AI and Robotics Join Forces to Revolutionize Health Care

Health care is one sector of the economy where the second wave of the Fifth Techno-Economic revolution will make an especially deep impact on the lives of almost every human being.

Price Waterhouse Coopers, or PWC, recently identified five converging trends leading to an era in which AI and robotics will dominate health care.

First and foremost is the escalating health care value challenge that all countries across the globe face. It involves demands created by chronic disease, rising costs, an aging population and limited financial & human resources. Ironically, our economies are continuing to invest in facilities and equipment that were built to address a completely different set of healthcare needs and are not designed to cope with the new demand profile. For instance, a "hospital-centric system" deals very well with serious health episodes that require days or weeks of acute care for very ill people. But it was never intended to deal with large numbers of people whose conditions are chronic, complex and require treatment for the longer term.

Second, the past decade has seen an explosion in the amount of health data that is available to us. For example, for a skin specialist there are 11,000 new dermatology articles published every year. In 2013, it was estimated that the volume of health-related data had reached over four zettabytes; that's four trillion gigabytes (or 1021 bytes). And there are those who project it will rise by a factor of ten times by 2020, and, to beyond a yottabyte (or 1024 bytes) by 2040. Furthermore, fully 80% of this extraordinary amount of data is unstructured, meaning that it's not contained in a database or some other type of data structure. Staying current with and being able to access this data is simply beyond the scope of any human individual, no matter how capable or intelligent.

Third, information technology development in healthcare has been rapidly moving from products to platforms to solutions. Past decades have focused on the innovation provided by medical products delivering evidence-based care. The present decade is one of medical platforms focused on real-time, outcome-based care. And the next decade is moving towards medical solutions - using AI and robotics, as well as virtual and augmented reality - to deliver intelligent solutions for both evidence-based and outcome-based health care and focusing on collaborative, preventative care. This confluence of technology-based products, platforms and solutions is leading to the previously impossible world of "precision medicine," personalized at the individual level. This new paradigm may even enable doctors to predict and thereby prevent disease from ever occurring.

Fourth, information technology has obviously had an enormous impact far beyond the developments in healthcare. The explosion of digitally enabled, wireless connectivity across increasingly mobile devices has created an increasing democratization of access to healthcare. Some of the most powerful AI tools are already embedded in Android or iOS devices. Harnessing this technology is providing consumers with the data and information they need to proactively manage their own health and wellness, and to make better, more informed decisions in partnership with their healthcare providers.

Finally, there's the trend toward the general-public becoming active participants in their own health and wellness. Significantly, this participation level has now reached critical mass. The explosion of technology and the increasing ubiquity of the Internet of Things is bringing about breakthroughs that are erasing healthcare boundaries and enabling care anywhere and everywhere. Furthermore, consumer acceptance is increasingly extending into the areas of AI and robotics, which are the subject of this segment.

According to PWC, market opportunities for AI and Robotics in health care can be broken down into eight functional areas: keeping well, early detection, diagnosis, decision-making, treatment, end of life care, research, and training. Just the AI component across these eight areas is expected to grow to $6.6 billion worldwide by 2021.

Let's start with keeping well. One of AI's biggest potential benefits is to help people stay healthy so they don't need a doctor, or at least not very often. The use of AI and the Internet of Medical Things (or IoMT) in consumer health applications is already helping people to manage their own healthcare and to keep themselves well through healthier living. For example, the Smart Belt has a built-in mechanism that alerts the person when they overeat. It relies on a magnetic sensor to track waste size and tension to determine when the users may have over eaten and alerts the wearer. Further, IBM has announced three new consumer-focused partnerships, one of which is with Under Armour which will use Watson to power a cognitive coaching system.

These applications and others all encourage healthier behavior in individuals and help with the proactive management of a healthy lifestyle. It puts consumers in control of their health and well-being. Additionally, AI increases the ability for healthcare professionals to better understand the day-to-day patterns and needs of the people they care for, and with that understanding they are able to provide better feedback, guidance and support for staying healthy, even as the sheer volume of data becomes increasingly difficult for humans to deal with, or make sense of.

