cutting-edge technologies such as GenAI is imperative to address the complexities of modern healthcare delivery.
Some key highlights in this edition encompass articles delving into improving transition to nursing practice in the digital age, Artificial Intelligence Revolutionising in Asia Medical Industry, future medical technology trends alongside with expert interviews offering insights into the transforming cancer care: innovations, challenges, and future directions. Additionally, the impact of eHealth on
the healthcare landscape is examined. A panel of experts have graciously expressed valuable insights on emerging trends and transformative technologies in the healthcare sector. Their collective wisdom paints a vivid picture of the interconnected future-a future where healthcare innovation and human expertise converge to create a healthier, more connected world.
As you delve into the pages ahead, you'll discover thought-provoking articles, expert viewpoints, and concrete examples showcasing how technology and AI are reshaping healthcare. Join us on this captivating journey through the intricate world of healthcare technology, where the integration of innovative solutions and human understanding promises a healthier, more interconnected future.
This edition beckons you to venture beyond mere exploration of the latest developments in the healthcare sector. It prompts a deep dive into the broader considerations of an increasingly digitalized healthcare landscape. Furthermore, it challenges us to envision the future of health, where the virtual realm becomes an indispensable cornerstone.
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Medi Swetha Editor05 Perspectives on Improving Transition to Nursing Practise in the Digital Age
Leona Paula L. Macalinta, Director of Nursing, Cardinal Santos Medical Center
08 The Role RWE Plays in Helping Patient Groups and the Private Sector Accelerate Access to Treatment/ Services in Asia
Liu Chang, Founder and CEO, ASK Health Asia
Sharon Hsiao Fei Yuan, Professor and Director, Graduate Institute of Clinical Pharmacy
12 Operational Analytics for Healthcare Services
Gurrit Kaur Sethi, Founder, Mind My Mind
17 Breathing Easy
Early Detection & Treatment based on Comprehensive Asthma Education and Nebuliser Adoption in India
Tetsuya Yamada, Managing Director, OMRON Healthcare India
20 Early Detection of Asymptomatic Coronary Artery Disease in the Hospital Setting Using CT Imaging
Dr. Jeffrey J Fine MS, PhD, Executive Director, National Heart Health Program
23 Cerebral Small Vessel Disease Burden is Associated with Outcomes after Minimally Invasive Surgery of Acute Spontaneous Intracerebral Haemorrhage
Wendy C. Ziai, Department of Neurology, Anesthesiology and Critical Care Medicine, Johns Hopkins University
25 How CT Imaging Powered by AI and Technology Holds the Key to Improving Patient Care and Radiology Workforce Efficiencies in ASEAN
Chris Kim, Head of Imaging, Philips APAC
28 Future Medical Technology Trends
Probir Das, Group Executive Officer, Terumo Corporation 31 The Impact of New Technologies on Patient Outcomes and Healthcare Professionals' Stress Levels
Joana Santos Afonso, CEO & Founder, Careceiver
Chris Brucker, CEO & Founder, Nammu Lab SAS
35 Advantages of Telemedicine for and beyond the patient care
Jessica Masotino, Founder & CEO, JSMedtech
Artificial Intelligence Revolutionising in Asia
Industry
Joalin Lim, MS, PhDc,CCRP, CEO, Agape-Life Medtech & Healthcare Group
The Changing Regulatory Landscape for Artificial Intelligence in Healthcare
Derek Hill, CEO, Panoramic Digital Health
Healthcare at your Fingertips
The Future of Health is Virtual
Raymond Ng, CEO & Country Manager, Cigna Healthcare Singapore
Alex Boulton, Southeast Asia Head of Healthcare & Life Sciences Practice at Bain & Company
Transforming Cancer Care
Innovations, Challenges, and Future Pathways
Samara Mahindra, Founder and CEO of Carer
Emerging Trends and Transformative Technologies in the Healthcare Sector
Panalist 1: Tan Cher Heng, Executive Director
Panalist 2: Konrad Dobschuetz, National Director at NHS Innovation
Accelerator and Chief Enterprise Officer UCL Partners
Panalist 3: Mohammad Al-Ubaydli, CEO & Founder of Patients Know Best
Panalist 4: Sheena (Morjaria) Pirbhai, CEO & Founder, Stress Point Health
Beverly A Jensen
President/CEO
Women's Medicine Bowl, LLC
David A Shore
Adjunct Professor, Organisational Development Business School, University of Monterrey
Eiman Shafa Medical Director Spine Surgery Abbott Northwestern Hospital
Gabe Rijpma
Sr. Director Health & Social Services for Asia Microsoft
Gurrit K Sethi Founder, Miindmymiind
Imelda Leslie Vargas Regional Quality Assurance Director Zuellig Pharma
K Ganapathy Director Apollo Telemedicine Networking Foundation & Apollo Tele health Services
Luzviminda Nietes
Vice-President, Business Planning & Development, Metro Manila
Nicola Pastorello Data Analytics Manager Daisee
Piyanun Yenjit Founder & Managing Director APUK Co.,Ltd.
Pradeep Chowbey Chairman
Minimal Access, Metabolic and Bariatric Surgery Centre, Sir Ganga Ram Hospital
Pradeep Kumar Ray Honorary Professor and Founder WHO Collaborating Centre on eHealth UNSW
EDITOR
Swetha M
EDITORIAL TEAM
Debi Jones
Harry Callum
Supraja B R
ART DIRECTOR
M Abdul Hannan
PRODUCT MANAGER
Jeff Kenney
SENIOR PRODUCT ASSOCIATES
Ben Johnson
David Nelson
John Milton
Peter Thomas
BUSINESS EVENTS
Sussane Vincent
PRODUCT ASSOCIATE
Ethan Wade
CIRCULATION TEAM
Sam Smith
SUBSCRIPTIONS IN-CHARGE
Vijay Kumar Gaddam
HEAD-OPERATIONS
Sivala VNR
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The transition of nurses to clinical practice has been marked with challenges not only because of the demands of the healthcare environment but also of the healthcare innovations that are in place. Novice nurses need to be prepared and equipped with the knowledge and skillset to utilize such advanced technologies at the bedside.
Leona Paula L. Macalintal, Assistant Vice President and Director of Nursing, Cardinal Santos Medical CenterThe process of transition from student to professional nursing practice has been considered as complex and very challenging, much more after the pandemic. In the recent years, it has been highlighted that nurses experience a lot of challenges when transitioning to their professional roles because of the growing demand for “real-world” ready nursing professionals who can already adapt to the complexities of the healthcare environment. This transition to clinical practice still brings significant anxiety and feelings of instability among novice nurses because the realities of working in a healthcare setting are brought about by increasing responsibilities and accountability which they were not so much used to during their academic years as they were still under the supervision of their clinical instructors.
While there are already programs and initiatives that provide support to novice nurses and promote positive and safe transition into practice, matters become more complicated as healthcare innovations and digitalization set in. The rate of
clinical advancement and utilization of innovative technologies in various healthcare settings especially in the hospitals grew exponentially brought about by the impact of the pandemic; thus, adding to the demand of having professional nurses who are expected to learn, adapt and utilize these healthcare innovations at a fast pace when they provide care to patients at the bedside. However, these technologies and innovations were not yet fully embedded in academia, so much so that novice nurses were not prepared and equipped to utilize it in clinical nursing practice, adding to the stress and uncertainty of work expectations. This role conflict can lead to unsafe practices putting patients and nurses at risk. The growing concern over new nurses’ transition to practice in the digital era has also been documented globally in various research studies and forums and is said to influence nursing workforce retention.
Joseph, et al. (2022) highlighted in their study the extent of the nursing turnover problem among new graduate nurses which was supported by the report from the National Healthcare Retention and RN Staffing in the US indicating a high percentage of about 43% who left their initial jobs within the first to third year of employment. The multifaceted challenges associated with the transition include lack of orientation, an unwelcoming environment, heightened responsibilities, disproportionate workload and nowadays, inadequate support system to help them navigate through the advanced technologies and healthcare innovations which they are not familiar of. It is then imperative to identify measures and streamline efforts that will support novice nurses’ transition to clinical practice as well as their transition to adopting multiple innovations in the delivery of safe, quality care.
Effective transition to nursing practice is grounded on a firm and rich foundation
from the nursing students’ academic years. The role of nursing education is a significant factor in driving the acquisition of knowledge, skills and attitude that will build the confidence and competencies of novice nurses who will soon be entering clinical practice in various healthcare settings. Thus, academic institutions will also need to transform the way they prepare nursing students for professional roles in healthcare. Healthcare innovations and advanced modalities must be introduced at this stage and further elucidated in their related learning experiences so that graduate nurses will know what to expect when they are exposed to these kinds of innovations. Required skill set and competencies in using health information technology tools must also be developed during these formative years so that these future nurses will be more aware and equipped to utilize health technologies. There are various strategies that can be employed to enhance nursing education which are geared towards this positive transition.
With the recent growth of digitalization in healthcare, nursing and midwifery programs nowadays have started to integrate health informatics in their curricula. This strategy is said to enhance nursing and midwifery students’
digital health literacy and prepare them to use technological innovations to support their learning both in the academic and clinical environment. In embedding nursing informatics and healthcare innovation in the nursing curricula, nursing students also become more aware of the available technologies and innovations that are already being used in the care settings. They are also able to understand how these tools can make their work more efficient at the bedside while still upholding the value of caring and of patient safety.
Another strategy is to provide opportunities to nursing students for actual clinical experience that involves utilizing healthcare innovations. Certain practices in some countries involve academic institutions having partnerships with hospital and other healthcare settings to intensify related learning experiences and clinical immersions for their students; thus, they can actually observe, manipulate and navigate through these technologies and gradually develop digital competencies and skills. This approach prevents “shock” and anxiety for nursing students when they are already in transition to their professional roles in nursing because they are already exposed and familiar with the healthcare innovations that they encounter. They become more confident and engaged in further developing their prowess and later on, their expertise.
It is then imperative to streamline efforts that will support the nurses’ transition to clinical practice and their transition to adopting multiple innovations in the delivery of safe, quality care
Providing nursing informatics infrastructure and ICT tools is also a very significant aspect of improving nursing education that will prepare nurses for such transition. Academic institutions will also need to upgrade and equip their learning facilities with innovative and technologically advanced equipment and tools that can be used for training, simulation exercises and other cutting-edge methodologies which the nursing educators can employ when they teach nursing students. Having these educational resources and infrastructure cultivates a proactive approach to learning and developing the required
skills, competencies and attitude when utilizing various innovations in the care of patients.
The strategies to equip academic institutions in preparing nursing students for professional practice in this digital age is also tantamount to elevating the standards of teaching and learning in the hospital setting. Part of the collaborative approach to the transition of nurses for clinical practice is also developing a robust in-service training program and orientation for nurses in the hospitals. As novice nurses enter hospital practice, they expect thorough orientation and discussion of their roles and responsibilities, opportunities for learning and patient care expectations. However, teaching and learning in the hospital setting must also be a transition to collaborative, outcome-based and simulation-driven approach so that nurses will not only be equipped with knowledge and skills required to utilize healthcare innovations but also have the capability and flexibility to troubleshoot problems, make clinically informed decisions and maximize the use of healthcare innovations towards efficiency and patient safety. Ideal scenarios as well as critically challenged scenarios must be integrated in the orientation programs and hospital training programs so that nurses will determine how to respond and understand the implications of these advanced tools and modalities in the work that they do at the bedside.
Hospitals will also need to invest on healthcare IT infrastructure, systems and applications, high-fidelity mannikins and even artificial intelligence and augmented realities. These will intensify training and education among their doctors, nurses and allied healthcare providers who are not only geared towards developing competencies but also promoting critical thinking and evidence-based clinical decision making.
Implementing this kind of approach and methodology can provide a safe, learning environment for novice nurses and healthcare providers alike in the hospital settings leading to the transition to their respective roles in healthcare.
Successful transition to nursing practice in this complex, demanding healthcare environment and digital era also entails active involvement of nurses. What better way to aid them in this kind of transition but to determine how they can take part in the various aspects of healthcare innovation implementation. In the early phases of healthcare innovations and advancement, nurses are viewed as mainly end-users of technology. Recent studies though showed that there are other roles that nurses can employ to be more involved and proactive in the utilization of healthcare innovations. There are already nurses who take part in the development of innovations and advanced tools; nurses who take part in health technology assessment together with the multi-disciplinary team; and nurses who evaluate health innovations for patient outcomes.
As they become more involved in these roles and responsibilities and
develop expertise in this field, they are able to determine gaps in learning, strategies for effective implementation and utilization of these innovations and methods to enhance teaching and learning from a deeper and clinically driven perspective, not just from a theoretically driven outlook. The recommendations of such nurses involved in this field are now driving the change in streamlining initiatives that will enhance transition to clinical practice in the future as we anticipate more healthcare innovations and advancement in the years to come.
The transition to clinical nursing practice will continue to be challenged by people, process and the environment as healthcare innovations and clinical advancement continue to expand. Academic nursing institutions, hospitals and other healthcare settings must also be equipped and prepared to provide a learning environment that is not only centered on theory but also on evidence and various clinical situations that will challenge nurses in terms of their knowledge, skills, critical thinking and decision making which are very essential in their transition to professional roles in the clinical setting. Nurses will need to be more empowered to define and elevate their practice as experts in the field of healthcare innovations in this digital age as they can be effective change agents in transforming nursing education towards successful transition to practice.
Ms. Leona Paula L. Macalintal has been in the clinical nursing practice for 13 years. She is the Assistant Vice President and Director of Nursing in one of the tertiary hospitals in the Philippines and a part-time professor at the University of the Philippines where she is also taking her Doctor of Philosophy in Nursing. She was a recipient of Nursing Excellence award for Chief Nurse of the Year in the 2023 Hospital Management Asia awards.
To achieve health equity, the spotlight turns to realworld evidence (RWE) – a powerful tool that can bridge healthcare gaps, accelerate access to medical treatment or services, and shape important health policies that reflect underrepresented groups..
Liu Chang, Founder and CEO, ASK Health Asia and 2024 APPIS Council Member Sharon Hsiao Fei Yuan, Professor and Director, Graduate Institute of Clinical Pharmacy
As healthcare systems across Asia Pacific (APAC) start to gather more real-world evidence (RWE), this article takes a look at how patient groups and the wider healthcare community can come together through public and private partnerships and platforms such as the Alliance & Partnership for Patient Innovation &
Solutions (APPIS), to incorporate RWE into health policy decision-making and better reflect patients’ needs. Clinical data has been traditionally used to inform healthcare choices, but looking at RWE, in all its forms, has become increasingly important in understanding the more holistic impact on patients.
How is RWE being used in APAC? Healthcare systems across APAC are incredibly diverse. In recent years, we’ve seen markets with national healthcare systems increasingly incorporating RWE into practises, including postmarket pharmacovigilance, testing innovative treatments, insurance reimbursement, clinical usage, and healthcare policy decision-making.
Taiwan, for instance, has comprehensive national databases, including the Taiwan National Health Insurance Research Database (NHIRD), as well as electronic medical records, hospitals’ medical records, national registries, and investigatorinitiated studies. These sources of data contain comprehensive, large-
Other developed markets with robust and systemic healthcare systems, like South Korea, Singapore and Japan, also incorporate RWE to inform policies in areas of health financing, reimbursement policies, and healthcare innovation. Meanwhile, developing nations without nationwide healthcare databases may find it more difficult to generate RWE to inform healthcare policies, especially those that lack resources and infrastructure, but they are exploring other ways to generate RWE to expand the breadth and depth of their healthcare systems.
There is an opportunity for governments to leverage RWE to provide better care and coverage for their populations. However, due to the lack of resources, they often need to make trade-offs and issues may go unaddressed, especially those of underrepresented patient groups. This is where the healthcare community can step in to partner and fill the gap.
The role of RWE in shaping health policies for underrepresented groups
especially in drug trials. However, they are still a significant population whose treatments need to be supported by evidence like RWE.
When weighing the pros and cons between RWE and randomised clinical trials, RWE is often the preferred option, as it presents concrete data on benefits, costs, and potential impact –data that the government places heavy consideration on when it comes to policymaking. It is important to note that the data required for policymaking and clinical trials are quite different. The former requires descriptive data – a disease’s background information, economic burdens of the disease and treatments, the percentage of population affected, and so on; data used for clinical purposes require more data elements such as sophisticated study designs and treatment outcomes.
How can patient groups fill the gap by generating RWE?
scale records such as demographics, prescriptions, and treatments, all of which can be used as powerful sources to generate RWE and shape healthcare policies.
Early access zones can also expedite approvals for innovative medication. In China, pilot zones like Boao Lecheng have generated RWE to support the approval of new drugs from the United States and Europe for wider use in other areas of China, creating the opportunity to reduce or even avoid the need for further clinical trials. We’ve seen drugs to treat rare diseases being successfully approved in China using this pathway, and in other disease areas, RWE is being used in conjunction with clinical trials to obtain full approval.
Governments commonly adopt randomised control trials for their policy formation processes, but that methodology has shortcomings that RWE can easily address. Most notably, vulnerable and underrepresented populations are commonly excluded from the trials.
Researchers avoid paediatric trials due to the lack of funding, and rapid developments of the body make it difficult to compare children of different ages. There are also ethical concerns as children lack the capacity to understand the potential risks of trials. Pregnant women, on the other hand, are traditionally excluded from trials out of ethical considerations for potential damage to foetuses and an increased perception of risk. Additionally, the elderly – typically those over 80 – are excluded due to heightened adverse reactions,
It’s not just medical professionals who can generate RWE. Equipped with the right data collection processes, patient groups (with support from clinicians) can create small, clean subsets of the population that are representative of what is happening in the real world and provide immediate evidence to inform policymaking. It is particularly beneficial in the rare diseases space, where we often see more patient groups.
Patient groups are commonly underrepresented and under resourced. Through our interactions in China for example, we find that they are generally eager to find ways to systemically create change for those they are representing but are not equipped with the information or infrastructure to push for this change. Beyond policymaking, patient groups can play a role in collecting relevant data sets and first-hand patient reported outcomes that supplement their national health database and play a part in developing and refining their
national registries and data sets with more inclusive data.
Patient groups have great potential to generate their own RWE, yet in Asia, many communities are not aware of RWE and its use cases. Many organisations don’t have a deep understanding of the importance of collecting data, and patients are unwilling to share their data due to privacy issues. Thus, encouraging patients and peers to share data for RWE becomes the first barrier we must address.
In some instances, groups like ASK Health Asia encourage patient groups to prioritise privacy by separating personal information from RWE and keeping personal patient information within the patient groups – especially if data collection was not performed by authorised institutions such as hospitals. Another method to ensure privacy is through deleting private information after specified durations so personal information won’t be leveraged for purposes other than its original intention.
In addition, we find that smaller patient groups without professional staff are not always aware of ways to ensure patient confidentiality. This is where collaboration between private and public sectors comes into play, as patient groups would benefit from professional partnership opportunities with academics, analytical organisations, and others who are well-versed in patient confidentiality and can offer guidance and support. Another aspect we must take into account is the capability of patient groups, organisations, and third parties in collecting usable real-world data, and the government’s willingness to leverage the evidence for policy making.
Platforms like APPIS have spent the last few years providing educational sessions to guide patient organisations
Platforms like APPIS have spent the last few years providing educational sessions to guide patient organisations and other healthcare stakeholders in the collection and usage of RWE in health policy shaping.
and other healthcare stakeholders in the collection and usage of RWE in health policy shaping.
To ensure that data gathered is unbiased and is suitable to be taken into consideration by governments to inform decision making, patient groups will need to generate data without bias. A partnership with academics, clinicians, or other professionals will also be able to guide patient groups to develop rigorous protocols and methodologies and help them convert the data into suitable RWE.
We find that governments are willing to use RWE generated by patient groups, as long as the evidence contains usable data that are relevant to the population and collected using a proven methodology. Case in point: in China, the government has begun to pay more attention to RWE. More think tanks, organisations, and academic institutions are devoting their efforts into developing RWE tools, thus helping to raise awareness about it in the country. It is clear that public health institutions are keen
to understand real values, outcomes, and budgets for innovative use cases that can help them make informed decisions around shaping healthcare policies.
