February 4, 2021 marks World Cancer Day. In Canada, the Cancer incidence rates across the country vary because of varying risk factors (including risk behaviours) and early detection practices. According to Canadian Cancer Society, Lung, breast, colorectal and prostate cancer are the most commonly diagnosed types of cancer in Canada (excluding non-melanoma skin cancer).
Across the globe, healthcare authorities, public health, academic institutes, and research organizations are joining forces and evaluating the use of Artificial Intelligence to improve cancer detection. Innovative technologies are being tested and evaluated to improve predictive intelligence to better deliver personalized care, with precision.
What has COVID-19 taught us regarding Innovation?
One of the most disturbing aspects of this pandemic is the manner in which COVID-19 paralyzed and overwhelmed some of the world’s best health systems. The OECD’s latest Health at a Glance report shows just how much money the countries worst impacted by COVID-19 pump into their healthcare systems each year. Northern Italy is regarded as having one of the world’s best and most efficient health systems, but it was swiftly overwhelmed by the COVID-19 tidal wave. Italy’s health expenditure is equivalent to 8.8% of GDP and Spain’s is similar at 8.9%.
While the COVID-19 landscape in Canada looks much better now when it comes to the path towards economic revival, things are a bit different in the US where healthcare spending is more than Canada and COVID-19 remains an overwhelming challenge.
THE NEED FOR SMART INVESTMENT AND EVIDENCE-BASED INNOVATION: While healthcare organizations across the globe have remained under pressure to deliver cost-effective and high-quality care, the COVID-19 challenge has exposed the basic premise of how health systems in developed countries have been designed, and now facing challenges in the delivery of personalized care and enabling precision health, that has been the hallmark of discussions around healthcare transformation in the western world.
One way to achieve this is to empower public health policy planners and physicians with predictive, fast, easy, and direct access to all of a patient’s clinically relevant medical data, social determinants of health, genomics, and population risk factors. When it comes to new diseases, we are discovering more information about COVID-19, and still, need to learn more about why COVID-19 impacts some more than others.
What’s needed is a digital health profile of our population, and not just focusing on patients presenting with clinical manifestations. It is time to create a digital twin of our population; there’s a need to aggregate the available data intelligently to enable the visual health profile of our population, deliver personalized care and improve academic knowledge for our future workforce
The investments should not primarily focus on medical equipment or supplies procurement, the investments should guide towards evidence-based problem prediction, diagnosis, and outcomes that need to be improved now and in the future.
WHAT ABOUT THE ROLE OF ARTIFICIAL INTELLIGENCE (AI): Generally speaking, and when it comes to innovation, Canada was one of the first countries in the world that announced an Artificial Intelligence strategy in 2017. The Canadian government launched the Pan-Canadian Artificial Intelligence (AI) Strategy in its 2017 budget with an allocation of $125 million, administered by CIFAR.
Provinces and Federal Government need to evaluate a Pan-Canadian Health Intelligence Strategy that helps not only alleviate some of the challenges associated with older technology being used in our healthcare systems but also look at how the provinces can be more predictive in capturing diseases earlier.
According to a report by Fraser Institute, referral by a general practitioner to consultation with a specialist, the waiting time in this segment increased from 8.7 weeks in 2018 to 10.1 weeks in 2019. This wait time is 173% longer than in 1993 when it was 3.7 weeks. Can technology and automated decision support tools help alleviate this challenge and help our care providers with more precision in care delivery?
Fast and timely access to evidence-based personalized care, at the right time, and with the right tools (technology, decision support, skills) should be the aim of a precision health model.
Canada can shape a Precision Health Intelligence strategy by creating a framework focusing on the following fundamentals:
- Population Health Focus: Identifying the top population health challenges where data analytics and AI can be leveraged (consider cancer screening, chronic disease including Tuberculosis in rural communities, Hypertension, Diabetes, Diabetic Retinopathy, new diseases and other national and provincial challenges)
- Centres of Excellence: Creating a network of hubs acting as centers of R&D innovation (MOUs between select public hospitals, national and international universities)
- Public-Private Partnership: Industry, academia, and talent collaborating on an integrated strategy, whether it is product development or drugs and vaccines
- Collaborative Research Infrastructure: Bringing talented people, knowledge and innovation under a collaborative body
- Governance: Establishing a national strategy that follows a holistic approach focused on population, disease analytics, social and environmental factors, and talent of its people currently available and in the pipeline
This is an integrated strategy that fosters national collaboration, introduces efficiencies, and helps address not only the challenges of today but also provides a data-driven framework to help prepare the system (hospitals, medical equipment manufacturers, pharma) much ahead in time as an opportunity instead of responding to challenges.