Early detection is another enormous area of opportunity. AI is already being used to more accurately detect diseases, such as cancer, in their early stages. Increased accuracy is key. Just consider one example: according to the American Cancer Society, 12.1 million mammograms are performed annually in the US, but a high proportion of these mammograms yield false results, leading to 1 in 2 healthy women being told they have cancer. The use of AI is enabling review and translation of mammograms 30 times faster with 99% accuracy, reducing the need for unnecessary biopsies as well as reducing the uncertainty and stress of a misdiagnosis.

The proliferation of consumer wearables and other medical devices combined with AI is also being applied to oversee early-stage heart disease, enabling doctors and other caregivers to better monitor and detect potentially life-threatening episodes at earlier, more treatable stages.

On the horizon, Microsoft is developing computers programmed for use at a molecular level to start fighting cancerous cells as soon as they are detected. They are also doing research into using AI to interpret online search engine behavior, for example, at the point where someone might research symptoms online long before they approach their physician.

Now, consider the critical area of diagnosis. It's estimated that 80% of health data is invisible to current systems because it's unstructured7. IBM's Watson for Health uses cognitive technology to help healthcare organizations unlock vast amounts of health data and use it to drive to a sound diagnosis. Watson can review and store far more medical information, including every medical journal article, every case study of treatment, and every symptom from around the world exponentially faster than any human. And it doesn't just store that data, it's capable of finding meaning in it. Unlike humans, its decisions are all evidence-based and free of cognitive biases or overconfidence, enabling rapid analysis and vastly reducing or even eliminating misdiagnosis.

Similarly, Google's DeepMind Health is working in partnership with clinicians, researchers and patients to solve real-world healthcare problems. The technology combines machine learning and "systems neuroscience" to build powerful general-purpose learning algorithms into neural networks that mimic the human brain.

Between diagnosis and treatment lies the crucial area of "decision-making" in which the patient and physician decide which course of treatment to follow. Improving care requires the alignment of broad-based data analysis with appropriate and timely decisions, and predictive analytics that can support clinical decision-making and actions as well as prioritize tasks.

Using "system-dynamics-driven pattern recognition" to identify patients at risk of developing a condition - or seeing their health deteriorate due to lifestyle, environmental, genomics, or other factors - is another area where AI is beginning to take hold in healthcare. For example, in an extension and application of AI, PwC's Bodylogical system captures learning through mechanistic modeling to digitally represent the physiology of the human body. This enables true-life simulations to predict the likely progression of chronic diseases in the future, based on today's actions and interventions. These simulations help pharmaceutical companies, providers, payers, employers, researchers and consumers better understand how daily life choices and therapeutics impact individual patients or population health outcomes and associated costs.

Once the major decisions about the course of treatment are made, execution and monitoring of the treatment are key. Beyond scanning health records to help providers identify chronically ill individuals who may be at risk of an adverse episode, AI can help clinicians take a more comprehensive approach for disease management, better coordinate care plans and help patients to better manage and comply with their long-term treatment programs.

For instance, AiCure has built an application to monitor patients with long-term conditions and help them adhere to medication intake. The application uses a visual recognition system to identify the patient's face, the medication they're taking, and confirm ingestion. The data is then sent back to the care provider or to a pharmaceutical company conducting a clinical trial.

It's here in the treatment phase that robots are likely to have the biggest impact. Robots have been used in medicine for more than 30 years. From the first programmable universal machine for assembly (or PUMA), used in urology surgery in the 1980s, to the da Vinci robot, the most widely used robotic system in clinical use today, robots have evolved to perform a wide range of tasks and functions. They range from simple laboratory robots to highly complex surgical robots that can either aid a human surgeon or execute operations by themselves. In addition to surgery, they're used in hospitals and labs for repetitive tasks, in rehabilitation, physical therapy and in support of those with long-term conditions. RoBear is a nursing-care robot that is able to lift and move patients in and out of bed into a wheelchair, helps those who need assistance to stand, and even turns patients in bed to prevent bedsores.