What’s next for RWE in Asia?
To support patient groups to develop suitable RWE that helps shape healthcare policies, we need to raise awareness about RWE to a wider audience, dispel misunderstandings, and create frameworks that can be used by groups with limited resources to further facilitate collaboration between public and private stakeholders.
For instance, ASK Health Asia is in the process of developing toolkits with industry partners to create systemic designs for patient groups to collect data for RWE. They are also extending outreach to hundreds of patient groups, including umbrella patient organisations such as the Chinese Organisation for Rare Disorders (CORD), to raise awareness about the possibilities of RWE and assist them in presenting their data to local governments. By providing methods to collect and analyse data by themselves, ASK Health Asia empowers them to reach their own objectives and generate RWE use cases.
The toolkits aim to be presented to as many patient groups as possible through platforms such as APPIS, which convenes healthcare stakeholders to prioritise action towards addressing patient access barriers. Its initiatives such as the APPIS Summit, which took place last month, and local APPISx sessions, which focus on country-level engagements, play an important role in facilitating the shaping of health policies around RWE through dialogue and knowledge-sharing year-round.
In India, for example, the opportunity of RWE lies in addressing the gaps in healthcare data – which is commonly paper-based and fragmented, making it difficult to track patient outcomes and identify trends. This was the topic at hand during a
2023 APPISx India session, which brought together patient organisation leaders and medical experts, including Dr Moni Abraham, Medical Director & CEO of Karkinos Healthcare and an RWE expert. The session illuminated how RWE can help provide a more comprehensive understanding of a treatment’s safety and effectiveness for patients in real-world settings, which in turn plays a crucial role in shaping healthcare policies and practises.
Another example of collaboration between public and private organisations for RWE development is the Taiwan Society for Pharmacoeconomic and Outcomes Research (TaSPOR). The organisation is currently in the process of establishing a task force in collaboration with the United Kingdom’s National Institute for Health and Care Excellence (NICE) International. The task force will incorporate NICE’s RWE Framework to develop a comprehensive RWE framework in Taiwan, which will establish terminologies that different stakeholders, from patient groups and hospitals to governments, can align on to better facilitate cross-sector collaboration.
To support the task force’s framework development process, TaSPOR invited Taiwan’s Centre of Drug Evaluation (CDE) to provide case studies of how the CDE has used RWE in their review process in policy shaping efforts. Once TaSPOR sets up a first draft of the framework, the organisation will invite different healthcare stakeholders, including patient groups, to provide feedback and advise on the adaptability of the framework in Taiwan – a true example of public-private partnership.
It’s a win-win situation
RWE developed by patient groups in Asia can inform and create new healthcare policies, especially in countries with less resources, to accelerate treatment to groups that are
underrepresented, including patients living with rare diseases. Empowering patient groups to take on the challenge of generating RWE and making this process better known and understood will create a positive influence for governments, providing them with a clearer picture of their population’s needs and encouraging them to incorporate RWE into more policy formation processes.
In addition, sharing these success storeys about patient groups that helped generate RWE that have influenced health policies can inspire and accelerate the development of robust patient organisations and communities, especially in developing countries. RWE generation models in more developed countries can even build global pioneer models for RWE in emerging economies and ultimately support systemic data infrastructures for RWE.
RWE can be developed through national databases, but data from patient groups have the possibility to act as another source of relevant data that can further improve on current RWE ecosystems, shining a spotlight on underrepresented patient groups with lesser-known diseases, and influencing impactful policy making decisions. Enabling partnerships between different stakeholders and regions is thus a significant component to the collective improvement of healthcare systems across APAC, which are in turn crucial in accelerating patients’ access to treatment, especially in countries where they need it most. By bringing healthcare communities together across patient groups, academia, and public policy, and more, we can work together to better use RWE to facilitate access for patients.
Dr. Liu Chang is the CEO and founder of ASK Health Asia, a catalyst for health systems transformation in Asia. Through in-depth research, consultancy, platform creation, solution co-creation and resource connection, the company works closely with leading industry leaders to provide innovative solutions to jointly promote new tangible health policies and capture growth opportunities within a global emerging economy.
Dr. Fei-Yuan Sharon Hsiao is a Professor and Director of the Graduate Institute of Clinical Pharmacy at National Taiwan University. She has a background in Pharmacoeconomics and serves as a board member on several committees, including the Drug Safety Committee at TFDA, Taiwan. She supports professional organizations, including the Taiwan Society for Pharmacoeconomics and Outcome Research and the Taiwan Association of Integrated Care.
Operational analytics is that effective balm that can enable any healthcare organisation to read the mood of the crowd (internal and external), and then with correct usage, enable a good experience for all stakeholders –patients, employees, and investors alike.
Gurrit Kaur Sethi, Healthcare Management ExpertRunning healthcare service business operations is akin to conducting an orchestra – ensuring that the myriad of talent, equipment, infra etc. comes together to deliver good patient care services – good medical outcomes with good hospitality services, food and a superb overall experience. And all this, with a smile and ensuring that the people undergoing the treatment also smile so we need to ensure that there is optimal pain management – for the patient, as well as for all the myriad of talent delivering these services, and of course for all the business stakeholders… I am taking the liberty of calling operational analytics the pain management system for healthcare operations – allowing for spewing up the right data for data driven decisions.
Analytics is a critical business tool for every business. The complexity may vary from industry to industry, also to the level of detail each business manager may require. Good analytics can propel the business in the right direction. While analytics typically has been around for
most industries for multiple decades now, the operational analytics in healthcare has generally lagged. Even today, while the bigger corporates do indulge amply in this, the smaller businesses are yet to take advantage of this, or even fully understand the need to use this at all.
Having worked with different types of institutions ranging from big corporate chains to smaller regional ones struggling to make a mark, kicking off green field operations, taken over brown field hospitals, kick starting new concepts or pulling along the laggers to perform, I can say with confidence that each time even a raw form of operational analytics applied went a very long way in streamlining operations and get more than just a few smiles on the faces of patients, employees and stakeholders alike. Especially as they realised how things became easier for them to initiate activities or take decisions that were well informed. These ‘well informed’ decisions enabled these leaders to empower their teams to work with clear objectives and with reason.
There is another reason that employees work happier and also leave a trail of patients and their families with a good experience when the leadership teams take advantage of operational analytics. Good application of operational analytics also allows for efficient operations. In the traditional sense we all read operational analytics as decent business metrics. Underlying these good metrics is an efficient flow of work which is enabled by the data driven decision making and alongside that building on process flows that remove the obstacles the teams face while delivering their tasks. When the work flows are easy for an employee, the task gets done quicker, with ease with better outcomes both quantitatively and qualitatively. But this does not just happen. We need to make it happen by constantly keeping an eye on the obstacles and not just overcoming them when these happen, but by redesigning the on-ground process flows to negate the obstacles. To
make this happen, of course, needs a lot of creativity, tenacity and motivation. But the results can be outstanding. Each storey you read about any business’s big stride or turnaround, has a storey which underlines these principles.
Of course, analytics for healthcare services can be complex, a little more complex than most industries. Being a manpower intensive industry where the outcome depends more on the manpower than on the machines and equipment, the skill of each hand (be they nurses, technicians, doctors or admin staff), especially on the shopfloor, makes a huge impact on the outcomes – clinical, overall experience, as well as financial. The operational analytics, to be effective, needs information of varied types within each of the clinical and non-clinical domains along with market trends and inputs, to come together coherently to allow for tactical decisions and actions which then adds up to business intelligence thrown up for inputs for strategic direction. In all of this what needs to be considered is also that often a lot of data that needs to come together is very difficult to measure, for example wait times of different sorts - did the patient walk in well before the appointment time, after meeting the doctor, how much time did the patient wait to get the investigations done and whether this was voluntary or involuntary, so on and so forth. Each of these little data points needs to be collated efficiently with other staffing related data which may not be captured by the same source, to determine how the process really work and was it effective. And this for the multitude of things that go on for a hospital. And all of this is important because it is these factors on ground that determine whether your patients went back with a satisfactory experience, which in turn defines how the brand that you have built, or building, is being seen. I would stress here on one thing. Operational analytics is impactful when accompanied by good communication and action on ground.
Most hospitals do not have the luxury of purchasing sophisticated systems that can spew data with ease. But all is not lost even in these cases. There are ways that a systemic way of collecting data can be easily converted to good information. The key lies in the the implementation of the reporting system. Whichever system or methodolofy is deployed, it is very essential that this does not simply redeem itself to become a data collection system. Each member of each team needs to understand what the data states and what we need to read through. Only then operational analytics can be impactful.
A key point to remember through all of these practises. While technology has made life easier and more and more data driven, the one thing that these analytical tools cannot measure is the effect of the touch and feel and interactions with the patients and their families. We need to view this data through a humane lens of how alive our communication is through each touch point. This is what is the final driving force to better operations and to finally better our profit and loss statements.
with a career spanning 25+ years across different verticals and domains of services, Healthcare IT and Medical devices. Her key strengths are business process re-engineering and startup incubation. She is also the Founder of one of a kind mental fitness platform miindmymiind.com, Advisory Board member of AHHM and Board member of the Punjab Institute of Medical Sciences.
FHIR, the health data standard built for the Internet, is changing how clinicians, hospitals, and governments deliver healthcare. By enabling data-driven care, it promotes better outcomes, efficiency, and patient experience. Global FHIR expert Dr. Russell Leftwich from InterSystems writes about the new standard and its rapid adoption in Asia.
As populations live longer, medical treatments improve, and expectations for equitable access to care increase, demand for healthcare services continues to grow. With the global shortage of medical professionals, no country can meet the healthcare challenges and increasing expectations of an older population by maintaining a traditional approach to care provision.
At the same time, new diagnostic technology, including genomic sequencing, is creating exponentially increasing amounts of data, making new technologically driven approaches even more imperative.
Data-driven models of care and advances in technology like Generative Artificial Intelligence (GenAI) can and must bridge the gap to help clinicians be more productive and patients and their families more involved in managing their care. The Internet and smart devices have already revolutionized almost every other industry. Now, it’s healthcare’s turn.
Until recently, a key reason why we were held back was because health data is much more complex than other industries. One healthcare system could not readily understand and interpret
the data held in another healthcare system. Now that we have a global Internet standard for healthcare data, HL7® FHIR®, those barriers are coming down, particularly in the Asia Pacific region.
Previous health data standards were created to connect two electronic systems together. They were designed before smart devices and the Medical Internet of Things came along. They were not built for the Internet like the application programming interfaces (APIs) that power the apps on our smartphones. On the other hand, FHIR, or Fast Healthcare Interoperability Resources, uses the same technology as the World Wide Web, so interoperating with these devices is also natural.
Probably the easiest way to explain FHIR is to think about a travel booking website. If you want to fly from Singapore to Bangkok on May 5th, in a few seconds, you can see all the flights on all the different airlines. It works because the airline industry has agreed on how to represent flight data –departure time, arrival time, and price. FHIR offers the same for healthcare. It
is like a contract between systems about how to ask for the data and what you get in return.
FHIR is based on a flexible data model. It can be applied to an almost infinite number of use cases – financial, quality, supply chain, scheduling, etc. –not just clinical healthcare, to cover the entire healthcare system.
FHIR is also unique because it allows the same representation of data about an individual to be used in different interoperability paradigms. Because FHIR data is inherently computable, a data set obtained from a FHIR API can be used in messaging with another electronic system, in a FHIR document, or in clinical decision support.
Because of this flexibility, FHIR is not interoperable out of the box. However, if you customize it for a particular use case by creating a FHIR profile, it becomes interoperable. Every country’s healthcare system has different use cases, and they can create and use their own FHIR profiles.
You could say each national healthcare system is a use case. Over
20 countries have created national FHIR Core Profiles, including the U.S. Core, U.K. Core, Japan Core, and Australia Core Profiles. These are highlevel “national use cases” from which more specific profiles can be created for specific use cases in care delivery, public health, research, etc.
Governments across Asia Pacific have been quick to understand the power of FHIR. Indonesia’s national integrated health data platform SATUSEHAT, for example, has adopted FHIR to enable integration with healthcare providers’ electronic medical record (EMR) systems and with APIs for consumer healthcare apps. SATUSEHAT aims to remove the burden of patients taking their records to appointments, reduce duplicate testing and other wasted efforts, streamline service delivery, and improve Indonesia’s population health and genomics capabilities through large-scale data analytics.
Thailand, Malaysia, and Vietnam have also accelerated their digital health plans. Malaysia is deploying a national healthcare data lake around a common platform. Vietnam is planning to build a national platform for connected healthcare that includes interoperability between hospitals. While these countries have individual plans and approaches and are at different stages of digital health development, FHIR will play a key role in enabling interoperability between different systems and devices.
InterSystems is heavily involved in implementing FHIR across the Asia Pacific region. For example, we offer the InterSystems IRIS for Health™ –Indonesia Edition data platform to meet the interoperability and data quality requirements for SATUSEHAT, easing compliance for healthcare providers.
Organizations implementing FHIR for the first time shouldn’t see it as a compliance issue but as an opportunity to unlock the power of their own data
and get a return on their investment. InterSystems IRIS for Health also creates a repository of normalized, usable FHIR data so healthcare providers can perform advanced analytics and AI. Providers can connect the FHIR repository to medical devices, smart watches, mobile apps, insurance systems, and other data sources. Using their preferred data analytics solutions, they can gain actionable insights to improve patient care, experience, and engagement and streamline their operations.
Many people learning about FHIR assume incorrectly that a “FHIR enabled” EMR system has a FHIR repository. However, this is not correct. EMR systems typically use a FHIR API to convert data stored in the EMR database into FHIR resources on demand to a query. This is not the same as storing data as FHIR resources, as the IRIS for Health FHIR repository does, providing better performance, reduced processing requirements, and the ability to supplement FHIR data from multiple sources. You can’t add FHIR data to an EMR system.
The InterSystems FHIR repository also supports SMART on FHIR apps. These apps can do things like generate a pediatric growth chart on demand
With an engineering background and over 20 years of medical practice, Dr. Russell Leftwich is Senior Clinical Advisor, Interoperability, for InterSystems and Adjunct Assistant Professor of Biomedical Informatics at Vanderbilt University School of Medicine. He is board certified in internal medicine and clinical informatics.
using the latest data or provide clinical decision support using FHIR resources stored in IRIS that may have come from multiple different systems, may have been converted from non-FHIR formats, or may have been generated from other apps, such as an app that captures patient-reported outcomes. This could help open up a whole app economy in countries where local EMRs don’t support SMART on FHIR, which was developed for the U.S. and is supported by EMRs built for the U.S.
Other benefits of the IRIS for Health FHIR repository include:
• Support for SQL analytics on native FHIR data in the repository
• Transformation of other health data formats, such as HL7 V2, to FHIR
• The machine learning (ML) and AI capabilities of IRIS, including Vector Search
In Japan, InterSystems has helped to implement FHIR repositories at leading medical institutions. The country’s Intractable Disease Genome Project, for example, uses FHIR to coordinate questionnaires from consenting patients and capture their data from EMR systems at participating institutions.
A FHIR repository built on InterSystems IRIS for Health underpins a clinical decision support system at Osaka Metropolitan University. This repository captures and enables the analysis of data from multiple hospital information systems, including EMR and laboratory systems. At the University of Tokyo Hospital, an InterSystems FHIR repository maps injection orders from the hospital’s EMR system and an order app on clinicians’ smartphones with infusion pump configuration information for administering to patients.
InterSystems is a founding member of Sparked, an Australian FHIR accelerator that aims to deliver a core set of FHIR standards to facilitate electronic health data exchange. In a first for an Australian health jurisdiction, InterSystems is leveraging FHIR to help implement CSIRO’s Ontoserver in conjunction with a new EMR system in the Northern Territory. The Ontoserver FHIR API provides a simplified way to interact with complex structured clinical terminology products such as SNOMED CT-AU. This will improve day-to-day clinical workflows and facilitate future activities such as predictive analytics and research efforts. Such FHIR terminology services are also necessary in order to implement FHIR profiles.
Further afield, New Zealand’s Hira Programme is driving the move to use FHIR-based APIs so citizens can access their health information securely. InterSystems became an early user of
the Hira Programme’s FHIR APIs while delivering the patient administration system (PAS) for Te Toka Tumai Auckland. The FHIR-based APIs make it possible to reconcile PAS data within the wider information systems environment. In addition to demographic information from the New Zealand National Health Index, for example, data can be exchanged with the National Enrolment Service about the doctor and primary care practice a patient is enrolled with.
A theme of many FHIR projects is capturing and analyzing clinical data independently from a single EMR or other healthcare system. Adopting this standards-based approach means far more data can be captured from multiple sources that represent data differently and then represent that data consistently based on FHIR. This will help to realize the benefits of AI and ML which will need vast volumes of clinical data to deliver the promised benefits to patients and clinicians. AI needs data in a standard format and in an interoperable state – using the same FHIR profile, for example – to represent data from different systems in precisely the same way. This is called semantic interoperability and is necessary in order to make reliable predictions, decisions, or recommendations.
FHIR also enables new data-driven models of care that provide better equity and access across the population or a more appropriate level of care for individuals with different conditions. For example, through the integration of healthcare apps and remote monitoring devices, FHIR enables care to be delivered to the community outside of healthcare facilities. This reduces the demand for resources that should be reserved for more acute and complex problems.
FHIR is already being used in Asia for community care. One of my former students and an attendee of my
FHIR workshop, which I have delivered around the world, is now working for a non-government organization (NGO) in Indonesia. She is training community care workers on the use of FHIR-based apps for disease management. These workers are volunteers, not healthcare professionals, who help treat individuals in their homes. You can imagine the future potential to expand initiatives like this by connecting them to a larger healthcare data ecosystem like SATUSEHAT.
FHIR Provides the Foundation for Innovation
Because it is based on the technology of the Internet, FHIR has become the foundation for healthcare innovation that wasn’t possible with previous standards. It is a technology familiar to millions of young, tech-savvy individuals and represents a paradigm shift that we should all promote. With FHIR and low-code/ no-code data platforms like IRIS for Health, we can all be innovators and address our many healthcare challenges.
Jen-Hsun “Jensen” Huang, the CEO of AI chip company Nvidia, was recently quoted as saying that we should stop teaching our children to code because AI can do that for us now. That is an extension of the idea that we can all become innovators without having to write code. We can be innovators if we can identify and describe a problem, often one in our own workspace, and have a unique idea for a solution. And that is exactly what FHIR enables us to do.
Dr. Russell Leftwich will be discussing the importance and evolution of FHIR in Asia at the InterSystems Asia Healthcare Summit on 21-22 August in Jakarta. Learn more about this event at:
The act of breathing is something that we typically do unconsciously. We breathe in and out about 22,000 times a day. However, there is a large stratum of the population that is aware of every breath that they take. People suffering from respiratory diseases like asthma, bronchitis, and allergies are the ones, who would know the value of each breath.
Tetsuya Yamada, Managing Director, OMRON Healthcare Indiamidst severe air pollution, a concerning surge in respiratory diseases, particularly asthmarelated, grips India. According to a report published in 2022, the total burden of asthma in India is 34.3 million, accounting for 13.09% of the global burden. From 150,000 deaths in 1990, the asthma related toll has now surpassed 200,000, persistently rising*.
Most fatalities occur in adulthood, indicating a lack of childhood diagnoses and treatment, necessitating urgent awareness among parents and children about ‘Early Detection and Early Treatment’.
When kids with asthma have lots of asthma attacks, it can harm how well their lungs work as they will grow. If we don't treat the swelling in their airways
when they're young, it can make their lungs weaker as they get older. This can cause a problem where it's hard for them to breathe out, and it doesn't get better. This bad change in their airways makes them lose their lung function faster when they grow up, and it can make them have breathing problems as adults.
This makes Asthma as much a serious social issue as it is a medical issue.
