What Is AI-First Healthcare
Editor’s Note: AI has had a transformative effect on many industries, the healthcare industry included. In this concise yet insightful piece, Kerrie Holley, SVP and Technology Fellow at Optum, and Dr. Siupo Becker, VP of Health Care Strategies at UnitedHealthcare, explore the underlying foundation behind AI-First healthcare.
There is so much excitement involving AI in healthcare, but what exactly is AI in healthcare supposed to fix? People look to AI to predict future disease, prevent disease, enhance disease treatment, overcome obstacles to health care access, solve the burden of overworked and burnt out clinicians, and overall improve the health of people while decreasing the cost of healthcare. While some of this is achievable, AI is not a miracle panacea to all health and healthcare related problems.
Roy Amara, a previous head of the Institute of the Future, coined Amara’s Law, which states, “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” One of the major myths regarding AI is that AI will replace physicians and other healthcare providers. AI relies upon the knowledge base provided by trained and experienced clinicians. AI cannot replace the “care” aspect of human interaction and its associated documented therapeutic effect. AI does not have the capability to determine the best solution when a holistic review of a patient would recommend an approach that relies on human creativity, judgment and insight. For example, take an otherwise healthy ninety year old patient who develops an imminently treatable cancer. Logic and current medicine would support aggressive treatment to destroy the cancer. The human aspect comes into play when this same patient lets their clinician know that they are widowed and alone, and although not depressed, feel they have lived a full life and decline treatment. AI and most physicians would argue for treatment. Patient autonomy and holistic review of an individual’s wishes and autonomy in their healthcare decisions takes priority here and would have been missed by an autonomous AI agency operating without human oversight.
AI can apply counterintuitive strategies to health management, but the steps from raw data to decision are complex and need human perceptions and insights. The process is a progression, starting with clinical data, obtained from innumerable sources that is built and developed to become relevant information, which is then used and applied to populations and/or individuals. The transformation from raw data to insights to intelligence is a process that is guided by clinicians working with data scientists using AI. The clinical interpretation of data is dependent upon humans and their understanding of disease processes and its effect on the timeline of progression of disease that molds this early knowledge. Algorithms for disease management, identification of risk factors predicting the probability of development of disease, all this is based on human understanding and interpretation of the disease process and the human state. The use of AI and clinicians activities are intertwined and together the potential for improving health is remarkable.
AI has inherent benefit and broad application, but it is AI in collaboration with the human interface which allows AI tools to be so impactful. AI will not replace health care providers, but is a powerful tool to augment disease identification, and management along with the physician.
Let’s explore some of the ways that AI and healthcare providers have been able to work together, while also dispelling the myths that AI can do it all on its own.
AI Will Cure Disease
AI is not a replacement for a medicinal cure that may one day end diseases (e.g., coronary artery disease or cancer); however, advances in AI, the massive accumulation of data (i.e., Big Data), and data sharing in health care could lead to what does. Some people believe that if AI can be used to predict who is at risk for disease, then we can intervene and change behaviors or start treatment that would circumvent the disease from ever becoming present. Of course helping people avoid getting a disease is not the same as curing a disease. Defining what we mean by a cure can be confusing, and is never more evident than in certain diseases, such as Human Immunodeficiency Virus (HIV). Magic Johnson, NBA All star proclaimed he was cured from HIV, because doctors were unable to detect virus in his body after, and with ongoing treatment for HIV. Without the anti-retroviral medications, HIV would have increased in number and once again been found in his body. Was he ever truly cured? For certain diseases what defines a cure is not well defined. However, preventing a disease for an individual is better than trying to cure that disease. AI can provide clinicians with more and better tools, augment a clinician’s diagnostic capabilities by analyzing a holistic picture of the individual patient with broader data streams and technological understanding of the disease process and who is both at risk and will be most greatly impacted.
AI Will Replace Doctors
AI will not replace doctors now or in the near future. There are many tasks that AI can do better than a doctor but rarely if at all will AI replace entire business processes, operations, occupation or profession. The most likely scenario is doctors in the foreseeable future will transition to a doctor who wields AI, understanding how to use AI tools for delivering more efficient and better clinical care. AI today provides a lot of point solutions and its opportunity to improve diagnostics is significant. Treatment pathways and even many diagnostics today require decision making something AI is not good at.
A practical problem exists in that AI must live in our current brownfield world where several barriers must be overcome for AI replacing doctors. Today we have a proliferation of systems that do not integrate well with each other. For example, a patient who is cared for at a hospital, urgent care center or provider office may have his/her data spread across several different systems with varying degrees of integration and today a doctor’s ability to navigate the healthcare system is critical to patient care.
The reality is there is not going to be a computer, machine or AI that solves health care, just like there isn’t one solution to all banking, retail, or manufacturing. The path to digitization differs based on clinical speciality and most likely will occur one process at a time within domain or speciality. AI systems are here and on the horizon for assessing mental health, diagnosing disease states, identifying abnormalities and more.
AI Will Decrease Healthcare Costs
US health expenditure projections for 2018–2027 from CMS [cms.gov] show that the projected average growth rate on health care spend is 5.5% with expectations of meeting 6 trillion in spend by 2027. Looking at these numbers, it’s clear that healthcare spending will outstrip economic growth. All components of healthcare are projected to increase at exceedingly high annual rates over the next decade. For example, inpatient hospital care, which is the largest component of national health expenditures, is expected to grow at an annual average rate of 5.6%, which is above its recent five year average growth rate of 5%. AI alone won’t fix these problems but it can help with cost containment and cost reduction.
The myth about AI and healthcare costs is thinking that AI will reinvent or overturn the existing healthcare or medical models in practice today. Or that AI will transform or revolutionize the healthcare industry triggering enormous savings. The reality is that AI as a general purpose technology will be transformative. Tremendous evidence abounds showing that the big technology companies and startups will transform how healthcare is done. AI will be the tool of trade making many of these transformations possible. You might see this as splitting hairs but the point is that the problems facing healthcare lie with resistance to change, historical inefficiencies and inertia, lack of cooperation for the greater good by companies designed to compete with each other and the lack of a game changing technology. Now we have the game changing technology, AI.
So, what does AI-First healthcare really mean?
AI first for healthcare means adopting direction, strategy for AI that goes beyond just machine learning. A common industry definition of AI may not exist nor will it be a necessity for advancing an AI First agenda for healthcare. Companies without an AI strategy operate like a machine coasting downhill with no direction, no goals, no plans on how to use AI for making their business work better, creating awesome experiences, making digitization work or making their products better.
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Kerrie Holley is focused on advancing UnitedHealth Group (UHG) in the adoption of emerging technologies — including machine learning, graph databases, deep learning, natural language processing, IoT, virtual reality, genomics, blockchain, and virtual assistants — with a heavy focus on Artificial Intelligence. Kerrie leads an engineering team committed to applying and incubating emerging technologies to make the health care system work better and help people live healthier lives. Dr. Siupo Becker joined Optum/UnitedHealthcare in 2016, focusing on population health management and data analysis focusing on application to improving health care and quality outcomes. She has since been named as Vice President of Health Care Strategies within UnitedHealthcare and drives nationwide health care initiatives that impact the quality and control of health care costs.