Inevitably, some patients transition from normal treatment to end of life care. We are living much longer than previous generations, and as we approach the end of life, we are dying in a different and slower way, from conditions like dementia, heart failure and osteoporosis. It is also a phase of life that is often plagued by loneliness.

Robots have the potential to revolutionize end of life care, helping people to remain independent for longer, reducing the need for hospitalization, human caregivers and "care homes" by performing routine tasks such as taking vital signs and prompting for medications. AI combined with the advancements in humanoid design are enabling robots to go even further and have conversations and other social interactions with the people; this keeps aging minds sharp and solves helps solve the problems of loneliness and isolation. For instance, Kompai robots talk, understand speech, remind people of meetings, keep track of shopping lists and play music. Developed to assist the elderly in their own homes, they are able to monitor them for falls and other health parameters, provide alerts, and connect them via video-conference with healthcare providers, friends and family.

The foundation upon which modern medicine rests is, of course, research, and this is the aspect of health for which AI is most well-suited. Every one of us has taken medications prescribed by our doctors for symptoms or illnesses at some point in our lives. Those with chronic diseases often depend upon medication to manage what might otherwise be debilitating diseases. But the path from the research lab to patient is a long and costly one.

According to the California Biomedical Research Association, it takes an average of 12 years for a drug to travel from the research lab to the patient. Only five in 5,000, or 0.1%, of the drugs that begin pre-clinical testing ever make it to human testing and just one of these five of those is ever approved for human usage. Furthermore, on average, it will cost a company US $359 million to develop a new drug from the research lab to the patient.

Drug research and discovery is one of the more recent applications for AI in healthcare. By directing the latest advances in AI to streamline the drug discovery and drug repurposing processes there is the potential to significantly cut both the time to market for new drugs and their costs, not only for the labs who develop the drugs, but for those people whose health depends upon them. One of the best examples is Pharma.AI, the Pharmaceutical Artificial Intelligence division of Insilico Medicine, a bioinformatics company. It's located at the Emerging Technology Centers at Johns Hopkins University and was launched in March 2016. They focus on drug discovery programs for cancer, Parkinson's, Alzheimer's, and other aging and age-related health issues. However, medical research is not just about finding new drugs to combat disease. It also includes research into disease itself, with the ultimate goal being to inoculate against or completely eliminate disease. A great example is Meta, a Canadian start-up that uses AI to quickly read and comprehend scientific papers and then provide insights to researchers. It was bought by the Chan Zuckerberg Initiative in January 2017 as part of the charitable foundation's mission to eradicate disease.

Finally, it's training that enables physicians and other medical professionals to make optimal use of all of the available resources. AI allows those in training to go through naturalistic simulations in a way that simple computer-driven algorithms cannot. The advent of natural speech in technology and the ability of an AI computer to draw instantly on a large database of scenarios means AI can respond to questions, decisions or advice from a trainee and can challenge them more effectively than a human can. And the training program can learn from previous responses from the trainee, meaning that the challenges can be continually adjusted to meet their learning needs.

Importantly, training can be done anywhere with the power of AI embedded on a smartphone. For example, AI can provide "quick catch-up sessions," in response to a tricky case in a clinic or while traveling.

To date, the main way new technologies have been used to augment training is through virtual reality (VR). Combining VR with AI will offer boundless opportunities for extending the skills of trainees in a targeted fashion.

AI and robotics are redrawing the healthcare landscape. The wave of innovation being driven by these technologies is not only transforming clinical decision-making, patient monitoring and care, and surgical support, but fundamentally changing how we approach healthcare for our populations. We are already experiencing this shift as we focus on integrating prevention and wellness into our health systems and we are heading towards a time when people work more proactively with their healthcare professionals across illness and wellness.