First and foremost, the lack of awareness. The majority of patients and their caregivers are not simply not aware of the long-term ramifications of this condition. In a country like India financial constraints coupled with insufficient access to basic medicines add to the burden. Data from a study done in 2021, by Global Asthma Network showed a significant decline in symptoms of asthma compared to previous studies. The study highlighted underdiagnosis and under-treatment in children and adults with asthma. The study revealed that an alarming 82% of individuals experiencing wheezing and 70% of those displaying severe asthma symptoms had not received an official diagnosis of asthma from a medical professional. Furthermore, the issue of undertreatment was brought to light, with less than 9% of individuals diagnosed by doctors with wheezing or severe asthma using daily inhaled corticosteroids (ICS), across various age groups.
The factors contributing to this underdiagnosis and under-treatment are multifaceted. They include limited access to medical facilities, socioeconomic challenges such as poverty and low levels of education, patient ignorance, improper medication administration techniques, non-adherence to prescribed treatments, and inadequate communication skills among healthcare providers.
Also, the stigma associated with asthma often leads parents to conceal the diagnosis, resulting in sporadic medication usage, typically only
during symptomatic episodes or when discomfort becomes intolerable.
These findings underscore the considerable morbidity associated with asthma and the strain it places on healthcare resources. Addressing this issue is of paramount importance, particularly within the context of asthma education programs, as it holds significant clinical implications in terms of treatment compliance.
Although people can make changes to their lifestyle to reduce symptoms, there are limitations to what individuals can achieve in the short term when it comes to avoiding air pollution, managing genetic factors, or handling environmental triggers like pollen and mites. This is where the idea of "Early Detection & Early Treatment” comes into picture led by technology and social interventions.
Creating awareness and removing the stigma attached to Asthma - These
are the two most important things that we can do. Parents need to be aware that even a simple night cough can be a symptom of asthma or any respiratory problem. The other aspect is to make sure that the medication is followed through properly with or without any symptoms.
Effective use of Nebulizers can be another way to help our children navigate asthma. Nebulizers, owing to the precision in lung medication, can play an important role in managing respiratory ailments as kids can be hypersensitive to dosages and slight variations in medication dosage can impact symptom control.
Here are some reasons why nebulizers may be a better option for children:
• Coordination with inhalers can be difficult for some children, but nebulizers don't require as much coordination.
• Nebulizers are suitable for children of all ages.
• Regular dosing protocols with
nebulizers can reduce the frequency of hospital visits, as the instances of severe flare-ups decrease.
Children with asthma require access to nebulizers more than adults do. This is because treating asthma at a young age is crucial. In many cases, doctors prescribe medication to young children, but their parents may stop the medication prematurely due to myths surrounding the side effects of these drugs. It is essential that children continue their medication until the doctor advises it to stop. If discontinued before the appropriate dosages, it can cause symptoms to reoccur and also result in remodeling of airways which might lead to further worsening of asthma in children.
It's crucial to remember that nebulizers should always be utilized in conjunction with a comprehensive treatment plan and under the supervision of a healthcare professional. By collaborating closely with their healthcare provider, individuals can ensure that their nebulizer is being used safely and effectively in treating their respiratory symptoms.
A prevailing myth suggests that respiratory problems in children are a phase they will naturally outgrow. While some respiratory conditions, such as transient wheezing, might be temporary, others like asthma or chronic bronchitis can persist into adolescence and adulthood. Early diagnosis and appropriate management are crucial to ensure children receive the necessary care and support for optimal lung health.
Also, there is a persistent myth that the use of nebulizers for respiratory treatments can lead to addiction. In reality, Nebulizers are not addictive, and their use is strictly regulated by healthcare professionals to provide targeted and controlled medication doses. They are a valuable tool in managing respiratory conditions, helping individuals breathe more comfortably and efficiently.
I feel education and awareness can come in handy and can create a real difference. We need education programs, especially in schools.
Breaking down these misconceptions including the myth about nebulizers being addictive, is a crucial step towards building a healthier future for individuals with respiratory diseases led by "Early Detection and Early Treatment”.
The focus needs to be on stressing the importance of early detection and prompt treatment, ensuring respiratory well-being for children through timely and appropriate medication.
Dispelling these myths about respiratory diseases is essential for fostering a more informed and compassionate society. By understanding that respiratory diseases are diverse in their causes and can affect people of all ages and backgrounds, we can work towards creating a supportive and
technologically-enabled environment that promotes awareness, prevention, and effective management of these conditions. Early detection of respiratory diseases is key, leading to prompt treatment and improved outcomes.
I feel education and awareness can come in handy and can create a real difference. We need education programs, especially in schools. During such outreach, we can impart knowledge about asthma to parents and teachers alike and emphasize the importance of early medication from a medical perspective. Simultaneously, we can provide school children with simpler information using comics and other engaging materials, making it easier for them to understand what asthma is and how to manage it. If we can establish model schools in each area and promote these initiatives, it could have an immense positive impact on the respiratory health burden and its management in India.
The approach should aim to include teachers to enhance their understanding of asthma and equip them to actively participate in managing the condition alongside their parents and healthcare providers.
Tetsuya Yamada is Managing Director of OMRON Healthcare India. Before joining this position, he worked as Senior General Manager of Global Product Planning for Respiratory related products and Pain relief products at OMRON Healthcare HQ (Japan). He has also worked in OMRON Healthcare Brazil as Director, where he was responsible for Corporate Planning, Product Planning, Regulatory affairs and PMI (Post Merger Integration) for acquired companies. He had a successful stint with Sharp Corporation before joining OMRON. Tetsuya holds a bachelor’s degree in economics and a Master of Business Administration (MBA) from Kobe University, Japan. He is a recipient of “Outstanding Leadership Award” in Health 2.0, Dubai (2023) and “Most valuable thesis in MBA” award from Kobe University (2008).
CT coronary artery calcium scoring is guideline indicated for almost 50% of the adult population. However, this lifesaving technology that allows for the early detection of CAD is vastly underutilised worldwide. A formalised scientific programmatic approach can increase utilisation and deliver significant clinical and economic results.
Dr Jeffrey J Fine MS, PhD, Executive Director, National Heart Health Program
For 50% of adults worldwide, the first symptom or warning of heart disease will be a heart attack or death. Despite the best of intentions, cardiology, imaging, and healthcare systems are not accurately identifying these vulnerable patients in a widespread manner until it is often too late. The most vulnerable demographic includes adults that fall into the “intermediate risk” category (ASCVD 7.5%-20% 10-year risk or males 45+ females 55+ years of age) defined by cardiovascular event risk prediction algorithms. The diminished predictive strength among this risk cohort exists because predictive models have a higher accuracy rate among the more predictable low-risk and high-risk cohorts but lack the same efficacy among the large segment of patients categorised as “intermediate risk.” To further illustrate the population health opportunity, consider that approximately 45% of adults fall into this largest intermediate risk designation and therefore remain underserved and vulnerable.
Prior to Cardiac CT imaging, including Coronary Artery Calcium Scoring (CAC), healthcare providers were limited to risk algorithm reliance and risk management until the presentation of symptoms allowed for diagnostic imaging to be employed. This left the largest risk cohort exposed, as, for 50%, a major coronary event would likely be that first symptom. With the genesis of CT based CAC testing availability, providers can now obtain a non-invasive diagnostic scan of the coronary arteries using this five
minute test. The test utilises relatively new software that detects and quantifies calcified plaque in the arteries of the heart. The CAC study allows for an unequivocal diagnosis or rule-out of atherosclerotic disease and significantly changes the clinical paradigm, allowing an enhanced opportunity for heart attack prevention and a corresponding reduction in the number of preventable deaths. In many regions the test is being referred to as the “Mammogram of the Heart.”
While published cardiovascular risk and prevention guidelines such as ACC, AHA, SHAPE, and ESC suggest almost 45% of adults would benefit from CAC scoring, hospitals today average less than one patient per day being tested (U= 3.5/week). CT CAC scoring is vastly underutilised, non-invasive, and is definitive for disease identification. Most hospitals in developed regions have invested in the technology and offer this diagnostic/preventive service, but lack patient volumes mirroring the Guideline suggestions. This equates to healthcare systems missing clinical opportunities for preventing heart attacks and growing the cardiovascular, imaging, and population health service lines.
Hospital underperformance is typically due to the absence of a focused programmatic approach, comprehensive primary provider training, and ongoing quality data acquisition and analysis to foster clinical and economic improvement.
CAC scoring outcomes data from over 150 hospitals in 16 countries, and over 350,000 CAC cases in the International Heart Attack Prevention Database https://nationalhearthealth. org/heart-attack-database suggest increased utilisation and referral patterns will afford an efficacious heat attack prevention strategy that has the potential to change the paradigm of atherosclerotic disease worldwide. The patient population that this technology will benefit most has been well defined and is well published. Increased adoption
and utilisation will be largely determined by healthcare systems prioritising this technology and formalising patient selection/referral and medical management training to the front-line medical provider community. (Figure:1)
The International Heart Health programme performed CT CAC testing on 350,142 asymptomatic patients (mean age 56.4), without known CAD, and classified “intermediate risk,” using the Framingham, ASCVD, or SCORE algorithms, between 2012-2022 in 151 medical facilities around the world. The CT CAC results were acquired using multi-slice CT scanners of at least 16 slice technology. No contrast was necessary for CT Calcium scoring procedures and the average testing time was less than five minutes in the scanner.
Traditional cardiovascular risk factors among tested patients included hypertension, elevated LDL cholesterol, diabetes, family history, tobacco use, and obesity. The most prominent risk factors that correlated best with increased disease incidence via CT calcium scoring were as follows: family history of CAD, elevated
LDL cholesterol, and diabetes. Included patients averaged 3.1 risk factors in this worldwide cohort.
Calcium scoring outcomes/results include the following cardiovascular event risk categories and are based upon “Total Agatston Value” as determined by the presence or absence of detected calcification within the coronary arteries. (Figure:2)
Accredited programme sites identified 213,581 asymptomatic patients (61%) with dae novo coronary artery disease using CT calcium scoring. Significantly, 18.2% (n=63,724) of patients tested were found to have “likely obstructive coronary artery disease” based upon a Calcium score of >400 Agatston value and were referred to cardiology for further testing and improved and more aggressive medical management. Scores exceeding 1000 are indicative of critical levels, often associated with the presence of at least one substantial blockage in a coronary artery. Participating sites identified 12,949 patients (3.7%) with these lifethreatening scores and a majority went
on for stent or CABG surgeries. The number needed to diagnose (NND) a patient having obstructive CAD was only six, and to identify at least one vessel critical stenosis was only 28, confirming the population health efficacy of this diagnostic test. (Figure:3)
Importantly, participating hospitals reclassified 136,561 patients (39%) to “low risk” based upon a zero (0) calcium score. Evidence suggests these patients are at extremely low risk of a major coronary event (less than 1%) for the next five years and the need for further short-term evaluation and therapy are currently being debated.
Mean radiation exposure for coronary calcium scoring procedures was 1.01 mSv, which is patient friendly and comparable to mammography which has been used worldwide for
decades with cost-benefit ratio widely accepted.
The economic impact at accredited sites was similarly impressive for both the CT imaging department and the cardiovascular service line. The implementation of a guideline based and accredited CAC scoring programme increased referrals and overall utilisation significantly from less than 1 patient/day to over 10 patients/ day on average. Corresponding revenue averaged $311,550 annually in imaging department increases and $926,600 annually in cardiovascular service revenue gains. (Figure:4)
Adoption of an evidence based, and guideline supported CT coronary calcium scoring programme can promote early detection and treatment, and thus change the paradigm of cardiovascular
disease, reduce major coronary events, and enhance the cardiovascular service and imaging lines of healthcare providers as we advance worldwide toward lower cost, non-invasive testing for chronic disease. Clinical outcomes data is remarkably similar across countries and even continents as this test becomes increasingly entrenched in the standard of care across the Western world. The opportunity to change the paradigm of cardiovascular disease and its debilitating effects across populations and reduce healthcare expenditures globally is now.
Dr. Jeffrey J Fine is a Cardiovascular Physiologist specialising in preventive cardiology and early detection via cardiac imaging. Dr. Fine is the Executive Director of the National and International Heart Health Initiatives focusing on the early detection of heart disease and has worked with and conducted training at over 150 hospitals across 16 countries. He is also a founder and CEO of International Cardiology Consultants, LLC which is a group of leading physicians from around the world focused on the prevention of heart attacks across the globe.
Dr. Fine is an internationally recognised expert in the field of coronary artery disease, and heart attack prevention with over 100 invited speaker presentations in over 20 countries.
This pre-specified sub study of data from the MISTIE III trial investigating the association between cerebral small vessel disease (CSVD) features on MRI and therapeutic outcomes of minimally invasive surgery in patients with acute spontaneous supratentorial intracerebral haemorrhage. Main findings showed that CSVD burden is associated with functional outcomes in those with successful haematoma reduction (end of treatment ICH volume ≤15 mL).
Wendy C. Ziai, MD, MPH, Department of Neurology, Anesthesiology and Critical Care Medicine, Johns Hopkins UniversityCerebral small vessel disease (CSVD) comprises clinical, neuroimaging and pathological findings involving the small penetrating vessels of the brain. CSVD has been linked to cognitive dysfunction and is both a risk factor for spontaneous intracerebral haemorrhage (ICH) as well as a predictor of poor functional outcomes after ICH occurrence. In particular, brain imaging biomarkers of CSVD, such as white matter hyperintensities (WMH), cerebral microbleeds (CMBs), or superficial siderosis (cSS), are associated with a higher risk of intracerebral haemorrhage (ICH) recurrence, and with poor outcomes in predominantly lobar hemorrhages.
There are few proven therapies for spontaneous ICH and although minimally invasive surgery (MIS) is being intensely studied, the definitive efficacy of surgical haematoma removal remains controversial, including specific
patient groups who may benefit the most.
This study was a pre-specified subgroup analysis in which we investigated whether cerebral small vessel disease is associated with functional outcomes after MIS for spontaneous ICH as performed in the Minimally Invasive Surgery Plus Alteplase for Intracerebral Haemorrhage Evacuation (MISTIE III) trial, the first clinical trial of stereotactic thrombolysis for spontaneous ICH to define thresholds for potential benefit from clot volume reduction. MISTIE III was neutral for the primary outcome of modified Rankin Score (mRS) 0-3 at one year follow-up comparing patients treated with MIS vs. standard medical care (SMC). However, the subgroup of patients with successful surgery (reaching the pre-specified end of treatment (EOT) volume of <15 mL) experienced a significant improvement in good outcomes compared with
SMC. This group was therefore of primary interest to the current study.
We defined CSVD using five welldescribed CSVD features according to the STRIVE consensus: lacunar infarcts, white matter hyperintensities (WMHs), enlarged peri-vascular spaces (EPVS), cerebral microbleeds (CMBs), and cortical superficial siderosis (cSS). We also analysed this data using 3 grading tools: the CSVD burden score, the Cerebral Amyloid Angiopathy (CAA) score, and a modified CSVD (mCSVD) score which we developed based on the distribution of CSVD features in our cohort. The cohort consisted of 288 patients who had at least one MRI (performed at a median of 1 day after ICH onset), and full clinical data.
In the MISTIE III trial cohort, which included only patients with good baseline function (mRS 0-1), but with large ICH (>30 mL) we found a high proportion of CSVD imaging findings on the baseline MRI. Using modified Boston criteria 61% of this severe ICH cohort had “possible CAA,” and 18% met criteria for “probable CAA.” These CSVD findings including all 3 compositae scores were almost all (with exception of EPVS in the basal ganglia) significantly associated with poor outcome at 1 year in the surgical group. In the SMC group, none of these MRI features were associated with poor outcome after adjustment for other covariates.
Comparing the SMC group to MIS patients with successful surgery
(EOT volume <15 mL), we found that presence of lacunes, severe white matter hyperintensities and CAA score>1 significantly modified one-year outcomes in the MIS group in favour of lower odds of a poor outcome when these MRI findings were absent. Stated another way, successful haematoma reduction by MIS was associated with significantly lower odds of good functional outcome when patients had a higher total burden of CSVD, and particularly presence of lacunes and severe WMHs. Comparing all MIS to SMC patients, we did not find any significant heterogeneity in the effect of MIS on one-year outcomes by any specific CSVD feature or by CSVD scores.
Figure 1 shows mRS score distribution by CAA score 0–1 versus 2–6 in (A) full MRI cohort (n=288), (B) MIS (n=149) versus medical (n=139) groups and (C) EOT volume≤15 mL (n=94) versus>15 mL (n=194). This figure shows that the odds of a good outcome (mRS 0–3 vs 4–6) were significantly higher for patients with CAA score 0–1 (vs 2–6) in fully adjusted analyses for the full cohort, MIS group and group with EOT volume ≤15 mL, but not for the SMC group and group with EOT volume>15 mL.
These findings emphasise the importance of substantial haematoma volume reduction when performing MIS for ICH, and the clinical implications of pre-existing small vessel disease in defining long-term outcomes even after successful clot evacuation.
The specific MRI features of greatest importance, lacunes and WMHs are both markers of cerebral ischaemia and are associated with severity of hypertension and with cognitive decline in older people. Therefore, chronic vascular dysfunction may be an important pre-existing condition which limits good outcomes after surgical treatment of ICH. Alternatively, these ischaemic markers may portend new conditions that limit recovery such as post stroke depression, cognitive impairment, and new ischaemic strokes, all of which are associated with white matter hyperintensities.
This data is consistent with the ischaemic stroke literature showing the relationship between CSVD markers and the outcomes of mechanical thrombectomy for large vessel occlusion, where severe WMH and higher CSVD scores have been correlated with poor 90-day outcomes. These data and ours highlight the current interest in identifying patients most suitable for interventional treatments to increase rates of good prognosis.
This was an exploratory study and has both strengths and limitations. MISTIE III was a well adjudicated clinical trial with blinded outcomes and a core of trained imaging reviewers blinded to clinical information. Weaknesses include generalisability where MISTIE III was very selective and specifically excluded patients with baseline mRS >1, ICH volume <30 mL, and clinical herniation. The trial was conducted in tertiary care academic settings which may not represent medical care in a community setting. Finally, MRI was difficult to obtain in high severity ICH patients limiting the number of available studies which may have biased our sample although baseline ICH volume, Glasgow Coma Scale and outcomes were not different between participants with and without MRI. More sophisticated MRI analysis including volumetric analysis of WMH and diffusion tensor imaging analysis of integrity of white matter tracts are areas for future research.
As the first study to evaluate use of MRI to target surgical therapy to those most likely to benefit, we do not currently recommend utilisation of CSVD features or CSVD scores as selection criteria for MIS for ICH. Rather these findings may help to stratify or select patients for clinical trials for ICH interventions where such imaging is available.
Dr. Ziai is Professor of Neurology, Neurosurgery, and Anesthesia/ Critical Medicine at the Johns Hopkins Medical Institutions in Baltimore Maryland. She is Co-Chair of the Grants Committee of the Neurocritical Care Society and is an Associate Editor for the journal Neurocritical Care. Her research is focused on mechanisms of injury and recovery in intracerebral hemorrhage and on multicenter clinical trials of minimally invasive surgery to treat hemorrhagic stroke.
Imaging technologies are the key to early disease detection, enabling timely access to care. Computed tomography (CT) is a cornerstone for diagnosis and management of a wide range of medical conditions, with AI and new technologies delivering next level of diagnostic confidence and advanced workflow, improving outcomes, consistency and productivity.
Chris Kim, Head of Imaging, Philips APACSoutheast Asia’s healthcare systems are facing a triple threat. Deemed an ageing population, the ASEAN population is getting older, faster, and that means more people will need care. According to the World Health Organisation (WHO), 1 in 5 people here will be aged 60 or above by 2050. Hospitals and healthcare facilities will need to handle this surge to treat the complex health problems older people often have.
Additionally, non-communicable diseases like cardiovascular disease (CVD) are becoming more common, imposing a
growing health burden in Southeast Asia, draining resources from healthcare systems. The region is also facing a significant shortage of healthcare professionals – by 2030, the estimated shortages of health workers will be 6.9 million, nearly 40% of this shortage burden will be in the Southeast Asia region.
