Asclepius was the God of Medicine, according to ancient Greek Mythology; and his ‘rod of Asclepius’, the snake entwined staff, is still a widely recognised symbol of medicine. For centuries, Asclepius was (and is) considered as perhaps the greatest healer. But surprisingly, ‘medicine’ is defined a little differently: according to the Oxford dictionary, it is ‘the science and practice of diagnosis, treatment, and prevention of disease (often excluding surgery)’. Yet, in healthcare today, we focus on providing reactive care – treating sick patients, instead of proactive care – helping prevention of diseases as well, in line with the complete definition of medicine. We are now therefore facing challenges with chronic conditions, for example, and don’t really have a Panacea (incidentally a daughter of Asclepius), at least a quick one for these problems.
That healthcare is undergoing transformation is a given fact. Dealing with expensive, life-long chronic conditions and an ageing population on the one hand, and with several technology innovations touted to address these challenges on the other, the model of delivering care is being upended. Moving towards a proactive or preventive care approach requires data-driven, clinically meaningful insights to be available for a physician to make prognostic, predictive decisions early-on. Luckily, with technology advances the healthcare industry is undergoing a digital transformation towards a much anticipated decentralisation of the care delivery models to bend the cost curve for lifestyle-driven chronic health conditions.
Today, digitisation of drugs (therapies), devices, services, and business models is democratising current healthcare systems, unlocking new values by displacing high-cost gatekeepers and previously inaccessible segments. This has made the digital transformation theme a core strategic priority for all healthcare industry participants, as they strive to justify the value in the much-anticipated data-driven, outcome-based reimbursement regime. The adoption of these technologies is being incorporated even in national strategies for healthcare, such as Saudi Arabia’s National Transformation Plan 2020, for example.
But implementing such advances in healthcare leads to another set of challenges altogether – privacy and cybersecurity of patient data for one, but even the ability to sift through and make sense of such large volumes of data (a long view for a patient, and at a population level). As we continue tracking the several technologies in healthcare at Frost & Sullivan, we continue to see emerging innovations in care delivery, with novel business models and some growth opportunities along the way. Here, we present our top three picks of transformative technologies in healthcare, and where we think they are heading.
Internet of Medical Things – Care Delivery Innovation Promoting Anytime, Anywhere Care
The Internet of Medical Things (IoMT) or the Healthcare Internet of Things (IoT) is a vast umbrella term with many applications of the technology. IoMT is well-suited to meet the needs of today’s transforming healthcare industry, supporting the transition from disjointed care to co-ordinated care and reactive to proactive care delivery approaches, for example. Capitalising on this trend with the right applications, for the right customers with the right partners and relevant business models is crucial for healthcare stakeholders to survive the fierce competition, which is supported by start-ups and tech giants alike. There are four broad application segments for IoMT that support the development of the ‘anytime, anywhere care’ approach of healthcare delivery, allowing for insights to be collected and shared with medical care practitioners, and allowing them to intervene when necessary in a proactive approach to lead to better patient outcomes:
On-Body (aka Wearables): After a wave of consumer-grade wearables tracking fitness, medical-grade wearables and ‘smart’ implants that can communicate parameters and be used by patients are now coming to the market. Even makers of consumer grade wearables are developing medical-grade features for their products; the most recent example being Apple Series 4 Watch for ECG monitoring that secured US Food & Drug Administration approval.
In-Home (extending to Smart Homes): Similar to the wearables, other connected and smart diagnostic medical devices that support telehealth services are also used at home by patients – such as TytoCare at-home physical examination device for ears, throat, heart, lungs, abdomen, skin, heart rate and temperature. Another example is of Inui Health that provides in-home urine testing using a smartphone app for colorimetric analysis, for testing kidney and general health, and urinary tract infections. All such devices and sensors, in combination with smart home systems can also provide better monitoring and care for residents, especially the ageing-in-place community.
In-Hospital (extending to Smart Hospitals): Clinicians in primary care are beginning to use smart, digitised clinical devices like digital stethoscopes. Hospitals are employing RFID, beacon or indoor GPS technologies for wayfinding within the their premises and smart hospital rooms that allow patients to communicate with care teams virtually, from their bedside - all in a bid to improve patient experience. IoMT technologies enable hospitals by providing data that can be processed for providing a valuable service or insight, which was not possible or available earlier – the very definition of smart hospitals. A great example is the use of advanced technologies at the Johns Hopkins Hospital’s Capacity Command Centre, built in partnership with GE Healthcare Partners.
In-Community (extending to Smart Cities): Outside of homes and hospitals, smart cars can track vitals of passengers during transit, and any exigencies can be supported by drones for emergency response. From a public health perspective, the MIT Underworlds Project explores sewers as a source of information to track spread of diseases using sensors, but smart city projects are probably not geared for healthcare at the moment, we envision these to become a reality in the 10-20-year timeframe.