This shift will inevitably alter many of the roles of healthcare professionals. As these new technologies and perspectives become more integrated within and across our healthcare systems and more ubiquitous among the population, the skills that are required by our new health landscape may well be markedly different than those that are needed today. We currently train our doctors and nurses in the context of health systems that may no longer exist once they graduate medical school. An understanding of technology will be imperative.
Programming, data analytics and human behavior may well be as much a part of the medical curricula as anatomy and neurology.

AI and robotics technology will free up clinicians for other types of work that enable them to spend more meaningful time with their patients. Rather than a profession of 'healthcare providers', AI and robotics will open opportunities for more holistic patient care, with a focus on keeping patients healthier longer, instead of primarily treating illness.

AI will likely challenge the traditional role of the doctor. But, rather than worrying if these technologies are going to replace doctors and other healthcare professionals, we should be considering more deeply their wider role in the entire healthcare continuum with a clear eye towards training our healthcare workforce for the future.

In short AI and robotics will dramatically enhance the cost-effectiveness of health care. And the opportunities for patients, health care professionals, and investors are enormous.

Given this trend, we offer the following forecasts for your consideration.

First, over the next decade there will be widespread acceptance of AI and robotics in major health care roles by patients, worldwide. Exactly one year ago, in November 2016, PWC surveyed 12,000 people in 12 countries. The findings of the survey revealed three key themes impacting consumers' willingness to engage with AI and robotics in their health care:

People are increasingly willing to engage with AI and robots if it means better access to healthcare, as seen with the UK Health System and Medicaid, free health care is worthless if you can't get it when you need it;
Speed and accuracy of diagnosis and treatment is a critical factor in this willingness; and
Trust in the technology is vital for wider use and adoption, even as the 'human touch' remains a key component patient want in the healthcare experience.

Second, as with most truly disruptive technologies AI and robotics in health care will first achieve widespread adoption among less affluent consumers who have fewer alternatives and subsequently come to dominate more sophisticated markets. Nearly 30 years ago, Harvard's Clayton Christensen found that most truly disruptive technologies were adopted by nontraditional consumers for whom the initial offerings were "good enough." The PWC research clearly showed that in consumers in countries currently lacking quality health care, like Nigeria, patients are eager to adopt AI and robotics in every area from prevention and diagnosis to surgery. Patients in affluent countries, with high quality medical care, like the UK and Germany, are far less enthusiastic.

Third, several concerns will need to be resolved before governments, health care professional, patients, technology developers, and institutional decision makers embrace this new world of healthcare.

For governments, the big challenge is creating quality standards and a regulatory framework which are applicable to and obligatory for the entire healthcare sector, as well as the appropriate incentives for adopting new approaches. Linking regulations to facilities or humans, will naturally inhibit adoption. Also, AI and robotics should be seen as making healthcare more accessible and affordable. Otherwise there is a risk that these technologies may become limited to the well-off.
For healthcare professionals, the big challenge is understanding how AI and robotics have the potential to work for and with them in a medical setting as well as throughout the healthcare eco-system, and be open to change. If clinicians are not as good as AI and robotics at monitoring, diagnosis, decision-making or surgery, then what is the unique role for the human practitioner, and how can they prepare for it?
For patients and the general public, the big challenge is becoming more accustomed to artificial intelligence and robots and discovering the benefits for themselves. Although, we suspect just as they have already adopted AI in their everyday lives, health technologies will similarly be taken up with alacrity.
For the private sector developing AI and robotics solutions, the big challenge is ensuring that solutions resolve the big issues of demand and resources that every health system faces. In essence, by providing AI and robotic driven solutions, the private sector has the opportunity to disrupt healthcare for the good.
For decision-makers at healthcare institutions, the big challenge is developing an "evidence base," measuring the success and the effectiveness of the new technology; and implementing it in phases, while prioritizing and focusing on what consumers want and need.