Precision Health-focused Integrated Health Intelligence:
Precision Health is all about being predictive, intelligent, and evidence-based. It is not about creating new drugs or medical solutions for each and every individual patient, but it looks at an evidence-based approach to cohorts of the patient populations with similar health challenges and disease profiles.
Last year’s report from the Canadian Cancer Society (CCS), in collaboration with Statistics Canada and the Public Health Agency of Canada, has found that the chances of successful treatment and survival for lung cancer are dramatically increased when it is found and detected early.
Digital transformation or Artificial Intelligence alone cannot be the game changer if you do not incorporate human intelligence and scientific evidence with it. While new diseases are on the rise, with its vast network of the workforce and academic institutes, Canada can reshape and innovate its digital health strategy.
Technology is getting sophisticated and faster at doing what humans can do, hence the debate around man vs machine has shifted to the man working with machines and tools, an approach that can be referred to as Augmented Intelligence.
AI’s transformational benefits revolve around early disease detection, informed decision making, clinical decision support, academic research and training, population health analytics and improving drug efficacy.
Canada’s Precision Health Intelligence strategy should have 5 major goals:
- Improve early disease prediction and detection (new and unknown diseases, and top clinical challenges, for example, cancers, chronic diseases, TB in rural communities, and others
- Increase the number of artificial intelligence researchers and skilled graduates in Canada focused on top clinical and technology gaps identified
- Establish an interconnected, collaborative, approach between the provinces to enable data sharing so that established hubs of innovation focus on needs-based development of new technologies and innovative solutions
- Develop global thought leadership on the economic, ethical, policy, and legal implications of advances in blockchain, artificial intelligence, and new drug discoveries
- Support a national research community on new innovations, based on measurable outcomes. The world, the investors, are looking towards Canada and willing to invest in our expertise.
Looking to the future – Health 2.0:
Did anyone in the world prepare themselves for the unprecedented challenges faced by the current pandemic? Can anyone in Canada predict what new diseases, workforce, and capacity challenges the country will face in the next decade, let alone next year?
The race to become the global leader in the health intelligence-enabled workforce has already begun. Frameworks for artificial intelligence already began a couple of years ago. Besides Canada, UK, China, Denmark, the EU Commission, Finland, France, Italy, Japan, Mexico, the Nordic-Baltic region, Singapore, South Korea, Sweden, Taiwan, the UAE, Pakistan, and others, have all released strategies to promote the use and development of AI.
The strategies announced by each of these countries are unique, each focusing on different aspects of AI policy – ranging from scientific research, talent development, skills and education, public and private sector adoption, data and digital infrastructure.
UAE became the first country to appoint a Minister of State on AI in October 2017. Saudi Arabia established in 2019 the Saudi Data & Artificial Intelligence Authority (SDAIA). Saudi Arabia expects Data and AI will add more than USD 10 Billion to its economy.
On the other hand, the President of Pakistan’s Initiative for AI and Computing (PIAIC) is an impressive and ambitious program that is set to reshape Pakistan by revolutionizing education, research and business. The initiative was launched in 2018 and has over 100K enrolled in the 1-year program.
Why Canada has an innovative edge:
We live in a world powered by digital technologies because we needed faster access to tools for automation and actionable intelligence. There is a need to leverage digital data in healthcare and associated population health analytics.
Canada has a diverse multiethnicity population, intelligent workforce, evidence-based research and R&D mindset, digital infrastructure in place to a certain level when it comes to Electronic Medical Records and Medical Imaging IT (Radiology, Cardiology, Oncology). This puts Canada in the right place to begin rethinking leveraging these digital data lakes and deriving meaningful intelligence to not only train and develop machine learning algorithms, but also the aggregation of genomic data and relevant clinical intelligence.
The diversity of our population allows us to develop new innovations and solutions that the rest of the world is precisely missing, and looking for.
There is a strong need for a national framework that not only leads a Canada-centric effort to prepare the country with armed (health) forces of the future, but also lead a global effort that brings the best of minds and technology together.
Canada is in a unique position to fill the gaps realized from digital transformation experiences and new disease challenges experienced in the developed world. This will help put forward an integrated health intelligence and needs-based innovation strategy, that not only addresses pressing health challenges of today but also serves as a framework for enabling precision health and predictively intelligent care delivery models in the near future. This would help establish integrated health and care model that will enhance the academic research landscape and prepare an innovative workforce of the future.
Cover Photo: Shutterstock.com
About the author: Dr. Anjum Ahmed is a global speaker on AI and healthcare innovation. He is the Chief Medical Officer and Global Director for Innovation and Artificial Intelligence at a Belgium-based global healthcare IT solution provider. Dr. Anjum Ahmed has to his credit thought-leading publications on value-based digital transformation in healthcare and practical application of AI in medical imaging.