This is not helped by healthcare workforce challenges such as the increasing risk of burnout faced by healthcare workers. Already, a 2021 study found that 20% of Southeast Asian frontline healthcare workers reported job burnout, while moderate anxiety and depression were affecting 10% and 4% of the respondents.
Tackling the triple threat with imaging technologies
In response, healthcare systems are shifting from volume-based care to value-based care, transitioning from merely providing medical services towards optimising patient outcomes and cost-effectiveness. Investing in imaging technologies is an imperative for healthcare providers to enable valuebased care. Radiology scans are often critical in ensuring accurate and effective
diseases management. Access to imaging technologies is the key to early disease detection and diagnosis, which allow for timely access to effective treatments, lowering cost of care in the long run. Technologies also help healthcare facilities relieve administrative tasks and ease workflow so that healthcare professionals can dedicate more time to patient interactions and outcomes. This not only enhances their professional satisfaction and reduces burn-out, but also paves the way for better quality care for patients.
CT modality, a cornerstone for timely diagnosis and access to care Zooming into the imaging needs in ASEAN, the modality of computed tomography (CT) scan is a cornerstone for accurate diagnosis of a wide range of medical conditions due to its ability to provide incredibly detailed views inside the body with speed and accuracy. CT scans capture cross-sectional images, like slices of bread, revealing bones, organs, and soft tissues in high resolution. This detailed information allows doctors to diagnose even the most complex and difficult-to-treat conditions, from infections and tumors to blood clots
and bleeding. Furthermore, the precise information from CT scans goes beyond diagnosis where doctors can use these images to plan surgeries and other procedures with greater precision, ultimately leading to better patient outcomes.
Over the last decades, there have been huge advancements in the CT modality, from time taken to complete a scan, image resolution, reduction of radiation doses to advanced techniques for specific examinations. With the challenges we are seeing today, the next generations of CTs must be designed with healthcare professionals in mind, empowering them to see beyond clinical complexities and workflow obstacles to improve outcomes, consistency and productivity, and offering a new perspective in sustainable healthcare.
Today, first-time right imaging enabled by spectral-detector CT systems presents significant benefits in reducing the human and financial costs of missed and delayed diagnoses. Unnecessary, suboptimal, repeat imaging leads to
wastage of health systems’ resources and healthcare workers’ time. These systems deliver high quality images for every patient on every scan and a timesaving workflow which enable healthcare professionals to rapidly provide a confident diagnosis and an effective treatment plan for every patient. In some cases, 26% reduction in follow-up scans due to incomplete diagnosis, and 34% decrease in overall time to diagnosis have been observed with these systems. These systems also feature an advanced visualisation workspace powered by artificial intelligence (AI) to bring clinical insights directly into clinical workflows to inspire confident decisions for various clinical domains from Oncology to Cardiovascular and enables integration of results virtually, anyway, including the primary reading environment.
AI can deliver next-level diagnostic confidence and advanced workflow which will free both CT technicians and radiologists from tedious, timeconsuming tasks so they can spend more time focused on their patients. AI can be leveraged for new clinical capabilities and more workflow advances to address diagnostic imaging needs for complex diseases where precise patient diagnosis is crucial. For example, more accurate and reliable imaging results are needed to better manage increase in complex cardiac cases. High quality AI-enabled CT systems can triage patients presenting with chest pain with undiagnosed coronary artery disease to free them from unnecessary invasive procedures by meeting the advanced imaging requirements for this “CT first” approach. With its detector technology to support AI-based reconstruction, high-quality imaging can be delivered at much lower radiation dose.
Advanced technologies also enhance productivity of high-throughput, short-staffed radiology departments. Newer CT systems feature virtual tools to facilitate remote collaboration, education, and training, which can be instrumental in overcoming challenges
related to increased patient caseloads, complex cases, staff shortages, and budget constraints. These tools facilitate virtual over-the-shoulder support, enabling expert imaging technologists to assist their less experienced or specialised colleagues at distant locations while the patient is undergoing a diagnostic scan procedure. Collaborations such as these bring about the added advantage of enhancing healthcare access in remote and rural areas, where there is often a scarcity of specialised staff, such as radiologists.
Emphasising lifetime value and sustainability, eco-design principles can be employed in the design of CT systems to lower energy consumption and promote circularity. Reliable services, upgrades and clinical offerings can be applied to extend the life-time value and uptime and future readiness of the system.
Partnership is key Technology is bringing countless possibilities to address the imaging needs of patients and improve healthcare workforce experiences. To ensure health systems truly reap the benefits of these innovations,
collaboration between healthcare providers and technology innovators is key. Aside from workforce shortages, we are seeing a shortage of imaging equipment in low- and middleincome countries (LMICs) including in ASEAN. For instance, while high-income countries (HICs) boast nearly 40 CT scanners per million inhabitants, LMICs have fewer than 1. With imaging being essential to ensure timely diagnosis, appropriate treatment of diseases, and access to quality care for patients, healthcare providers and technology innovator must work together to address this.
Indeed, collaboration creates a platform for knowledge and best practise sharing, allowing technology providers to better understand and meet the needs and demands of hospitals and the healthcare ecosystem. With these technological advancements, across CT and imaging, healthcare practitioners can be better supported and enabled to deliver the best care for patients and to help meet the healthcare needs across ASEAN.
References are available at www.asianhhm.com
Mr. Chris Kim is Head of Imaging for Philips APAC, responsible for leading Philips’ Imaging business across multiple imaging modalities including MR, CT and DXR in the APAC markets.
A professional business leader with over 18 years of experience in South Korea, ASEAN and the Pacific, he has strong knowledge and expertise in medical device, software, long-term strategic partnership, new business development, sales operations, services, and pharmaceuticals. His specific areas of interest are in Smart Hospital, Artificial Intelligence, Big data, and Cloud.
Chris has held various healthcare leadership positions in multinational companies throughout his career.
Chris has a bachelor’s degree in Life Sciences from Korea University and completed executive programs in INSEAD and Yonsei University.
Medical technology, over the past 100 years have revolutionised healthcare delivery, alleviated pain and prolonged life. As the world transforms, medical technology transforms faster. What are its directions? Where is it headed? How will it transform? Here are some futuristic, yet pragmatic views from an experienced industry executive.
Probir Das, Group Executive Officer, Terumo CorporationMedical technology, essentially consists of devices and information systems that diagnose, prevent, treat, or improve a person’s health and well-being. Understandably therefore, it a huge swath of tools and technology. The USFDA, a leading regulator of medical technology, along with many other regulators classify medical technology or devices across three very broad types, depending on their risk and need for safety and effectiveness; Class I is lowest risk, while Class III is highest.
The magazine, and thus this article is likely addressed to an audience with innate involvement in the task or ecosystem of medical treatment. You are already likely familiar with the myriad of medical
technology. However, to look into the future, we must use a current lens.
For someone involved in medical technology for over three decades, I have a rather simplistic 9 X 9 approach; cluster medical technology around 9 broad applications and looking at 9 trends that I believe will propel the future.
1. Tools or systems that diagnose through physical or chemical analysis of tissue samples (microscopy, biochemistry, haematology, molecular biology, etc.)
2. Tools or systems that diagnose through the science of imaging (X-ray, CT, MRI, Fluoroscopy, etc.)
3. Devices used perform endoscopic or surgical procedures, both manually and by robotic means (to look into, cut open, drill, dissect, cauterise, ligate, suture, seal, etc.)
4. Implants of various sorts to enhance organ functions (stents, pacemakers, IOLs, orthopaedic, dental, vascular, gastrointestinal, etc implants)
5. Devices used to deliver nutrition, medication or a device or implant into the patient’s body (syringes, catheters, tubing, pumps, etc)
6. Devices to monitor or aid the patient’s condition, and ensure impairments are electromechanically or radiologically monitored or mitigated (ICU monitors, ventilators, heart lung machines, apheresis, dialyzers, radiation therapy equipment, etc.)
7. Bags, pouches, and containers to collect or store body fluids or discharges (blood bags, evacuated blood collection tubes, urine bags, etc.)
8. Furniture and electrical fittings that deliver the treatment infrastructure (beds, tables, speciality chairs, OT lights, etc.)
9. Software or information systems that aid by collecting, storing, analysing data, and providing insights to health care professionals on treatment options and success status.
With that as a perfunctory context, let me share the trends I see shaping, in various speeds, and not in any order, medtech’s future.
I am deliberately staying away from predicting the future treatment of specific clinical domains (e.g. neurotherapy as compared to infectious disease), or how medtech company business models are likely to morph (e.g. devices companies expanding into health services), but rather sharing my thoughts basis tech or engineering trends, as these trends may apply across several therapy domains.
Over the past three decades there has been much advance in minimally invasive procedures. The march of this will continue. While the applications are virtually limitless, I am providing a few examples.
Even at a basic level we are likely to see needle-free injections, aided by lasers
and bubble guns that will push liquid injectables at ~ 100km / hour, that will penetrate skin almost obsolete damage, wound or pain.
Such devices as ingestible cameras already significantly reduce patient stress and improve visibility.
Heart valve replacements are moving full throttle to minimally invasive, and I see that most of openheart surgery will move to small incision procedures reducing blood loss, infections and hospital stay
(ii) Personalization / customization
Such technologies as better imaging and 3D printing are opening new vistas of heavily personalised devices. From AI powered predictive dental aligners to 3D printed prosthetics the power of personalisation will revolutionise outcomes.
(iii) Robotics & Exoskeleton
Medical technology is ‘miracle’ technology. It helps healthcare to improve, often quite disruptively. As the world of technology transforms, medtech too is transforming, both technologically, and through business model innovation, to continue to create its magic on improving life. The scope of this transformation is limitless
General surgery, orthopaedics, interventional cardiology, etc. will largely migrate to precision robotics, improving control, flexibility and remote capabilities. Recently, there was robotic angioplasty performed across two different cities One can only imagine how the expansion of this technology will improve access to highly skilled physicians into remote locations around the world.
Exoskeletons will augment and correct neurobiological impairments and will create wonder devices that aid mobility and quality of life.
(iv) Connectivity / Interoperability
This is one area that will see the maximum rapid improvement in medical care. Applications and examples are limitless, but I am just providing a few illustrative examples.
As devices across different companies and different applications start connecting with each other, the ecosystem output will drastically increase and minimise cost.
Imagine the power of a syringepumps that seamlessly communicate with monitoring devices and anaesthesia machines and can deliver virtually robotic assisted anaesthesia.
Another example remotely monitored beds not only will reduce healthcare costs, but also carry quality of care to remote locations and non-hospital settings, thereby liberating access.
While computerised clinical decision support systems (CDSS) existed since the 1970s and 80s, the advent of AI and high-speed computing will completely change the paradigm in future. Medical decisions are after all calls of evidencebased judgements, and the modern forms of CDSS rely on the billions and trillions of medical data points, triangulate several thousand patient parameters quickly, and suggest treatment protocols and watch out flags to clinicians that avoid complication, enhance outcomes, and reduce cost. Most medical technology companies are on a device to solution drive and are arming themselves with different forms of CDSS.
While software often drives the medical device hardware, software as medical device is defined as software intended with a medical purpose running on a generally non-medical platform (e.g. medical apps on a smartwatch), or software that is linked directly to treatment planning.
Medical devices have always come out of medical device hardware companies and have been a physically engineered set of products. This paradigm is already changing fast and will further rapidly change and redefine the medical technology ecosystem, bringing in non-traditional disruptors (such a patient journey app designers) into the game.
As more and more software and connected devices come into play,
healthcare cybersecurity threats will rapidly climb. IBM’s 2023 Cost Of A Data Breach report pegs the rise of health cybercrime at 53% over the past 3 years.
Medical records, treatment data, and online nature of connected devices (even lifesaving ones) are already targeted in such examples as attacks on HCA, USA and Medibank, Australia.
Governments and regulators around the world will become more vigilant and demand the medical technology companies to label the threat potentials and offer robust security features.
While drugs and medical devices have been separate worlds so far, the lines between these two industries will blur, especially with many medical devices and medicinal products forming single integrated solutions (e.g. tissue allografts, pre-filled delivery devices, drug coated balloons, drug eluting stents, etc.)
(viii)
This is where I have taken the liberty of a bit of crystal ball gazing.
Medical education is rather traditional and has not kept up with
the rapidly changing technology landscape. It still tends to be very much in the hospital setting and using patients as subjects. This will transform fast. Due to massive improvements in sensor technology, medical training simulators these days can replicate clinical complexities almost one is to one, in risk free learning environments. No pilot today flies an aeroplane without being certified (and repeatedly) on a set of flight-simulators. Similar reality will come into the medical technology world. The transformation will mean that (a) most simulators will be strictly regulated, as in the airline industry, and (b) many medical technology companies will build and acquire simulation technology.
Lastly, confronting the reality that used and single use medical devices comprising of plastics, metal, battery components have a big negative impact on the environment, there will be more societal and regulatory pressures to reuse, recycle, and use sustainable materials. This will require the medtech industry to rethink packaging, choice of raw material, as also the entire supply chain and business model. Most reputed medical technology companies have undertaken carbon neutrality goals and are redefining how they operate. This trend will determine their ‘right to operate’.
References are available at www.asianhhm.com
Probir Das is a global medical technology executive with over three decades of experience. Since 2012, he works for Terumo Corporation, a century old medical technology multinational, and is currently responsible for overseeing Terumo’s operations across Asia Pacific and India. He is a Group Executive Officer, a board member of several Terumo subsidiaries, and is the Vice Chair of Asia Pacific Medical Technology Association (APACMed).
The integration of cutting-edge technologies in healthcare is transforming patient care and reducing stress among healthcare professionals. This essay examines the pivotal roles of telemedicine, artificial intelligence (AI), wearable technology, and electronic health records (EHRs) in enhancing treatment outcomes and professional satisfaction.
Joana Santos Afonso, CEO & Founder, Careceiver Chris Brucker, CEO & Founder, Nammu Lab SASTelemedicine has emerged as a crucial tool, particularly in remote patient consultations and monitoring, drastically reducing hospital visits and exposure to infections. This technology is a boon for individuals in underserved areas, ensuring they receive timely care. Notably, it has also been instrumental in chronic disease management through regular virtual follow-ups, allowing for dynamic treatment adjustments.
Moreover, telemedicine plays a crucial role in minimising exposure to hospital-acquired infections. Traditional hospital visits often involve waiting in shared spaces, which can be a potential source of various infections. Telemedicine eliminates this risk by allowing patients to consult with their healthcare providers from the safety and comfort of their own homes.
In addition to patient consultations, telemedicine can also facilitate remote patient monitoring. Healthcare professionals can monitor a patient’s vital signs and symptoms in real-time through connected devices, enabling them to respond promptly to any changes in the patient’s condition. This not only leads to timely and personalised care but also empowers patients to take an active role in managing their health.
Furthermore, telemedicine can provide much-needed support for chronic disease management. Regular virtual cheque-ups can help healthcare professionals track the progress of the patient’s condition and adjust treatment plans as necessary. This continuous, proactive care can lead to better health outcomes and improved quality of life for patients.
Artificial Intelligence (AI) and Machine Learning (ML) are transforming the healthcare industry by providing innovative solutions for diagnosing and treating diseases. These technologies can analyse vast
amounts of data, often far beyond human capacity, to predict disease patterns, enabling early diagnosis and intervention.
AI and ML algorithms can process and analyse complex medical data, including electronic health records, genomic data, and medical images. For instance, AI algorithms can detect anomalies in medical images such as X-rays, CT scans, and MRI scans. These algorithms are trained on thousands of annotated images and learn to recognise patterns associated with different diseases. This can aid in the early detection of diseases like cancer, where early diagnosis significantly improves the prognosis.
Moreover, AI and ML can be used to predict disease progression. By analysing a patient’s health data over time, these technologies can identify patterns and trends that may indicate a worsening condition. This allows healthcare professionals to intervene early, potentially preventing the disease from progressing to more severe stages.
AI and ML also play a crucial role in personalised medicine. They can analyse a patient’s genetic data to identify mutations associated with specific diseases. This information can be used to develop personalised treatment plans that target the underlying genetic causes of the disease, improving the effectiveness of the treatment.
In addition, AI and ML can help healthcare professionals stay updated with the latest medical research. These technologies can analyse and summarise vast amounts of medical literature, helping healthcare professionals keep up with the latest developments in their field.
Wearable technology, a significant development in the healthcare sector, has the potential to revolutionise patient care. These devices, which include fitness trackers, smartwatches, and heart rate monitors, can monitor vital signs such as heart rate, blood pressure, and glucose levels in real-time.
The continuous stream of data provided by these devices offers a comprehensive view of a patient’s health status. This is a significant advancement over traditional methods, which typically provide only snapshot data during clinic visits. With wearable technology, healthcare professionals can monitor patients’ health around the clock, allowing for more accurate diagnoses and personalised treatment plans.
One of the key benefits of wearable technology is its ability to detect abnormalities in vital signs early, often before the patient is even aware of a problem. This allows for timely interventions, which can be crucial in managing conditions such as heart disease or diabetes. Early detection and intervention often lead to better health outcomes and can prevent complications.
Moreover, wearable technology empowers patients to take an active role in their health. By tracking their vital signs, patients can gain insights into how lifestyle factors such as diet, exercise, and sleep affect their health. This can
motivate patients to adopt healthier habits, further improving their health outcomes.
Wearable technology also reduces the need for hospital visits, as many chequeups can be done virtually. This not only makes healthcare more accessible, especially for those with mobility issues or those living in remote areas but also reduces the burden on healthcare systems.
Electronic Health Records (EHRs) are revolutionising the healthcare industry by streamlining the documentation process. They significantly reduce the time healthcare professionals spend on paperwork, thereby allowing them to focus more on patient care. This shift in focus not only enhances the quality of care provided but also reduces the stress levels of healthcare professionals.
A key aspect of EHRs that amplifies their utility is interoperability. Interoperability refers to the ability of different information systems, devices, and applications to access, exchange, interpret, and cooperatively use data in a coordinated manner, within and across organisational boundaries. This feature is particularly crucial in the context of EHRs.
Interoperability in EHRs enables seamless data exchange between different healthcare providers, irrespective of the specific EHR systems they use. This means that a patient’s health information can be easily shared between different doctors, specialists, hospitals, and even across different geographical locations. This level of data fluidity ensures that every healthcare provider involved in a patient’s care has access to the most up-to-date, comprehensive health information, leading to more informed decision-making and better patient outcomes.
Moreover, interoperable EHRs also facilitate better coordination and communication between healthcare
Experience the future of healthcare with cutting-edge technologies like telemedicine, AI-driven diagnostics, wearable devices, and interoperable EHRs. These innovations not only enhance patient outcomes but also alleviate stress for healthcare professionals by streamlining workflows and empowering personalised care" to add it in the blurb.
providers. They eliminate the need for redundant tests and procedures, saving time, and resources, and reducing patient discomfort. They also enable a more holistic view of the patient’s health, considering all aspects of their health history rather than isolated incidents or conditions.
Artificial Intelligence (AI) and automation are transforming the healthcare industry by automating routine tasks, thereby freeing up valuable time for healthcare professionals. This includes tasks such as scheduling appointments or refilling prescriptions, which, while necessary, can consume a significant portion of a healthcare professional’s day.
AI algorithms can handle these tasks efficiently and accurately. For instance, AI can analyse a patient’s medical history, predict when their medication will run out, and automatically send a refill request to the pharmacy. Similarly, AI can manage appointment scheduling by analysing appointment patterns, predicting cancellations, and optimising the schedule to reduce patient wait times and improve clinic efficiency.
The automation of these tasks not only saves time but also reduces the likelihood of errors. Manual processes are prone to human error, which can lead to mistakes such as double-booking appointments or prescribing the wrong medication. These errors can have serious
consequences for patient health and can also lead to legal issues for the healthcare provider. By automating these processes, AI significantly reduces the risk of such errors.
