How the Human-to-Machine Bond is Transforming Health Care

The biggest problem the United States health care system faces is preventable disease. We do not have enough doctors, nurses, or health coaches to fix it.

Yes, we have a doctor and nurse shortage; however, the larger issue is that the treatment or prevention of these types of diseases requires significant behavior and lifestyle changes, which are achieved through extensive coaching, carefully timed intervention, and constant monitoring. All of these are very hands-on, human activities.

Even the best, most attentive health care providers simply can’t be there for a patient around the clock, to catch every bad habit or reinforce every positive behavior. Many make the argument that we need to increase federal funds and train more nurses, license more physicians, and deploy more health coaches. Yes, we need to do these things, but it’s not going to be enough. Increasingly, people are becoming more comfortable interacting with machines than they are with humans.

Traditional approaches, even if they are wildly successful, only ensure that more people get to see their doctor in a timely fashion. They don’t do anything to help doctors spend more time with each patient. It’s time to turn to technology to help us do what it does best: scale. Artificial intelligence (AI) has evolved to the point that it can significantly augment the work done by physicians, pharmacists, and health coaches.

AI-powered technologies can fill in the gaps between appointments by reminding patients to take their medications according to their schedule, influencing and rewarding behavior change at exactly the right moment, and even intervening when something in the treatment plan is off.¹

AI is capable of learning and growing with a patient too, so it can adapt and adjust based on the patient’s individual needs, schedule, and disease. The preventable disease problem we’re facing in health care today can be solved by a deepening relationship between humans and AI. If this sounds futuristic, it is… sort of.

The technology already exists, and is deployed in other arenas, such as finance and business intelligence. But in health care, there’s a human and psychological barrier: can we trust AI with our health? Our health data?

In a recent study conducted by Next IT Healthcare and Kaiser Permanente, researchers found that patients are increasingly comfortable with, and trusting of, AI-driven virtual health assistant (VHA). In fact, many patients who interacted with AI-driven technology in a doctor’s office were inclined to disclose more information than they would otherwise tell their doctors. What does this new human-to-machine bond make possible for our health care system?

The implications for health care are profound.

Better data

When patients interact with a VHA on their phone, desktop, or tablet, human caregivers get new context that has heretofore been very difficult to obtain, particularly in real-time. VHAs are perhaps the best collection mechanism for data addressing patient medication questions, treatment plan adherence, and accessing how patients are feeling day-to-day.

Consider what happens when we can correlate this data with other patient-generated data, such as data from wearables, home monitors, scales, and environmental sensors. Health care providers can use this data to better understand when to intervene, to predict and prevent relapses, and to create a custom treatment plan specific to a patient’s routine, that also evolves with the patient. The value of high-fidelity and real-time patient-generated data is immense, and will be transformative.

Systemwide cost benefits Around-the-clock access to what is essentially a nurse-less hotline can reduce the burden on doctors and other care providers. They can ensure that when human interactions are needed, they are as impactful as possible. Imagine a patient needs help understanding the side effects of a drug they are taking.

A VHA can walk patients through the known side effects, and identify whether they are experiencing any of those effects. If they are, the virtual health assistant can determine the severity of side effects by asking a series of questions. The technology can then triage and route the resulting information to a live health care provider, who can intervene immediately, if needed, and help patients determine if they need a trip to the emergency department, or can treat the symptoms at home.

Early detection prevents potentially costly complications while patients would otherwise be waiting for an office visit. But the technology can also reduce the occurrence of unnecessary office visits. Whether there’s a problem or not, this technology can drive efficiency. Personalized treatment “Doctor’s orders,” treatment plans, and standards of care are rooted in sound science.

But studies involving hundreds, or thousands of subjects, are rarely tailored to the individual, with instructions such as eat vegetables 3 to 4 times a day, exercise 3 to 5 days a week, take your pills twice a day for 2 weeks. Yet, adherence to these kinds of recommendations are dismal because there is no guidance on how a patient can achieve the study’s goals and why, particularly given their existing lifestyle and behaviors.

A VHA is able to spend more time with patients than even the best and most attentive health care providers. By using motivational interviewing, the VHA can collect valuable information and insights, both passively and proactively. It can therefore learn patient preferences, habits, and routines, and adapt treatment plans to match.