Artificial Intelligence (AI) – Collaboration of Man-machine Intelligence to Redefine Healthcare Adoption of AI in the global healthcare market is expected to accelerate due to the need to automate the process of evidence-based business decision making and increasing availability of both platform grade and modular machine learning or deep learning solutions. With 55 per cent of the EMEA region, and 66 per cent respondents in Saudi Arabia and 62 per cent in UAE willing to have AI technology to help treat them, the potential for the technology in this region is high. We believe that AI solutions may never replace doctors but will definitely allow them to be more efficient and accurate. AI’s ability to help physicians identify disease patterns that were historically untraceable, will break new grounds in healthcare research and delivery. On the other hand, the surge in patient generated data can be handled and interpreted by AI platforms and can have multiple utilities for diverse set of healthcare stakeholders. The use cases for AI are plenty, but we will restrict them to the following two:
Medical Imaging: Apart from the most famous, and most advanced image analysis applications (detecting a tumour in a CT scan for example), there are several other applications in the medical imaging workflow for AI. Along all of the steps of the workflow, from ordering of imaging studies by a physician, to acquisition of the images by the imaging equipment, to assigning the images for review by a radiologist, to viewing, analysing, interpreting, deciding next steps and reporting – all can benefit from AI in different formats. And in almost each case, we are seeing some developments already. Even medical imaging equipment is becoming ‘smart’, and using AI to position the patient correctly while imaging to remove operator variability for example, saving time and also reducing patient radiation exposure. There also are pre-clinical applications in research using medical imaging such as imaging biomarker validation for radiomics, for example.
Patient-Facing Apps and Devices: Consumer or patient facing medical devices and mHealth apps are also equipped with AI to drive intuitive patient monitoring, patient safety management and self-care. Patient engagement is another important area where AI has multiple applications. Payers and providers are actively trying to automate the process of identifying patients who need preventive screening and cross-continuum follow-up support. The most recent example from the Middle East is the agreement between the Dubai Health Authority and Babylon Health, which provides medical consultation through an AI-based chatbot and telehealth support as well.
Blockchain – The New Trust Code for Digital Health Workflows
As the healthcare industry struggles to find the trade-off between the risk and reward of going digital, potential application of blockchain technology provides a timely solution to mitigate some of its pressing needs. Despite the enormous potential of blockchain in disrupting healthcare digital workflows, it may not be the panacea for all healthcare industry challenges. It therefore is critical for healthcare industry’s senior executives to first understand and decode the hype cycle of blockchain technology, and its realistic healthcare applications. By doing so, we believe that among several hundred use cases, the blockchain-based healthcare use cases mentioned below demonstrate more convincing opportunities, albeit at varying degrees of adoption across countries and health systems.
Health Data Exchange and Interoperability: It is important to understand that true interoperability transcends beyond the technical facets of information exchange - it is the ability of two or more systems or entities to trust each other and then use the information with shared accountability. As a result, despite increasing adoption of EMR/EHR systems and digital health solutions, lack of trusted digital workflows has resulted in disparate HIT systems and centralised health data management models. Based on industry estimates, current centralised IT systems for health data exchange cost about 150,000 lives and $18.6 billion every year globally to health systems. The unique properties of blockchain technology provide an immutable and trusted workflow with a “single source of truth” to warrant integrity around health data exchange, minimise cybersecurity threats, and augment health data governance applications. The recent collaboration between Guardtime, the data-centric security company, and the Estonian eHealth Foundation to secure the health records of one million Estonian citizens using its proprietary Keyless Signature Infrastructure® (KSI®) is a classic example of blockchain technology.
Healthcare Frauds Waste and Abuse: An estimated $455 billion in global healthcare spending is lost every year due to fraud, waste, and abuse. As countries move towards universal health coverage via health insurance, health insurance fraud and claims leakages continue to concern insurers globally including those in the Middle East. Industry estimates suggest that about 10 per cent of insurance claims in Middle East are fraudulent leading to waste and increasing cases of medical claim. For example, Saudi Arabia insurance companies are rejecting about 25 per cent of medical claims from hospitals and other service providers on the grounds of fraud. Blockchain-based systems can provide realistic solutions for minimising these medical billing related frauds. By automating the majority of claim adjudication and payment processing activities, blockchain systems could help to eliminate the need for intermediaries and reduce administrative costs and time for providers and payers. Recently announced limited availability of Change Health’s medical billing management blockchain solution called the “Intelligent Healthcare Network”, is a great example, which at its current capacity is processing 550 transactions per second.
Precision Medicine and Population Health Research: The precision medicine concept promises a paradigm shift in the care delivery arena. It aims to integrate personalised health data from direct (e.g., omics/health vitals) and indirect (e.g., environmental/exogenous) sources, targeting individuals’ health and well-being. However, with personalised health data being the “Holy Grail” for precision medicine practice, it is not unique to some of the prevailing challenges involving health data interoperability, privacy, ownership, and security. Additionally, current legal and ethical frameworks for health data exchange were built with a very different generation of medical and research practices in mind and raise some serious challenges for seamless exchange of personalised data to population-based genomic studies and research commons. Furthermore, blockchain technology, with its ubiquitous security infrastructure for seamless health data exchange, promises to drive unprecedented collaboration between participants and researchers around innovation in medical research in fields such as precision medicine and population health management. Furthermore, the trusted digital workflow of blockchain technology will promote Research Commons and remunerative models for data sharing and crowdsourcing-based research models. For example, emerging start-ups such as Encrypgen LLC, BitMED are working on blockchain-based patient-centric platform that would allow individuals and patients to securely grant access to their personal health information to researchers and pharma clinical trials sponsors and get rewards or even free telehealth consultation.
Emerging technologies outside and within healthcare are converging (see figure 1), along with the three technologies of AI, IoMT and Blockchain, that together are creating a significant impact on the healthcare industry in general. Needless to say, the state of healthcare by 2025 will be very different from the picture today, and the focus then will be on the patient to get better outcomes at lower costs and with an improved patient experience.
References available on request.