Furthermore, the reduction in errors and the freeing up of time have a positive impact on the stress levels of healthcare professionals. They can spend less time on administrative tasks and more time on patient care, which is both more fulfilling and leads to better patient outcomes. They also have peace of mind knowing that the risk of errors is reduced.
Virtual Reality (VR) is a transformative technology that is reshaping the landscape of healthcare training. VR allows healthcare professionals to practise procedures in a risk-free, simulated environment. This immersive technology provides a safe space for professionals to hone their skills, make mistakes, learn, and improve, all without any real-world consequences.
The use of VR for training purposes is particularly beneficial for complex, high-stakes procedures. In traditional training scenarios, the stress associated with performing these procedures can be overwhelming for healthcare professionals. However, VR allows them to practise these procedures repeatedly until they feel confident, thereby significantly reducing the stress associated with performing these procedures in real life.
Moreover, VR training can be tailored to the individual needs of each healthcare professional. It can simulate a wide range of scenarios, from routine procedures to rare, complex cases. This flexibility allows healthcare professionals to gain a broad range of experiences and be prepared for any situation they might encounter in their practise.
In addition to improving skills and reducing stress, VR training also has the potential to improve patient outcomes. Healthcare professionals who train using VR are likely to be better prepared and more confident, leading to more successful procedures and better patient care.
Virtual Reality (VR) stands out as a transformative force in healthcare education, offering a dynamic and immersive training environment. It enables medical professionals to refine their skills in a risk-free setting, mitigating the stress linked to complex medical procedures and paving the way for enhanced patient care. As VR technology advances, its influence on medical training is poised to expand, revolutionising traditional learning paradigms.
New technologies such as Electronic Health Records (EHRs), Artificial Intelligence (AI), automation, and Virtual Reality (VR) are significantly improving healthcare IT systems. They streamline processes, reduce errors, enhance patient care, and reduce stress levels for healthcare professionals. These technologies are transforming healthcare, making it more efficient, effective, and patient-centred.
Looking ahead, another promising technology that could revolutionise healthcare IT systems is quantum computing. Quantum computing holds immense potential in the field of drug discovery. Traditional drug discovery processes are time-consuming and costly, often taking years and billions of dollars to find a suitable drug candidate. Quantum computing could dramatically accelerate this process.
Quantum computers can process vast amounts of data and perform complex calculations at speeds far exceeding those of classical computers. This capability could be used to analyse biological molecules' vast and complex structures and predict how different drug molecules will interact with them.
Moreover, quantum computing could enable us to explore a much larger potential drug space in a shorter time. It could help identify promising drug candidates more quickly, speeding up drug discovery. This could lead to faster development of new treatments and cures, ultimately benefiting patients worldwide.
As we venture further into this era of technological marvels, the fusion of advanced technologies
promises a healthcare landscape that is not only more efficient and effective but also deeply personalised and patient-centric. This evolution holds profound promise for both healthcare professionals and patients, heralding a future where the boundaries of medical possibilities are continually expanding.
New technologies are playing a pivotal role in improving healthcare IT systems, and the advent of quantum computing could further accelerate this progress. As we continue to innovate and integrate these advanced technologies into healthcare, we can look forward to a future where healthcare is more efficient, effective, and personalised. The potential benefits for healthcare professionals and patients alike are immense and truly exciting.
Software Industry. Successfully blended technical skills, leadership, and entrepreneurial spirit to drive innovation and achieve business objectives. Recognised for developing innovative healthcare software solutions.
Although telemedicine is not new, it remains unfamiliar to many. In this article, the author provides an overview of new telemedicine tools and emerging technologies, highlighting their benefits and emphasizing that only through collaboration among the various stakeholders involved can its adoption be accelerated.
Jessica Masotino, Founder & CEO, JSMedtech
Telemedicine is a way to deliver healthcare services that leverages new technologies and devices to provide medical services remotely. This is possible thanks to the usage of new telecommunications tools, digital platforms, new devices and information technology, facilitating the diagnosis, treatment, and follow up of patients without the need for in-person visits or to complement them.
Despite Telemedicine is not a new concept, Covid 19 pandemic accelerated the transition to new models of remotely delivered healthcare. There was a boost of new technologies and services development, allowing new patients journeys creation and transforming the healthcare landscape with lasting consequences.
The Most Common Telemedicine Services are:
Video visit with patients through GDPR (Global Data Privacy Protection) compliant video calls systems to identify patients’ symptoms or prescribing/
adapting tailored therapies allowing patient to receive tailored medical support anywhere.
Teleconsultation
Healthcare providers can collaborate remotely anywhere in the world with their peers for complex cases diagnosis and management. This is particularly valuable when a multispecialty team approach is needed or in cases where higher expertise is needed.
Patients Remote Monitoring
Healthcare providers can monitor remotely patients using AI (artificial Intelligence) tools, or IoT (Internet of Things) Devices, new wearables, such as sensors detecting patients' vital signs, as blood pressure, heart rate, glucose levels, oxygen saturation, body weight and more, smart home devices. This real-time data helps in early diagnosis and in managing chronic conditions, such as diabetes, hypertension, and asthma. Moreover, the usage of Artificial Intelligence (AI) and machine learning to analyse big set of data is a great complement to physician work, providing new insights for patient diagnosis and personalised treatments, opening endless opportunity to clinical research with the final goal to improve patient care and outcome.
Remote Reporting
A doctor interprets and report medical imaging examinations from a location outside the clinic or hospital where the examination has been performed, thanks to the usage of digital platform.
Other less well known Telemedicine services are:
Telae-assistance/Telepresence Robots
Dedicated Totem or Robots are equipped with cameras, microphones, screens allowing healthcare professionals to remotely interact with patients real-time. Totem can be installed in in dedicated area, even outside the hospitals, allowing patients to communicate
Discover the transformative power of telemedicine in healthcare delivery! Explore how new technologies and digital platforms are revolutionizing patient care, enhancing accessibility, and driving personalized treatment plans.
users learning capabilities. For instance physicians can use AR for guidance during complex procedures, and VR is utilised for therapeutic interventions.
As technology continues to advance, telemedicine is expected to play a growing role in shaping the future of healthcare delivery.
Telemedicine is a more accessible, equitable, sustainable, personalised, humane, environmentally friendly medicine, and safer, reducing the exposure of contagious illness.
That thanks to telemedicine, even patients living in remote areas can access to healthcare services. Telemedicine allows for quicker access to medical professionals, reducing waiting times for appointments and diagnostics. This is especially valuable when time matters to treat patient and their outcome.
with doctors without going to the hospital. Telepresence mobile robot can navigate hospital corridors, patients rooms, deliver goods, interacting with patients, providing even more immersive experience compared to traditional video conferencing. Rehabilitation robot with telemedicine features can guide patients through personalised rehabilitation programmes, providing feedback on their movement and progress, remotely monitored by healthcare professionals, facilitating therapy adherence and optimisation.
A doctor assists other health care professionals at distance to perform a medical act using new technologies such as “smart glasses” or other innovative systems. The adoption of other new technologies in telemedicine such as Augmented Reality (AR) and Virtual Reality (VR) is driving more immersive experiences enhancing new
Enhancing healthcare accessibility everywhere and faster, Telemedicine removes geographical barriers and allows better patients outcome. Earlier diagnosis and treatment, improved adherence to treatment plans with the use of digital health applications in fact, may impact on patient morbidity and mortality reduction and improved health and well-being.
Telemedicine allows as well personalised medicine, incorporating genomic information, new diagnostic and monitoring tools to tailor treatment plans based on an individual's genetic makeup and records. This personalised medicine approach allows for more targeted and effective interventions.
Virtual consultation allows economic and time savings due to no need for travelling to the healthcare facility. Patients that benefit the most are individuals with mobility issues and their caregivers, often obliged to require time off from work to accompany them. Others are patients that lives in rural areas and chronic patients
requiring continuity of care or support from different healthcare professionals. Others are busy professionals or parents or in general for all individuals having difficulties in taking time off for medical appointments. It is not to be underestimated the positive impact of virtual consultation on diseases prevention and care for them. Telemedicine offers the flexibility to consult with healthcare providers at a time and place that is convenient for them. During Covid 19 pandemic we learnt as well that patients with infectious diseases could benefit of virtual consultation, reducing the spread of infectious diseases, minimising the need for in person visit, facilitating timely medical consultation.
It has been proven in several studies that Telemedicine can be cost-effective for both patients and healthcare providers. Patients save on transportation costs, parking fees, and potential time off from work. Healthcare providers can reduce overhead expenses associated with maintaining physical facilities, and remote consultations may streamline the appointment process, increasing overall efficiency.
The usage of Telae-proctoring improves the health care professional learning curve and provide confidence, accelerating the adoption of new technologies, being an extremely valuable complement to the in-person training. New tools and technologies available offers endless possibilities and immersive experience to train doctors on new devices and techniques. Artificial Intelligence Assistance and deep learning tools can analyse patient data, provide diagnostic recommendations, offering decision support to doctors for more and more accurate diagnostic and treatment. Modern and faster imaging transmission facilitate doctors communication even when in the operating room facilitating best practises sharing, remote training and removing geographical barriers. The usage of telemedicine and robotic technology brings new perspectives
for less invasive procedures, enabling remote or semi-autonomous surgical procedures allowing expert surgeons to deliver training, supporting trainees to operate in different geographic locations through high definition cameras and robotic arms.
Using Telepresence Robots redesign the patients journey enhancing a more efficient and effective healthcare delivery, especially in the light of healthcare professionals constrains and growing demand from patients. The integration of robotics into telemedicine opens new perspectives and holds new promise for improving access to healthcare.
One different and often overlooked benefit of Telemedicine is its positive impact on the environment.
In several studies and in recent systematic reviews1,2 the carbon emissions produced from the use of the telemedicine systems themselves were found to be very low in comparison to emissions saved from travel reductions.
Virtual consultations and remote monitoring impacts on carbon emissions and contributes to energy conservation and a more sustainable healthcare system.
Morevover, the usage of electronic recording systems in telemedicine and
its shift to a paperless system helps conserve forests, decrease water usage in paper production, and reduce the environmental impact associated with waste disposal.
Last but not least, Telemedicine, by promoting remote consultations and digital prescriptions, helps mitigate the generation of healthcare waste. This shift aligns with the principles of a circular economy, emphasising sustainability through reduced waste production and increased resource efficiency.
The adoption of telemedicine and the development of new technologies and devices presents an opportunity to revolutionise healthcare practises enhancing accessibility and efficiency. It improves patient care while simultaneously impacting positively the planet through carbon footprint reduction, leading a greener and more sustainable future. Healthcare providers, Payors, Industry, Patient Associations, Caregivers should work together to embrace telemedicine as a fundamental ally for the patient health and its well-being, the community and the environment, removing all barriers to adoption.
Jessica Masotino has over 25 years of international healthcare experience in leadership positions in Sales, Marketing and Medical Affairs in several medical devices and equipment businesses (Cardiac Surgery, Cardiology, Neurosurgery, Neurointerventional, Radiology, Drug Delivery, Spinal Surgery). She was Vice President for Marketing and Professional Education in EMEA and APAC for AtriCure, Global Marketing and Global Medical Affairs Director for LivaNova, she was Responsible for Marketing and Sales in Italy, Greece and Israel for Johnson & Johnson Medical. Jessica has a Bachelor in Economics and marketing and a master in Digital Marketing in Italy, a Medical Affairs Certification in USA.
The advent of Artificial Intelligence (AI) in the medical industry marks a pivotal shift in healthcare delivery, diagnosis, and patient care. AI technologies are transforming the landscape of the medical field, offering innovative solutions to age-old challenges, enhancing efficiency, and paving the way for more accurate, personalised care. This article explores the multifaceted impact of AI on global healthcare systems, including its applications in diagnostics, treatment planning, patient monitoring, and the development of new drugs, underscoring the significant potential and ongoing challenges of integrating AI into the medical industry.
Joalin Lim, MS, PhDc,CCRP, CEO, Agape-Life Medtech & Healthcare GroupThe integration of Artificial Intelligence (AI) into the medical industry is arguably one of the most significant advancements in healthcare technology in recent times. With its unparallelled ability to analyse large datasets, recognise patterns, and make predictions, AI is revolutionising how medical professionals diagnose diseases, develop treatment plans, and manage patient care. This digital transformation extends beyond the confines of traditional medical practises, offering hope for tackling complex health challenges with greater precision and efficiency.
AI's most notable impact in the medical industry is in diagnostics. Machine learning algorithms, a subset of AI, are trained on vast amounts of medical data, enabling them to recognise complex patterns associated with specific diseases. For instance, AI-driven diagnostic tools can analyse X-rays, MRIs, and CT scans with a level of accuracy that matches or even surpasses that of human radiologists. This capability not only speeds up the diagnostic process but also significantly reduces the margin of error, leading to better patient outcomes. The role of AI in diagnostic and treatment planning within Asia underscores a transformative shift towards more efficient, accurate, and accessible healthcare systems. In a continent characterised by vast disparities in healthcare infrastructure and access, AI emerges as a pivotal tool in bridging these gaps, offering solutions that are scalable across diverse healthcare settings, from urban hospitals to rural clinics.
AI's application in diagnostics has been ground-breaking, particularly in areas like radiology, pathology, and ophthalmology. Machine learning algorithms are now capable of analysing complex medical images with a precision that matches, or in some cases, surpasses human experts. This not only accelerates the diagnostic process but also enhances diagnostic accuracy, crucial for conditions where early detection significantly improves prognosis. Countries like China and India, with their large populations and high burden of diseases like cancer and diabetic retinopathy, have been at the forefront of adopting AI for these purposes, aiming to improve outcomes through earlier and more precise diagnoses. In treatment planning, AI's impact is equally profound. Through predictive analytics, AI systems can analyse vast datasets of
Artificial Intelligence is revolutionising healthcare by improving diagnostics, personalizing treatment plans, and enhancing patient monitoring. Its integration presents ethical considerations and challenges, yet promises more precise and efficient healthcare delivery worldwide.
patient information to forecast disease progression and response to various treatments. This enables personalised medicine, where treatments are tailored to the individual characteristics of each patient, improving the efficacy and reducing the side effects of treatments. In regions where certain diseases are prevalent, such as hepatitis in Southeast Asia, AI's ability to predict individual responses to treatments can significantly improve public health outcomes. Moreover, AI plays a crucial role in optimising healthcare resources in Asia, where the demand often outstrips supply. By automating routine tasks and aiding in decision-making, AI allows healthcare professionals to focus on more complex cases and patient care, improving service delivery and patient satisfaction.
Wearable technology and IoT (Internet of Things) devices are increasingly becoming integrated with AI to offer real-time patient monitoring outside traditional healthcare settings. These devices collect health data continuously, which AI systems analyse to detect anomalies that may indicate emerging health issues. This proactive approach enables timely interventions,
potentially preventing conditions from worsening. Furthermore, AI-powered chatbots and virtual health assistants provide 24/7 support to patients, answering questions, offering medication reminders, and even providing psychological support, thereby enhancing the overall quality of patient care. The integration of AI in patient monitoring and care in Asia is revolutionising the healthcare landscape, offering innovative solutions to enhance patient outcomes and healthcare efficiency. This region, with its dynamic blend of advanced and developing healthcare systems, is witnessing a rapid adoption of AI technologies, which are instrumental in overcoming challenges related to patient care and monitoring. AI-driven patient monitoring systems are becoming increasingly prevalent in Asia's hospitals and clinics, leveraging wearable devices and sensors to continuously collect and analyse patient health data in real time. These systems are capable of detecting abnormalities in vital signs, predicting potential health issues before they become severe, and enabling timely interventions. This is particularly beneficial in managing chronic conditions such as diabetes and hypertension, which require constant monitoring and have a high prevalence in Asian populations.
Moreover, AI technologies are enhancing patient care through personalised treatment plans and medication management, tailoring healthcare interventions to the individual needs of patients. By analysing patient data, AI can identify the most effective treatment strategies, predict patient responses to certain medications, and adjust dosages to optimise therapeutic outcomes. This level of personalisation not only improves patient health but also minimises the risk of adverse drug reactions, contributing to safer healthcare delivery. Telemedicine,
powered by AI, is another significant advancement in patient care within Asia. AI-enabled telemedicine platforms facilitate remote consultations, diagnosis, and treatment planning, making healthcare more accessible to rural and underserved populations. These platforms use AI algorithms to analyse patient symptoms, medical history, and even visual and auditory data, offering preliminary assessments that guide physicians in their decisionmaking processes. Furthermore, AI in healthcare extends to mental health support, with chatbots and virtual health assistants providing psychological counselling and monitoring mental well-being. These AI tools offer a level of convenience and anonymity that encourages more individuals to seek help for mental health issues.
Despite the exciting progress, the incorporation of AI in healthcare presents challenges. Data privacy and security are top priorities due to the sensitive nature of healthcare data. Ensuring the protection of patient information while utilising AI technologies is crucial to maintaining trust in healthcare systems. Moreover, ethical considerations around AI decision-making processes and the potential for bias in AI algorithms highlight the need for transparent, fair, and accountable AI systems in medical applications. The rapid advancement and application of Artificial Intelligence (AI) in Asia bring forth a unique set of ethical considerations and challenges. As AI becomes increasingly integrated into various sectors including healthcare, finance, and governance, the need for a robust ethical framework to guide its development and deployment is more critical than ever. These challenges are exacerbated by Asia's diverse cultural, social, and economic landscapes, which influence
the perception and implementation of AI technologies. One of the foremost ethical considerations is data privacy and security. With vast amounts of personal and sensitive data being processed by AI systems, there is a heightened risk of breaches and misuse. Countries across Asia are at different stages of developing and enforcing data protection laws, leading to inconsistencies that could potentially harm individuals' privacy rights. Bias and fairness in AI algorithms pose another significant challenge. AI systems are only as unbiased as the data they are trained on, and if this data reflects societal inequalities, the AI's decisions will too. This is particularly concerning in diverse societies found in Asia, where biased AI could exacerbate existing social inequalities or discrimination against minority groups. Moreover, the lack of transparency and explainability in AI decision-making processes raises accountability issues. In sectors like healthcare and criminal justice, where AI's decisions can have profound impacts on individuals' lives, understanding how these decisions are made is crucial for trust and ethical responsibility.
To address these challenges, there is a growing call for ethical AI governance frameworks in Asia that consider the region's cultural diversity and ethical values. Such frameworks should promote the responsible development and use of AI, ensuring that technologies are developed and deployed in a manner that
is transparent, fair, and respects privacy and human rights. Engaging diverse stakeholders, including governments, industry leaders, ethicists, and the public, in the conversation around AI ethics is vital for fostering an inclusive approach to AI governance that benefits all members of society.
The integration of Artificial Intelligence into the medical industry represents a monumental leap forward in healthcare. From revolutionisng diagnostics and treatment planning to enhancing patient care and accelerating drug development, AI's potential to improve health outcomes is immense. However, realising this potential requires careful navigation of ethical, technical, and regulatory challenges. As we move forward, it is imperative that the medical community, technology developers, and policymakers work collaboratively to ensure that AI technologies are implemented in a manner that is safe, effective, and equitable. The AI revolution in the medical industry is not just about technological advancement; it's about shaping a future where healthcare is more accessible, personalised, and effective for everyone.
Joalin Lim has over 25 years of extensive experience in R&D, Regulatory-Quality, Clinical, EBM Marketing, Reimbursement and Medical Affairs; leading operational teams in Asia and globally.
Currently, she is the Founder & Group CEO at Agape-Life MedTech & Healthcare Group. Through her senior management roles in these departments, she has successfully supported the launch of over 30 MedTech & IVD products from concept inception to commercialization into Asia & US/EU markets. She has published above 50 medical white papers and taken part in over 80 oral presentations at conferences, as well as written medical journal articles.
Artificial Intelligence is undergoing a transformation, as AI technologies can now generate content (documents, images, movies etc) that can be indistinguishable from content generated by human experts. Such AI technologies can generate output that is highly plausible, but may not be accurate or real. This has raised many concerns about how AI should be regulated. For many applications of AI in healthcare, however, regulations already exist. Where an AI device is used to prevent, diagnose, or treat a disease, it is covered by the medical device regulations require not just that the output is “plausible” but that the device benefits are demonstrated to outweigh risks, and that residual risks are well managed in clinical use. The medical device regulatory framework is already being updated to take account of AI and provides useful framework to ensure that AI entering healthcare with appropriate controls in place.
Derek Hill, CEO, Panoramic Digital Health, Professor of Digital Health, UCL
Artificiel Intelligence becomes Mainstream.
The last 18 months have seen a dramatic increase in public interest in artificial intelligence (AI). There has been a huge amount of coverage in the media about recent developments in artificial intelligence – especially generative AI such as the large language models used
in the Chat-GPT software. Many argue that AI algorithms can now generate output that is indistinguishable from human-expert created content, and is therefore poised to transform all our lives, for the better or worse.
Just a few years ago, there was debate about whether or not to regulate artificial intelligence – and much criticism was directed at the European Union proposing the first regulatory framework for AI (the AI act) in April 2021, on the grounds that this could stifle innovation. But in the last 12 months, as a result of rapid technological process and raising public awareness, the debate has shifted from whether to regulate AI, to how to regulate AI. There are increasing concerns that, unless properly regulated, AI could soon start having negative
impacts on our quality of life. In late 2023, many world leaders responded to recent developments in AI, for example President Biden’s executive order on AI, and an AI Safety Summit in Bletchley Park hosted by UK Prime minister Rishi Sunak, attended by many business and political leaders.
Within the healthcare world, it is increasingly argued that AI will transform the healthcare system for patients and staff, including a widely reported publication that showed that generative AI can create such smart answers to questions that it can pass 3rd year medical exams, suggesting AI could disrupt patient-physician relations.
It is important to realise, however many applications of AI in healthcare are already regulated. If AI is used in software that is intended to diagnose, prevent, manage, treat or alleviate a disease or injury, then it is already regulated as a medical device. I have recently published a paper on the evolving regulatory landscape for AI in medical devices. That paper focuses on medical imaging applications, but the conclusions are more generally applicable, and below I summarise some of the key issues from that paper.
The medical device regulators have been regulating software, whether this is stand-alone (Software as a Medical Device – SaMD), or integrated into hardware (Software in a Medical Device – SiMD) for decades and have been considering the implications of AI for many years. A guidance document proposing an international harmonised approach to clinical evaluation of medical device software was proposed in 2017 by the International Medical Device Regulators Forum, and machine learning algorithms (a type of AI) was discussed in this document. More recently, medical regulators have been publishing more dedicated discussion documents specifically related to use of AI in medical devices, and there are new
global standards that describe how risks in AI should be managed.
Many hundreds of AI-enabled products have already been put on the market as medical devices. The US FDA, which has the most comprehensive publicly available medical device database, regularly publishes the number of AI-enabled medical devices that have received marketing authorisations (510k, dae novo or PMA). In October 2023, the FDA published the list of nearly 700 devices that have received marketing authorisations. either pure software devices, or AI enabled hardware.
It is notable in this FDA list that the overwhelming majority of AI-enabled medical devices on the market are for applications in radiology, with cardiology (eg: ECG arrhythmia detection) second largest.
Medical imaging applications tend to dominate AI-enabled medical devices marketing authorisations because it is relatively easy to bring these onto the market. That is because most AI-enabled medical imaging devices don’t actually collect data from patients themselves – they analyse data collected from traditional medical imaging systems such as radiographs, CT scans, MRI, ultrasound etc. As a result, the AI models in these devices can be trained and validated on pre-existing data: there is no need to prospectively recruit patients for a clinical investigation to demonstrate the device has adequate performance. Similarly, many AI enabled cardiology devices are coming onto the market, both trained and validated on pre-existing ECG data, rather than needing longer and more expensive prospective studies.
Furthermore, many innovators in AI are also able to take advantage of large, publicly available databases on which they can train and validate their algorithms. Examples include the Alzheimer’s Disease Neuroimaging Initiative, and the UK Biobank data. These shared databases can dramatically accelerate the time needed to develop an AI-enabled device for applications
that can be trained and validated on pre-existing data.
There has been a lot of excitement about generative AI because it can generate very plausible answers to complicated questions or generate “deep fake” images and videos that are indistinguishable from the real thing. There is no-doubt that recent innovations in AI have resulted in such “plausible” output, and that it is increasingly difficult to distinguish AI generated content from human-generated content.
In the world of medical devices, however, the output of devices needs to have well characterised performance that gives a positive benefit:risk profile. The output of a medical device doesn’t just need to be “plausible”. Medical device regulators insist that performance of devices is assessed rigorously against industry standard, or using well established statistical metrics like sensitivity and specificity, accuracy etc. A core part of medical device development is a detailed analysis of risks, identifying how harm might arise to patients, the hazards that might lead to that harm, and putting in place mitigation for significant risks. Furthermore, medical device regulations require that the performance of medical devices is not only assessed before they are put on the market, but that performance and safety monitoring continues during clinical use.
While there is evidence that some AI enabled medical imaging devices can work as well or better than normal clinical practise, there is also evidence that real world performance of AI enabled devices can be substantially less good than their advertised performance.
The COVID pandemic also was associated with much innovation in AI algorithms, but a systematic review of these in the British Medical Journal found that the great majority appeared to have very limited clinical value.
AI algorithms are not written by programmers like traditional rule-based algorithms, but rather they learn how to generate their output using a process called “training”. The performance of the AI algorithms is then “tested”, a process often called validation. A major challenge in the development of AI-enabled medical devices is that the performance of AI medical devices is highly dependant on having well labelled training and test data. For example, to automatically identify a stroke from a CT scan, the AI model needs to be trained on lots of data that is known to have strokes, as well as data without strokes, so the AI algorithm can distinguish the two cases. For this to work well, the images need to be precisely labelled with the location of the stroke, which is a time consuming process. While hospitals have huge amounts of healthcare data, obtaining sufficient high quality labelled data from representative patient populations is very often a significant challenge. As a result, many AI-enabled devices have been trained on publicly available data such as ADNI or UK biobank, which has been criticised for being unrepresentative of true clinical populations. When an AI-enabled medical device is trained and tested on unrepr¬¬esentative data, it is likely to perform much less well when subsequently applied “real world” clinical conditions. The data used needs to be representative of patient population (demographics, co-morbidities etc) but also data source (eg: type of scanner or electrophysiology device), and clinical practise (eg: how patients are positioned in a scanner, positioning of electrodes in ECG or EEG). When data used for training and/or testing is not representative, it is described as “biased”.
Medical device regulators are aware of these issues, and have therefore been proactive in providing innovators and manufacturers with further guidance on how to develop and evaluate AI enabled medical devices. This is especially case with the US medical
device regulator, FDA Centre for Devices and Radiological Health (CDRH).
Regulators are responding to some of the challenges in this field by requiring that AI enabled medical devices have more rigorous clinical evaluation than medical devices containing traditional rules-based algorithms. A recent standard proposed by the AAMI and BSI (BS/AAMI 34971:2023), now recognised as a consensus standard by the FDA, starts with a cautionary note:
Despite the sophistication and complicated methodologies employed, machine learning systems can introduce risks to safety by learning incorrectly, making wrong inferences, and then recommending or initiating actions that, instead of better outcomes, can lead to harm.
The amplification of errors in an AI system has the potential to create large scale harm to patients.
Regulators are now encouraging companies developing AI enabled medical devices to consider the particular risks arising from AI, including risks of bias from unrepresentative training data and test data.
Regulation always involves a tradeoff between ensuring safety and enabling innovation, and striking the wrong balance can either prevent effective new technology getting to patients, or result in a flood of unsafe devices entering clinical practise.
But a clear regulatory framework can also support innovation by providing clarity on the evidence needed in order to demonstrate that a medical device is safe and effective, and giving healthcare providers confidence that devices that have been cleared or approved by regulators have been properly evaluated, speeding up adoption.
As several systematic reviews have shown, the quality of the rapidly rising volume of academic publications in medical applications of AI is highly variable. Recent regulatory guidance documents should encourage good practise – such as training and testing
algorithms on representative data, validating algorithms on a dataset that is independent on the data used for training, that the clinical application of the technology is properly considered, that any upgrade of the devices while in clinical use is carefully managed, and that there is appropriate human oversight.
An examination of the published information about AI-enabled medical devices that have been put on the market in the US suggests that the great majority of these devices are unlikely to have significant impact on clinical workflows or professional practise. That is because the indications for use of these devices, tend to emphasise that they need to be used under the supervision of clinical experts, with statements such as: “not intended to be used as a primary diagnostic device”, “notified clinicians are ultimately responsible for reviewing full images per the standard of care”, and to be used “in parallel with standard of care”.
These indications for use are caveated in this way, because manufacturers have not managed to generate adequate performance data to show that these AI-enabled devices can operate independently of normal clinical pathways, or without clinical supervision. Medical device regulators therefore insist that manufacturer mitigate the risk that performance is inadequate by caveating the way they can be used in the device labelling.
Current AI-enabled medical devices are therefore unlikely to prove disruptive in healthcare. But with the huge increase in investment into AI, by small and large companies alike, it is very likely that disruptive technologies will come onto the market.
Artificial intelligence technologies are undergoing rapid development, and attracting huge amounts of
investment. Ever increasing numbers of AI-enabled devices are coming on the market. However, the requirement imposed by medical device regulators that manufacturers carefully assess performance of devices before they put them on the market means that the impact of current AI-enabled devices is likely to be more incremental than disruptive to healthcare systems in the near future.
Regulators have been careful to insist that risks of AI are mitigated in devices put on the market, and they are being proactive in providing manufacturers with updated guidance as the risks (as well as benefits) of AI in healthcare applications emerges. While the need for more rigorous assessment of AI-enabled devices that traditional software devices does slow down AI reaching the market, it is reassuring given that evidence shows that AI algorithms are particularly at risk of performing less well in a real world setting than they did during testing. These evolving regulatory frameworks should mean that, as more sophisticated AI driven technologies are developed, the testing and clinical implementation of these is done in a way that ensures human oversight and rigorous and on-going testing in realistic clinical conditions.
Derek Hill is professor of Digital Health and Director of Enterprise at UCL, London. He has experience interacting with global medicines and medical device regulators in applications of medical imaging and digital health technologies, including technologies incorporating AI. He is also CEO of Panoramic Digital Health.
Amidst rising healthcare costs and inflation in Singapore, leveraging virtual health innovations is critical. This strategic shift enhances access to care, curtails medical expenses, and boosts patient outcomes, demonstrating how digital health solutions can transform and optimise a rapidly evolving healthcare landscape.
Raymond Ng, CEO & Country Manager, Cigna Healthcare SingaporeIn the face of inflationary pressure and an unprecedented demand for health services, Singapore's healthcare costs have surged dramatically. This escalation is pressing the government and healthcare industry to innovate and rethink the traditional approaches to medical care, setting the stage for transformative changes in how health services are delivered and accessed.
In Singapore, government spending on healthcare between 2012 and 2022 tripled from about S$3 billion to S$10 billion, and is projected to hit S$27 billion in 20301. At the same time, while
1 https://file.go.gov.sg/healthiersg-whitepaper-pdf.pdf
Singapore has one of the most advanced healthcare systems in the world, certain demographics, including the elderly and those with mobility limitations, still encounter significant challenges in accessing and affording quality healthcare services.
These challenges are further compounded by the country’s ageing population and additional manpower needed to operate medical facilities that are being built to meet demand for healthcare services. It is widely accepted that the industry and its consumers need to embrace rapid innovation to address these issues.
One such innovation that has seen widespread adoption and application is virtual health, which has the potential to improve access to healthcare, reduce healthcare costs and improve overall patient outcomes.
Virtual health extends well beyond the confines of telehealth – it encompasses a much wider spectrum of clinical practises, including remote patient monitoring, imaging and diagnostics, virtual triage and hospital management, patient data management, and the integration of AI, such as in the use of virtual assistants.
The pandemic and its resultant lockdowns popularised virtual healthcare, with usage skyrocketing during that period. Between 2021 and 2023, about four in 10 respondents in a study we conducted on the usage of virtual health in Singapore had consulted a doctor over the phone or virtually, and the same proportion rated these virtual consultations as comparable to in-person consultations in terms of ease of arrangement, feeling listened to and understood, as well as follow-up care.
In addition, 86% of those who have used virtual health said that they would recommend, or have recommended using it, and 88% said that they would use, or have used it, again.
Having recognised the shift towards digital solutions, major healthcare providers in Singapore now offer teleconsultation services as more patients are becoming familiar and comfortable with this mode of seeking medical advice.
In response to this growing trend, the Ministry of Health has rolled out a Voluntary Listing of Direct Telemedicine Service Providers, which helps patients make informed decisions on service providers and offers guidelines on how to prepare for and what to expect from teleconsultations.
Amid rising costs of living – Singapore recently increased its Goods and Services Tax to 9% – and ongoing inflation, many Singaporeans are turning to more convenient and accessible healthcare options. Virtual healthcare, with its promise of lower costs and enhanced convenience, is ideally positioned to meet these evolving medical needs.
Transitioning the consultation process to a virtual platform significantly enhances healthcare access by eliminating concerns about the time, distance, and costs associated with traditional visits. Patients facing mobility or scheduling challenges can now access specialists at distant clinics and hospitals through teleconsultations, bypassing lengthy travel and waiting times while avoiding administrative and transport costs.
With its ageing population, Singapore also faces an increasing incidence of chronic diseases, such as diabetes, hyperlipidaemia, and hypertension – conditions that research shows become more prevalent with age and often require ongoing monitoring and regular cheque-ups, which can be both time-consuming and costly.
These challenges can be mitigated by utilising data collected from wearable devices issued to patients, offering a simpler way for medical professionals
to monitor patients remotely, thus reducing the necessity for patients to travel for short appointments.
Moreover, the continuous flow of patient data from wearables enables healthcare providers to detect health issues early, enhancing the likelihood of timely medical interventions. This proactive approach not only improves patient outcomes but also leads to significant cost savings by reducing the need for more complex treatments.
Healthcare providers also see significant benefits from the shift to virtual health services, notably through reduced administrative costs incurred for in-person registrations and data entries. This reduction in overhead allows healthcare professionals to allocate more resources and capital towards working more efficiently and focus on providing quality healthcare to their patients.
The expanded reach also benefits healthcare providers in the same manner as it does patients – specialists are now able to reach patients that might reside outside of their immediate vicinity with ease, while simultaneously allowing patients who live further away to access the specialist treatments they need.
Furthermore, virtual solutions and the digital platforms they provide allow for easier and more frequent followups with patients, especially those with chronic diseases. This increased engagement, which may include scheduling follow-up appointments and regular cheque-ins, leads to improved patient outcomes through proactive monitoring and management of health conditions. Digital platforms also enable healthcare providers to educate patients on preventative care measures and how to spot symptoms before they worsen, ultimately improving overall patient health.
While virtual healthcare offers numerous benefits, barriers to adoption
remain among certain demographics. As a relatively new phenomenon in Singapore, the availability of online healthcare services may not be immediately known to all, particularly among the older generation who may not be as technologically savvy, and tend to rely on word-of-mouth rather than online information for healthcare recommendations.
Without education or explainers on how patients can best utilise such services, what conditions are more suited to being addressed by teleconsultations, how to self-monitor, and how to schedule follow-up appointments, this lack of awareness can result in overall reluctance to use these new services.
Many patients who are accustomed to in-person consultations may be resistant to the idaea of shifting consultations online, feeling that it is too impersonal for them. This sentiment is particularly strong among those exhibiting symptoms that traditionally require physical examinations, such as listening to a patient’s heart or lungs, which cannot be conducted virtually without the help of appropriate equipment and technology. In fact, our research indicates that almost 7 in 10 respondents in Singapore still prefer traditional methods when it comes to specialist engagements.
Similarly, healthcare providers entrenched in the traditional delivery of their services might also resist adopting new technologies or integrating them into their existing systems. Training staff and familiarising them with new technologies requires additional time and resources, which can temporarily affect service efficiency.
On top of that, the sensitivity of personal health information adds another layer of complexity. With patient health data stored online and cybersecurity incidents on the rise all over the world, some individuals may be wary of potential data breaches. For those on the fence about utilising
digital services, the possibility of a data breach may deter them from doing so even further despite increasing investments in cybersecurity and data privacy in the nation in recent years.
Virtual health has established itself as a crucial and potentially life-saving innovation that improves operational efficiency for providers, while also enhancing access and affordability for patients – two fundamental elements in the push to achieve healthcare equity. Its rapid rise in popularity during the pandemic has also quickly proven to providers and patients alike that digital platforms can be quickly adopted and scaled to fit healthcare institutions of all sizes, from the smallest clinics to the national hospitals.
As patient needs continue to evolve, the next logical step in virtual
health is the provision of coordinated care to ensure that patients seeking help through such platforms receive comprehensive care without the need to supplement it with in-person visits, as much as possible.
By integrating patient monitoring and data interoperability, virtual health allows for the effective management of chronic conditions outside of hospital settings, thereby alleviating pressure on healthcare systems.
The onus is on healthcare service providers to build trust and optimise the care experience. Achieving this requires a deep understanding of patient needs and addressing barriers to adoption, in addition to investing in dedicated training for medical professionals who manage patient care through virtual channels is essential for enhancing patient trust and satisfaction.
Ng
& Country
Healthcare Singapore & Australia. A leader and a business innovator with more than 15 years in the insurance and health services industry. Raymond has dedicated his career to paving the way for sustainable quality healthcare that is centred around patient outcomes.
APAC’s diverse markets suffer from a chronic and escalating healthcare demand burden. These secular pressures overwhelm a constrained supply of medical professionals, with the pandemic highlighting the fragility of this imbalance. The silver lining is that APAC has become an incubator for global innovation in eHealth as traditional payer-providers recognize the need to escalate change.
Alex Boulton, Southeast Asia Head of Healthcare & Life Sciences Practice at Bain & Company1.How would you describe the current state of the eHealth industry? What major trends or developments have you observed recently?
Sink or swim time for eHealth startups. A significant portion of eHealth business models in APAC have started off by focusing on the customer and building a better value proposition compared to their traditional alternatives. While this led to enhanced customer experience and engagement, it is accompanied by a costly cash burn which, at the time, venture investors were willing to fund. That environment of capital abundance has changed and there is a concerted focus on the ‘path to profitability’ and supporting business model innovation. eHealth players in the region have pivoted quickly towards B2B models, with several moving into insurer services (e.g., TPA) and offline care provision. Startups that survive will need a clear path to profitability underpinned by a sustainable business model.
An ‘awakening’ of Traditional healthcare companies. The pandemic was a crucible for ‘offline’ stakeholders in the APAC healthcare markets. Notoriously traditional and slow-moving provider groups experienced extreme stress and were forced to ‘rethink’ the way care is and should be provided. After almost 3 years of fire-fighting and bootstrap innovation, both providers and payers are making concerted efforts to digitally transform. Consequently, we’ve seen a flurry of provider-led apps and technology capex investment. While starting from behind, these solutions will have a head start on delivering omnichannel experiences given existing infrastructure.
2.Can you highlight some of the most impactful technological advancements that are driving innovation in eHealth solutions?
Most recently, it’s been the telephone. I don’t mean to belittle all the great eHealth innovation that has come to market, including remote patient monitoring, clinical decision-making support and so on. The point here is that the technology to support eHealth has been around for a long time and, instead, it’s the openness of traditional providers to adopt these technologies ‘at scale’ that is changing. NHS 111 (UK), for example, is a free number to call when you have an urgent healthcare need that is not a life-threatening situation, and it has been around for over a decade. Virtual care is not new, it is just finally becoming the norm. Going forward, AI will change everything. A few years ago, we were expecting that automation and AI would allow clinicians to spend more time with patients and enable them to make better decisions. Fast forward to today and we have AI medical chatbots that are passing medical licensing exams. In an environment where medical
professionals are scarce, and demand is relentless with escalating costs, we will need to fundamentally rethink the way that healthcare is delivered and the role of technology.
3. Telemedicine has seen significant growth, especially in light of recent global events. How do you see this trend evolving, and what challenges does it present for the eHealth sector?
Telemedicine is here to stay. Telemedicine adoption increased dramatically through the pandemic and recent data on active users from the region’s top digital health apps has shown that the telehealth usage is persisting with a wide range of sustainable use cases. Across the region, hospitals that stood up telemedicine capabilities through the pandemic are doubling down on their technology investments; both internal systems and patient facing applications. eHealth players need to build trust. Trust is essential to any productive patient relationship with their healthcare provider and is something that
has historically been built (slowly) upon tangible assets like the credentials of the physician, the long-standing hospital infrastructure, or even the referral of a close family member or friend. Customer surveys from our ‘Frontline of Healthcare in APAC Report’ reported a significant increase in consumer trust in eHealth companies from 2019 to 2021 in several APAC markets, including China, Indonesia and Singapore. Furthermore, several eHealth startups in APAC are actively making the transition from a ‘digital health co’ towards a ‘healthcare co’, with a much broader mandate for a given patient’s health.
4. How are eHealth solutions enhancing patient engagement and improving overall healthcare experiences?
Expand accessibility. Digital delivery models have a distinct advantage over physical locations and providers and can help alleviate healthcare disparity. For example, access to healthcare is uneven across Indonesia. Metropolitan regions have almost five times the number of physicians as remote areas and patients residing in cities are often deterred by traffic and long waiting times. eHealth
platforms in Indonesia have enabled patients to manage appointments, prescription delivery, lab testing, consultations, and other services through a single point of contact.
5. Can you discuss the significance of partnerships in advancing digital health initiatives?
Aligned incentives. eHealth flourishes in an environment where incentives are aligned between payers and providers. Fully integrated payer-provider systems in the US and UK, for example, had been investing heavily in eHealth well before the pandemic forced their hands. Conversely, we see resistance to eHealth when hospitals fear the cannibalization of physical visits in favor of cheaper virtual consults, or insurers that fear higher utilization with easy to access eHealth services. These ‘conflicts’ disappear when each stakeholder is fully aligned to managing outcomes, experience, and costs. Payer-providerdigital health partnerships will play an important role in aligning these incentives and allowing digital health to thrive.
6. What do you envision as the future of eHealth?
Single (digital) point of care. More than 90% of surveyed consumers in Southeast Asia consumers want a simpler system of care—a single touchpoint to manage all their healthcare needs. That need is being fulfilled differently across the region. Digitally native companies are racing to provide this in markets like Indonesia, where primary care is limited, emboldened by the fact that one-third of survey respondents prefer that the ‘single touchpoint’ be virtual (an app or a hotline). The question to ask is which stakeholder within each healthcare system will win the right to lead this single point of care. Insurers
eHealth platforms offer a lifeline, streamlining services for patients amidst regional disparities.
The pandemic accelerated telemedicine adoption, revealing its sustained usage and diverse applications. Hospitals are amplifying investments in digital health technology, recognizing its capacity to address healthcare inequalities. This shift towards patient-centric care, underscored by tech-enablement, marks a transformative era in healthcare.
may have control over spend, but to what extent are they trusted to guide healthcare pathways today? Which population segments might be open to that ‘single point of care’ role being managed by an eHealth company?
Care everywhere. The notion of hospitals as de facto healthcare providers is slowly fading away. The industry is rapidly moving toward delivery models that are more convenient for consumers and less expensive to deliver, and care is moving outside hospital walls. A simpler pathway to
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care can increase population health overall. eHealth will play an important role in enabling the ‘last mile’ delivery of healthcare services into the home or mobile phone.
Seamlessly connected O2O care. Digital healthcare isn’t replacing established systems; rather, it’s enabling more connected, hybrid experiences. Integrated offline-to-online models have the potential to deliver better patient experience while optimizing cost and efficiencies for care providers. We expect to see unhindered flow of information between healthcare companies’ online and offline delivery models and along the care continuum. Patients will also be guided toward the right delivery model as telehealth develops.
Lastly, a transformation of traditional healthcare providers. The public health crisis forced traditional healthcare providers to accelerate innovation plans and deliver care in new, patient-centric ways. Patients have always been important. That did not—and will not—change. But now, healthcare companies are beginning to understand what’s important to patients. The future of healthcare will be characterized by a transformation of this traditional healthcare sector with patient-centricity and tech-enablement emerging as new norms.
Alex Boulton is a member of Bain & Company’s Private Equity and Healthcare & Life Sciences practices. He leads Bain’s Healthcare and Life Sciences practice for Southeast Asia and, since joining the firm in 2010, Alex has led numerous strategy and transformation programs with healthcare companies across the region and value chain; covering payers, providers, pharma, MedTech and digital health. In addition, he leads the Healthcare sector for our APAC private equity practice, supporting healthcare commercial due-diligence, portfolio and fund strategy engagements. He holds a BSc in Economics, with First-Class Honours, from the London School of Economics and Political Science.
Cancer, a complex disease marked by uncontrolled cell growth, poses a significant global health challenge. With over 100 different types, its multifactorial nature complicates both prevention and treatment. Genetic mutations, environmental factors, and lifestyle choices contribute to its rise. Early detection remains pivotal for successful intervention, yet many cases are diagnosed in advanced stages. Current therapeutic approaches, including surgery, chemotherapy, and immunotherapy, aim to target cancer cells while minimising harm to healthy tissues. Research continues to explore novel treatments, personalised medicine, integrative cancer care and breakthroughs in understanding cancer's underlying mechanisms to improve outcomes and quality of life for patients.
Samara Mahindra, Founder and CEO of Carer1. Can you share your journey and how you became involved in the field of integrative oncology?
My journey into integrative oncology began with a personal experience that changed my perspective on cancer care. Watching a loved one navigate the difficult path of cancer treatment, I was profoundly affected by the stark challenges of conventional approaches and their impact on quality of life. This fuelled a passion in me to seek out and advocate for more holistic yet effective methods of supporting individuals battling cancer.
2. What inspired you to found Carer, and what are its key objectives in transforming cancer care?
The inspiration behind founding Carer stemmed from a deeply personal encounter with the limitations of conventional cancer treatment, witnessed through the experience of a loved one. This journey showcased the
critical need for a more holistic approach to cancer care—one that not only targets the disease but also nurtures the overall well-being of the patient.
Carer was conceived with the vision to bridge this gap, offering comprehensive support that encompasses nutritional guidance, physical rehabilitation, mental health support, and financial counselling. Our key objectives are:
1. To enhance the quality of life for
cancer patients, ensuring they receive care that addresses both their physical and emotional needs.
2. To improve treatment adherence and outcomes by integrating supportive care that complement traditional medical treatments.
3. To democratise access to integrative oncology services, making them available to patients across various socio-economic backgrounds and geographical locations.
Ultimately, Carer seeks to transform cancer care into a more patient-centric, holistic journey, ensuring that every individual facing this challenging path is supported, empowered, and cared for every step of the way.
Samara Mahindra, founder and CEO of Carer, boasts 10+ years as an Integrative Oncology Specialist.
Accredited as a Senior Cancer Exercise Specialist, she's trained 100+ patients in physical therapy. Her expertise spans plant-based nutrition, mental well-being for cancer, and collaborations with renowned oncologists globally. Recognized for innovation, Samara's impact on Indian healthcare earned her a spot among the "25 Most Influential Women in Healthcare." Her podcast, "Healing Cancer the Right Way," ranks among India's top 20 science podcasts. A TEDx speaker, she pioneered evidence-based integrative oncology solutions, advancing cancer care quality.
3. How do you see personalised medicine impacting the future of cancer treatment?
Personalised medicine is set to revolutionise cancer treatment by focusing on tailored approaches that consider the unique genetic makeup of each patient. This patient-centric methodology not only promises better treatment outcomes but also a more holistic approach to healthcare. By integrating detailed genetic insights, treatments can be customised to target specific cancer cells, reducing side effects and improving efficacy.
Moreover, personalised medicine fosters a collaborative treatment process, actively involving patients and their families in decision-making. This inclusivity ensures that treatment plans resonate more deeply with the patient’s lifestyle, preferences, and concerns, enhancing adherence and satisfaction. In essence, personalised medicine heralds a future where cancer care is not just about battling the disease but about nurturing the patient’s overall well-being and dignity.
4. Can you discuss some cutting-edge technologies or therapies that are revolutionising cancer care?
Cancer care is witnessing a remarkable transformation thanks to cutting-edge technologies and therapies. Artificial Intelligence is at the forefront, improving diagnostic accuracy, predicting patient outcomes, and personalising treatment plans by analysing vast datasets. Precision medicine is another gamechanger, tailoring treatments based on genetic, environmental, and lifestyle factors to maximise effectiveness and minimise side effects.
Furthermore, the exploration of the microbiome presents exciting possibilities. Research into how the body's microbial communities affect cancer progression and treatment response is leading to innovative therapeutic strategies, including microbiome modulation to enhance the efficacy of immunotherapies.
These advancements collectively represent a shift towards more personalized, effective, and patient-centred cancer care, promising improved outcomes and quality of life for patients.
5. What role do you believe artificial intelligence and machine learning will play in advancing cancer research and treatment?
Artificial intelligence and machine learning are set to play transformative roles in advancing cancer research and treatment. These technologies enhance our ability to analyse complex biological data, leading to breakthroughs in understanding cancer's mechanisms. In treatment, AI and ML are improving diagnostic precision, optimising treatment plans, and predicting patient outcomes with greater accuracy. They're also pivotal in drug discovery, significantly reducing the time and cost to bring new therapies to market. By integrating AI and ML into oncology, we're moving towards more personalised, effective, and efficient cancer care, promising a future where treatments are tailored to the individual needs and genetic profiles of patients.
6. What are the biggest challenges currently faced in cancer care, especially in the Asian healthcare landscape?
In the Asian healthcare landscape, several significant challenges are impacting cancer care delivery and outcomes. High treatment costs emerge as a paramount concern, making advanced therapies and drugs less accessible to a broad segment of the population. This financial burden often results in patients forgoing necessary treatments or exhausting their resources.
Lack of accessibility to high-quality care is another critical issue, especially in rural or underserved areas. There's a marked disparity in the availability of specialised cancer treatment facilities, which are predominantly located in urban centres, leaving those in remote regions with limited options.
Furthermore, integrative cancer care therapies, which encompass a holistic approach including nutritional, psychological, and physical support alongside conventional treatments, are yet to become mainstream within the region. Despite growing evidence supporting their benefits in improving patient outcomes and quality of life, these therapies are not widely adopted across Asian healthcare systems due to a lack of awareness and insufficient integration into standard care protocols. Addressing these challenges requires concerted efforts across healthcare policy, insurance reform, and public awareness campaigns to improve affordability, access, and acceptance of comprehensive cancer care solutions.
7. How can healthcare systems address disparities in access to innovative cancer treatments, particularly in lower-income regions?
To address disparities in access to innovative cancer treatments in lowerincome regions, healthcare systems can adopt a multi-faceted approach. First, implementing public-private partnerships can mobilise resources to subsidise the cost of cuttingedge treatments, making them more accessible to underserved populations. Additionally, investing in telehealth and mobile health initiatives can extend the reach of specialised care to remote areas, breaking down geographical barriers.
Healthcare systems can also focus on capacity building by training health-
care professionals in lower-income regions on the latest cancer care protocols, ensuring that patients everywhere have access to knowledgeable practitioners. Lastly, fostering collaborations between governments, NGOs, and pharmaceutical companies can lead to the development of affordable generic versions of expensive drugs, further enhancing accessibility.
By prioritising equity and innovation, healthcare systems can make significant strides toward ensuring that all patients, regardless of their economic status or location, have access to the cancer treatments they need.
8. Could you elaborate on the concept of integrative oncology and its benefits for cancer patients?
Integrative oncology is a patient-centred approach to cancer care that combines standard medical treatments like surgery, radiation, and chemotherapy with complementary therapies. These may include nutritional counselling, physical exercise, and mental health support aiming to support the patient's overall well-being, manage side effects, and enhance the efficacy of conventional treatments.
The benefits of integrative oncology for cancer patients are manifold. It addresses not just the physical aspects of the disease but also the emotional, social, and spiritual challenges that accompany a cancer diagnosis. By doing so, it can significantly improve patients' quality of life, reduce treatment side effects, increase treatment adherence and potentially enhance survival rates. Integrative oncology also empowers patients, giving them an active role in their care and recovery process, which can lead to improved satisfaction and outcomes. This holistic approach ensures that treatment plans are tailored to the individual needs of each patient, offering a more compassionate and comprehensive form of care.
Discover how cutting-edge technologies like Artificial Intelligence and Precision Medicine are revolutionizing cancer treatment. Explore the personalized approaches that consider genetic, environmental, and lifestyle factors, promising better outcomes and enhanced quality of life for patients. Dive into the latest breakthroughs in microbiome research, offering innovative strategies to boost the effectiveness of therapies
9. What are your predictions for the future of cancer care, particularly in terms of new therapies or treatment modalities?
The future of cancer care is poised for transformative changes, driven by advancements in technology and a deeper understanding of cancer biology. Precision medicine will become increasingly central, tailoring treatments to the genetic profile of both the patient and the tumour, enhancing efficacy while minimising side effects. Immunotherapy, which harnesses the body’s immune system to fight cancer, is expected to evolve and combine with other treatments, offering more personalised and effective options. Additionally, we'll see the rise of less invasive, targeted therapies that can accurately target tumour cells without harming surrounding tissues. The integration of artificial intelligence and machine learning in diagnostics and treatment planning will enable more accurate predictions of treatment outcomes, optimising therapeutic strategies.
Furthermore, the concept of integrative oncology, incorporating complementary therapies into conventional treatment plans, will gain mainstream acceptance, focusing on improving patients' quality of life and overall wellbeing. This holistic approach, alongside the rapid pace of scientific discovery, heralds a future where cancer care is more personalised, less invasive, and more focused on the patient as a whole.
10. How do you measure success and impact in your work, both personally and for Carer as an organisation?
Quantitatively we look at patient health outcomes, such as improvements in quality of life, increased treatment adherence rates, and overall survival rates. Metrics like patient enrolment numbers in our programmes and the scale of our reach, especially in underserved communities, also serve as key indicators of our impact.
Qualitatively patient and caregiver testimonials provide invaluable insights into the effectiveness and emotional impact of our services. The feedback from healthcare professionals about the integration and usefulness of our approach in their treatment plans is another crucial measure.
For me personally, success is also gauged by the ability to drive meaningful change in the oncology care ecosystem, fostering a more holistic, patient-centred approach in the broader healthcare community. It's about the stories of individuals who've regained hope and strength through our support.
Ultimately, for Carer, success means continuously pushing the boundaries of what's possible in cancer care, making a tangible difference in the lives of those we serve, and setting new standards for compassionate, comprehensive care.
Welcome readers to our discussion on
"Emerging Trends and Transformative Technologies in the Healthcare Sector."
We are honored to host a panel of experts who would provide their valuable insights on this trending topic in healthcare.
This interview will discuss the complexities and potentials of healthcare technology. Join us on this enlightening journey as we navigate the landscapes of innovation, impact, and possibilities within the realm of healthcare technology.
Tan Cher Heng
Executive Director at Centre for Healthcare Innovation (CHI)
Konrad Dobschuetz
National Director at NHS Innovation
Accelerator and Chief Enterprise Officer UCLPartners
Dr Mohammad Al-Ubaydli
CEO and founder of Patients Know Best
Sheena (Morjaria) Pirbhai
CEO and Founder at Stress Point Health
1. In envisioning the future of healthcare, we see a trend toward patient empowerment. Patient empowerment refers to the process of enhancing a patient's knowledge, skills, and confidence, allowing them to actively participate in their healthcare decisions. How do you believe these shifts toward patient empowerment will influence the way healthcare services are delivered, and what role do you foresee technology playing in this evolving landscape?
Tan Cher Heng: As Singapore moves away from a paternalistic model of care delivery, to one where patients are aware and activated to take care of their own medical conditions, more emphasis can be placed on providing
patients with the autonomy to decide on the types of investigations and treatments for their medical conditions, that are aligned with the individual patient's values and attitudes. This would lead to greater compliance with prescribed treatments, and consequently better outcomes. Physicians can also focus on more upstream interventions to prevent, and not just to treat, diseases.
Technology will continue to play an even bigger role in the way care can be delivered. Machines are not limited by human factors of stress and fatigue, and can assist care providers to extend their reach, creating “higher touch” with patients and the population on a continuous basis. The advent of generative AI has created even greater potential for this to happen.
Mohammad Al-Ubaydli: Most healthcare professionals are unaware that most health care delivery is by patients: patients with long-term conditions are the ones taking the medications, changing their diet, and doing the exercise… or not. Patient empowerment increases the skills and effectiveness of patients. What’s missing is designing health care services with the recognition of patients’ potential, abilities, and importance. The urgency of the workforce crisis and funding crisis is finally making health care system designers aware of empowerment.
2. How would you describe the current state of AI adoption in healthcare, particularly in treatment and patient care? What are the primary areas where AI is making a tangible impact?
Konrad Dobschuetz: Treatment remains a clinical focused area where we see AI supporting but not leading. In mental health and well-being, we are seeing use of AI to suggest patient facing AI augmented treatments via Digital Therapeutics. As with all mental health interventions, it is crucial that the human factor is taken into consideration as remote treatments without sufficient clinical oversight can have an adverse impact on the patients. This counts for mental health in particular. In comparison in the diagnostics, patient flow and risk stratification space AI tools are emerging to be leading the decision process.
Personalized Medicine using a combination of AI and RNA tech-bio platforms is already entering the mainstream of patient impact treatments. Albeit still not widely available, it is an unstoppable trend.
3. How do you envision the integration of AI in breast cancer care evolving, considering the potential it holds for early detection and personalized treatment? What collaborative efforts or frameworks do you believe are crucial to harnessing AI's capabilities effectively across healthcare systems for the benefit of breast cancer patients worldwide?
Machines are not limited by human factors of stress and fatigue, and can assist care providers to extend their reach, creating “higher touch” with patients and the population on a continuous basis. The advent of generative AI has created even greater potential for this to happen.
Mohammad Al-Ubaydli: My medical training started as radiology was gaining in attractiveness as a career pathclinicians could work anywhere, anytime, thanks to digitisation. Today’s medical students are abandoning radiology as they see the extraordinary leaps in AI displacing their career prospects. I think they are unduly pessimistic - AI will multiply the radiologist’s abilities rather than displace them - but they are correct that that potential is huge. As more datasets become digital, including cancer biopsies and genomes, the training data set across a cancer’s lifecycle allows earlier detection, more personalisation, with fewer false alarms and more concise treatment. Countless lives will be saved and improved.
4. What aspects of your current role do you find most energizing and fulfilling? Conversely, are there tasks or situations that you find less engaging or draining? How do you navigate these different aspects to maintain your passion and productivity? Additionally, could you share any strategies
or approaches you employ to address challenges and sustain enthusiasm in the dynamic field of healthcare technology?
Sheena Pirbhai: I founded Stress Point Health so that I could help as many people as possible with their mental
health. Getting to do that, every day, is incredibly fulfilling and motivates me to keep going, even through difficult cycles that every start-up experiences. Healthcare is a deeply personal and human area to be involved in and this comes with its own challenges. Hearing stories of how the healthcare system has failed so many people with their mental health, can be emotionally draining and difficult at times. But seeing the change we are making and impact on
5. Over the forthcoming biennium, AI and Big Data are anticipated to remain the most disruptive forces in the healthcare sector. Can you elaborate on specific examples or use cases where AI and Big Data have already demonstrated disruptive forces in healthcare? How have these technologies transformed processes, improved patient outcomes, or enhanced overall efficiency within healthcare systems?
Tan Cher Heng: Big data and AI are synergistic in allowing for individualised care through data collection for continuous monitoring of biomarkers, behavioural nudges leveraging on generative AI, and analytics of multimodal datasets ranging from simple demographic to complex genomic datasets for risk stratification and more accurate disease prediction. When applied at the population level, this could help providers and payers better allocate their limited resources to achieve maximal gains in the healthcare system. At the care provision level, it could lead to better triaging of cases. For example, during COVID-19 when there was a surge in demand beyond capacity, Tan Tock Seng Hospital deployed an AI model that helped to prioritise patients with abnormal x-rays for urgent review by the radiologists, and consequently, the emergency care team. This leads to more expedient management of the sicker patients.
Konrad Dobschuetz: Here risk stratification is a key piece as it helps health systems to manage the ever growing number of patients that need specialist treatment. We are also seeing discharge and the assessment of bed occupancy a key piece driving down waiting list, relieving pressures from the health system.
people’s lives keeps me productive and passionate every day. It is particularly important in healthcare to put the patient first, understanding their needs and challenges and innovating to serve them. Innovation is essential but not at the expense of the patient experience. I always ensure time and resources are allocated to research in order to stay in touch with patients and their ever changing and growing needs.
6. Innovations in healthcare are undergoing transformative shifts, notably driven by technological advancements. Could you provide specific examples of technological advancements that are currently reshaping the healthcare industry? How do these innovations contribute to improving patient care, streamlining processes, or addressing critical challenges within the healthcare ecosystem?
Mohammad Al-Ubaydli: A smartphone is the most extraordinary behaviour change tool, and behaviour change is the most important treatment. As everyone carries a phone and a phone measures everything, your phone will advise you what to do - and not to do - at the time you need it. It is the ultimate point of care tool. By contrast, health care professionals receive little training in behaviour change and have even less time to deliver it. This is the biggest gap in health care as the
biggest spending is on behaviourdriven diseases, i.e. long-term conditions. The falling price and rising usability of smartphones - including the natural language user interface of ChatGPT - are just what we need.
Sheena Pirbhai: Technological advancements are playing a crucial role in reshaping the healthcare industry. Telemedicine has enabled remote consultations where traditional healthcare may not always be accessible and remote patient monitoring provides timely interventions and personalised approaches to care. This has improved the burden on healthcare systems, especially in a post-covid environment. Telemedicine has also helped in prioritising in-person visits and streamlining access to care thus allowing for continuous monitoring of patient’s health.
Artificial intelligence and machine learning have been effectively applied to diagnostics and predictive medicine. The next generation of care advancements need to continue to personalised treatment plans and AI is at the forefront of these technologies.
The benefits of AI have the potential to be far reaching from enhanced diagnostic accuracy, quicker data analysis all leading to improved treatment outcomes by tailoring interventions to individual patient profiles.
Wearable devices and smart devices have advanced the ability to monitor patients remotely allowing real-time data collection, proactive health monitoring, and improved management of chronic diseases. Data from these devices can also be integrated into smartphone apps and digital therapeutics, improving their accuracy and personalisation.
7. What imminent impacts do you foresee these technologies having on the sector shortly?
Sheena Pirbhai: I think we are continuing to see a paradigm shift in the approach to care with the fast pace of innovation. I think there will be impacts on patient care, operational efficiency and the ecosystem as a whole. I also see the opportunity for technology to move healthcare to a place where we can focus on prevention and health optimisation.
One of the key influences of technology will be the ability to reach more people who have limited access to care due to geography or socio-economic status. As telemedicine and virtual care continue to expand, this will provide patients with convenient access to healthcare services. The use of AI and machine learning in disagtonitcs also has the potential to lead to more accurate and timely diagnosis, which should contribute to the personalisation of treatment plans based on individual patient data and characteristics.
All these advancements in telemedicine, digital health, AI diagnostics have the potential to reduce healthcare costs by reducing hospital admissions and optimising resource utilisation. But as innovators we need to ensure we protect patients - both their data and their healthcare journey.
8. In the realm of emerging technologies, what industry trends are emerging regarding the adoption of these innovations to gain a competitive edge? Could you elaborate on specific instances where the utilization of emerging technologies has provided a substantial advantage within your respective domains?
Konrad Dobschuetz: We are looking at an increase in applicable and scalable AI solutions rather than silos. Data in structure, quality and quantity remain one of the key issues in designing successful AI augmented clinical interventions. The inclusion of prediction models in healthcare, especially in early cancer diagnosis is on the rise and one of the key elements of our work.
Mohammad Al-Ubaydli: I rarely come across useful competitive edges between health care providers - the dysfuctional financial incentives of health care mean that too often the competitive advantages are gaming the system, without improvements in health outcomes.
What’s more interesting to me is countries using innovation with a public health approach as a competitive advantage for their economies. Covid reminded us of the importance of vaccines for society. Sugar taxes and walkable cities are just as important as the new generation of weight loss drugs in tackling obesity.
9. With the escalating momentum of remote care adoption, a trend projected to surpass conventional in-person visits, could you elaborate on the factors propelling this shift? How might this transition impact healthcare practices and patient experiences, both nationally and globally, in the foreseeable future? Additionally, what potential challenges or concerns do you foresee associated with the widespread adoption of remote care, and how can these be effectively addressed within healthcare systems?
Konrad Dobschuetz: Key factors to consider here are a stretched health system, where in person treatment and beds have already become a much desired commodity to the empowered patient and the convergence of key technologies such as AI, blockchain, AR/VR and 5/6G for connectivity. Already we are looking at over 10,000 virtual wards beds in England and that will only expand dramatically in the coming years. We know that an effective virtual wards approach can lead to up to 50% of reduction in readmissions for example. One element that gets forgotten often is digital exclusion. According to the report by the Kings Fund from March 2023, close to 30% of people in England consider themselves digitally excluded from healthcare already or find it difficult to access it. That is a major factor and we have to take these people along, otherwise we are in danger of creating an ivory tower health and care system.
Tan Cher Heng: Remote care is heavily dependent on the audiovisual technologies that facilitate real-time communication between providers and patients, better known as telehealth. COVID-19 was certainly a catalyst for us to adopt this mode of care delivery into our workflows. The evolution of sensor technologies that are able to capture other aspects of human well-being, beyond history-taking, increases the confidence of physicians in making diagnosis and determining treatment for patients virtually.
The transition towards remote care as an accepted form of care delivery could disrupt our conventional models that are still largely bound by geography, within large countries and internationally. Democratising access to care, if planned and implemented thoughtfully, can increase health equity and lead to more effective use of healthcare resources globally. That said, the reliance on digital and data systems to drive the provision of remote care would mean that it is intrinsically limited by provision of access to technology. Foreseeably, IT outages can pose a danger in the emergency or intensive care settings.
10. In what ways do you foresee AI contributing to the enhancement of mental health services? Could you delve into specific applications or advancements within AI that have the potential to significantly impact the field of mental health, and how might these innovations shape the future landscape of mental health care?
Sheena Pirbhai: The next generation of mental health treatment and support needs to have a more personalised and adaptive approach. I believe that AI has the potential to significantly enhance mental health services by supporting digital mental health solutions with assessment, diagnoses and targeting treatment modalities.
AI-powered tools can analyse patterns in language, behaviour, and other data to identify early signs of mental health issues. This data can be used to feed AI algorithms to analyse large datasets and identify effective treatment strategies based on individual patient characteristics. This enables the development of personalised treatment plans that take into account genetic, environmental, and lifestyle factors, improving the efficacy of interventions.
Emotional dysregulation is a key driver of mental health conditions. AI can be trained to recognise facial expressions, vocal tones, and other non-verbal cues to assess emotional states. This technology can aid in understanding patients' emotions, administering effective digital health treatments to regulate emotions and provide additional insights for mental health professionals. These tools can offer effective, accessible, and scalable mental health treatments.
AI-enabled wearables and IoT devices can continuously monitor physiological, emotional and behavioural indicators related to mental health. This real-time data can be used to assess the effectiveness of treatments, track mood patterns, and provide timely interventions when necessary.
Even with the advancements in the mental health there is a still stigma associated with seeking help. Digital mental health platforms that focus on confidential and private treatment can help to reduce these stigmas. Online platforms and virtual support groups powered by AI can create a more inclusive and supportive environment for individuals seeking help.
While AI holds great promise in transforming mental health services, ethical considerations such as data privacy, transparency, and accountability must be carefully addressed. There have been concerning cases around AI chat bots encouraging suicidal ideation and being counterproductive to patient’s mental health. Clinical intervention is still necessary but being able to combine innovation with traditional pathways can have a powerful impact. Additionally, collaboration between AI developers, mental health professionals, and regulatory bodies is crucial to ensure the responsible and ethical implementation of these technologies in mental healthcare.
Mohammad Al-Ubaydli: I want to take a slightly different angle. One of the biggest blows to advancement was the world’s reaction to Facebook’s publication of its research on mental health. Facebook tried to measure the effect of changing its feed on the mental health of its users. We all need every service to do more of this research. Instead the reaction in the press ended all transparency around such research.
We must do more, more publicly, what’s missing is a mature attitude in the press.
11. How do the absence of specific skills and talents, inadequate funding, and the presence of organizational silos impede the adoption and progress of emerging technologies?
Tan Cher Heng: Using AI as an example, we now face challenges with its adoption, primarily due to the presence of legacy enterprise digital systems (e.g. electronic medical records) that are not able to easily incorporate the myriad of AI solutions emanating from the start-up ecosystem, many of which could effectively support the transformation of health services. The need for compliance with ever increasing cybersecurity regulations further limits our agility to adopt novel AI algorithms into our clinical and operational workflows. Organisational silos impose constraints on data sharing, compounding our inefficiencies not just in developing algorithms that can be generalisable, but also in crossvalidating AI models that are already proven to be of value in other practice settings.
Konrad Dobschuetz: Any of these elements are big issues in themselves. In England for example we are looking at 42 Integrated Care Systems (ICSs) that all represent a number of hospitals and care centers. These ICSs have significant procurement powers, albeit this is still in the early days. We can
already see some silos emerging and differentiation in the adoption of AI driven solutions, depending on the maturity of the system as well as willingness to adopt. Funding is another big topic with currently widely unsustainable funding models, running for only a small number of years in any. The flaw in the system currently is an annual funding cycle nationally which in time hopefully will be resolved and revert back to a longer period.
12 In the era of accelerated digital transformation, how do we balance the drive for innovation with the critical need to safeguard digital privacy and ensure data security? Can you explore specific strategies or frameworks that organizations can adopt to effectively balance the pursuit of innovation with the imperative of maintaining robust digital privacy and data security measures in the healthcare sector?
Mohammad Al-Ubaydli: I don’t think there is a conflict between innovation and security. Security is more important than ever as we store more data digitally. And innovation is more necessary than ever as we face multiple crises in health care from current approaches. What’s missing is a safe environment in which to learn how to improve security. Coverage of data breaches is premature and sensationalist, exaggerating problems and decreasing trust. The aviation industry shows us how to improve safety while embracing innovation through constant, non-judgemental disclosure.
Sheena Pirbhai: Balancing the drive for innovation with the imperative of maintaining robust digital privacy and data security is a critical challenge, especially in the healthcare sector where sensitive patient information is involved.
Integrating privacy and security measures into the development process is essential from the outset. This means considering data protection and security at every stage of product or service design and development, rather than treating them as add-ons.
Whilst regulation is a constantly evolving landscape, adhering to existing and emerging privacy and security regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States or the General Data Protection Regulation (GDPR) in Europe is vital. I recommend regularly updating policies and procedures to ensure compliance with regulatory requirements.
Conducting thorough risk assessments to identify potential threats and vulnerabilities in the technology infrastructure is important to keep patients safe. Designing and executing robust risk management strategies to mitigate and address these risks, will prioritise the protection of sensitive healthcare data.
Being prepared and responsive for incident resolution should be a high priority in the development of technology solutions. Developing and regularly testing incident response plans will ensure a swift and effective response to data breaches or security incidents. This includes having a clear communication plan to notify affected parties promptly.
I think it is also essential to maintain transparent communication with patients and stakeholders regarding
data collection, usage, and security measures. Clearly articulate how data is handled and protected, will build trust and transparency.
Within our organisation we have also established a culture of ethics and accountability. This involves considering the ethical implications of data use, ensuring transparency, and holding individuals and the organization accountable for adhering to privacy and security principles.
By adopting these strategies and frameworks, healthcare organisations can balance the drive for innovation with the critical need to safeguard digital privacy and ensure data security. This approach is essential for maintaining trust among patients, complying with regulations, and protecting sensitive healthcare information in an era of accelerated digital transformation.
13. In a fast-paced industry where innovations constantly evolve, how do you personally ensure you are always up-todate with the latest trends and advancements? Could you share specific sources, forums, or platforms you and your organization utilize to stay current and ahead of the curve in the rapidly changing landscape of healthcare technology?
Big data and AI are synergistic in allowing for individualized care through data collection for continuous monitoring of biomarkers, behavioural nudges leveraging on generative AI, and analytics of multimodal datasets ranging from simple demographic to complex genomic datasets for risk stratification and more accurate disease prediction
Tan Cher Heng: I believe that the best way to stay up-to-date with the latest innovations is to “walk the talk”, i.e. to be directly involved with any technology by either developing or deploying it. As a clinical radiologist myself, I have come across numerous deep machine learning models that are touted to be as accurate or even more accurate than a human radiologist in interpreting medical images to diagnose diseases. My team and I have learnt the most through a process of discovery by developing and deploying AI algorithms, based on our hospital’s ground-truth datasets, together with our scientific collaborators. We now have a deep appreciation of the infrastructure required to facilitate the mainstream application of image-based AI in a clinical setting. I have been able to extend my understanding towards facilitating AI adoption in non-clinical settings in my role of leading the Centre for Healthcare Innovation. We work closely with industry partners and government agencies like Synapxe, to accelerate the process of adoption, not just of AI but also, other technologies such as medical 3D printing, extended reality, digital automation and telehealth.
Sheena Pirbhai: There are number of key ways in which I stay on top of trends. It is important to continuously learn from others through industry conferences, webinars and workshops to ensure continuous professional development of new technologies and innovations.
Networking through professional organisations and associations is a great way to meet like-minded peers and exchange ideas and information. Actively engaging with online communities is also a great way get insights from industry experts.
As innovators I think it is key to read scientific journals and read articles, case studies, and whitepapers to stay informed about the latest medical advancements advances. In addition, reputable healthcare technology publications, journals, and blogs are a good source of background information and varied points of view.
Collaboration and partnerships are essential in healthcare and working with other organisations such as universities, or research institutions can give you access to cutting-edge research and innovations.
Lastly market research is the final building block of staying up-to-date. Conducting regular market research to identify emerging trends, competitors, and market demands and analysing industry reports and market intelligence will help to inform strategic decisions.
14. In the landscape of cancer care, AI innovations have played a pivotal role in reshaping early detection, diagnosis, and treatment methodologies. Could you
provide insights into some of the most impactful AI-driven advancements in each phase of the cancer control continuum? Specifically, are there any particular AI-driven advancements that have significantly impacted cancer care in recent years?
Konrad Dobschuetz: As mentioned before, there are significant improvements for example in image analysis of potential lung cancers as well as breast cancers. Another piece is the multi cancer detection via a single blood test, detecting over 50 cancers. This is being rolled out in England.
15. How do you envision the integration of AI in cancer diagnosis and treatment evolving in the next five years, and what challenges do you foresee in implementing these advancements on a larger scale within the healthcare system? Additionally, could you share insights on potential ethical considerations or societal impacts associated with the widespread implementation of AI in cancer diagnosis and treatment, and how these aspects should be addressed moving forward?
Tan Cher Heng: For diagnosis of cancer, AI can democratise the expertise of radiologists and
procedurists, to scale up efforts in increasing the penetration of population based screening, such as for breast and colorectal cancer. It can also be used to implement new screening modalities like CT scans for lung cancer. By combining the biomarkers across different modalities, AI can assist physicians in segmenting patients into low and high risk groups, allowing for tailored surveillance and therapeutic regimes. As with other potential medical applications of AI, we need to be mindful of ethical issues that pertain to data privacy and confidentiality and societal concerns that relate to health equity and access.
Konrad Dobschuetz: I can see a straight line from to at home blood tests to genomics, and prediction algorithms leading a much earlier and personalized cancer detection. We are already able to for example identify stage 1 GI cancers via a simple test, so why wouldn’t we be able to do this for others? Crispr in combination with TechBio platforms using AI and RNA technology will provide us with the ability to switch a cancer off before it becomes dangerous. Thinking beyond that, on a population health level all main cancers should be close to eradicated by 2050 and no longer be the leading cause of death.
A heartfelt thank you for your invaluable insights during our panel discussion on "Emerging Trends and Transformative Technologies in the Healthcare Sector." Your expertise and thoughtful responses have made a lasting impact on our audience, providing a clear understanding of the complexities and potentials of healthcare technology.
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Venue: Amsterdam, Netherlands
https://crgconferences.com/infectiousdiseases/
About Event: This Conference provides unique networking and collaboration opportunity to promote your merchandise and gain your brand recognition and credibleness. It delivers cutting-edge analysis on research in association with the intimate setting where attendees and exhibitors receive customized client service.
Listed Under: Medical Science
Event Date: 5th - 6th June 2024
Venue: Munich, Germany
https://researchplus.co/event/index. php?id=2332349
About Event: The International Conference on Cardiac Surgery and Cardiomyopathy, Cardiac Disorders (ICCSCCD - 24) aims to bring together researchers, scientists, academicians, policymakers, and industry experts to share their experiences and knowledge in their respective fields. This conference will provide a platform for attendees to exchange ideas, discuss research findings, and network with one another. (ICCSCCD - 24) offers a valuable opportunity for attendees to learn about the latest advancements and developments in their field. The conference is dedicated to showcasing the latest innovations, trends, and concerns in a variety of fields, making it a premier interdisciplinary platform for attendees.
Listed Under: Surgical Speciality
Event Date: October 07-08, 2024
Venue: Rome, Italy
https://www.stripeconferences.com/surgeryanesthesia-conferences/
About Event: The Global Conference on Surgery
Anesthesia Conferences and Anesthesiology Conference is a highly anticipated event set to take place in the Rome, Italy, from October 07-08, 2024. Bringing together leading experts, researchers, practitioners, and industry professionals from around the world, this conference promises to be a hub of cutting-edge advancements and insightful discussions in the fields of surgery and anesthesia
Listed Under: Surgical Speciality
Event Date: June 27-28, 2024
Venue: Amsterdam, Netherlands
https://www.globalscientificforum.com/ conferences/cardiology
About Event: Global Scientific Forum is formed to pursue the common and collective goals of the research scholars in order to endorse exchanging of their innovative ideas and know-how which facilitate the collaboration between them of the same field or interdisciplinary research.
Event Date: May 16-17, 2024
Venue: Rome, Italy
https://radiology.cmesociety.com/
About Event: 2nd International Conference on Radiology and Diagnostic Imaging event offers a platform for sharing cutting-edge research, exploring new imaging technologies, and discussing best practices in the radiology field.
Listed Under: Diagnostics
Event Date: July 15-17, 2024
Venue: Berlin, Germany
https://mindspaceconferences.com/digitalhealth/
About Event: Digital Health Conference, a premier international event will focus on driving transformative changes in the healthcare industry through integrating digital health and telemedicine. This conference aims to bring together esteemed experts, distinguished personalities from academia and industry, as well as healthcare professionals from around the world.
Listed Under: Technology, Equipment & Devices
Use the webinar as a platform to launch new products and services
Grow your audience with increased reach, impact and user-friendliness
Rise above geographical boundaries
Generate new business
Gain the strong web presence differentiating yourself from competitors
Connect and engage with your target audience
Give more exposure to industry specific people
Increase your brand profile and share your capabilities with leading industry professionals
Aspiring to be leading journals in the B2B landscape of Healthcare-Industry covering Medical Science, Business & Technology and all the latest innovations.
Introducing a group of highly focused magazines for the American and European markets.
Poised for bi-annual issuance, our new magazines bring a fresh outlook towards insightful and pragmatic Healthcare-Industry reporting.