For example, instead of prescribing a medication, and saying a patient needs to take it twice a day, 12 hours apart with food, a virtual health assistant can instead learn when you generally eat breakfast and dinner, when you wake up and go to bed, and help you determine a specific schedule that fits your lifestyle and improves the outcome.

Regulation and policy implications The human benefits that VHAs can bestow on the patient population are clear. But are there relevant policy issues that VHAs can help address too? First, it should come as no surprise that the debate around health care has centered on its fiscal impact.

For example:

• According to the CDC, the World Health Organization has estimated that by 2020, the number of Americans affected by at least one chronic condition requiring medication therapy will grow to 157 million individuals. Additionally, the direct economic cost associated with nonadherence to medication is estimated at $100 billion to $289 billion.²
• Chronic diseases are responsible for 7 of 10 deaths each year, and treating people with chronic disease accounts for 86% of our nation’s health care costs.³
• From 2015 to 2025, health spending is projected to grow at an average rate of 5.8% per year, and will grow 1.3 percentage points faster than the gross domestic product per year over this period.⁴

Only recently have policy makers begun to examine the benefits of how integrating health care professional services can create an improved outlook on cost containment and patient outcomes. Prior to the enactment of the Affordable Care Act (ACA), patients would receive siloed treatment, as there would be no coordination of care for a patient that transitioned from acute to post-acute care settings.

It is during this vital time that patient questions go unanswered, and the risk of nonadherence rises, therefore driving up health care costs. However, to tackle this problem, the ACA has created alternative payment models, such as bundled payments, that are forcing providers to share more risks in an effort to receive a greater piece of now “shared” reimbursement. As a result, providers must work together to demonstrate how they have affected a patient’s positive outcome, and thus, created value for the health care system.

The best way to do this is through data sharing. This is an area where VHAs have the greatest opportunity. The origins of data sharing as a way to tame health care spending can be seen through the enactment of the Health Information Technology for Economic and Clinical Health (HITECH) Act. The law’s enactment in 2009, along with the solidification of the importance of electronic health records in the ACA, set the stage for physicians and hospital providers to receive reimbursement incentives from the US Centers for Medicare and Medicaid Services for those who are successful in becoming “meaningful users” of electronic health records.

If providers have not found a way to do this by 2015, they would soon find themselves subjected to penalties under Medicare. As providers continue to struggle with how to implement electronic health records into their practices, perhaps they are overlooking the simplicity of AI-powered solutions. More than ever, consumers are becoming more involved with maintaining a healthy lifestyle using technology, such as fitness apps and telehealth.

Interestingly, about 35% of US adults said they have used the Internet to figure out what medical condition they or someone else might have,⁵ demonstrating a need for on-demand convenience. Utilizing a VHA can not only give health care providers a better look into what works for a patient, but also satisfy policy maker goals.

First, health care costs can be reduced, since a VHA serves as another powerful tool a provider can use in monitoring a patient. Second, the provider community could show records created by the VHA to illustrate they are meeting the “meaningful use” requirements set the by HITECH Act and by putting patients in control of their own outcomes through the use of a tool that can adapt to their lifestyle, this would more likely than not create a potent recipe for cost containment success.

Conclusion

Integrating AI into daily chronic disease management has the potential to solve some of the most burdensome problems facing the US health care system. AI-powered solutions improve engagement with patients, earn their trust in the process, and offer a comprehensive holistic one-stop shop ecosystem from which the patient can manage their health, something the previous generation of health technologies could not accomplish. The human-to-machine bond makes it possible for this new generation of technologies to directly address rising costs, while improving quality-of-life and patient outcomes. Though we’re still in the early stages, and we certainly don’t have all of the answers, we need to pursue this area of innovation with urgency. Imagine a health care system aided by artificial intelligence that is a trusted partner in a patient’s lifelong health care journey. That day, we believe, is just around the corner.

About the Author

RON LANTON III, ESQ is president of True North Political Solutions, LLC. He has over 20 combined years of government affairs and legal experience. This includes activities on the municipal, state, and federal levels of government. Most recently, he worked for a pharmaceutical wholesaler where he created and oversaw the company’s government affairs department, served as their exclusive lobbyist, and advocated for the company’s various health care customers. Prior to that, Ron worked at a government affairs consulting firm in Arlington, Virginia, where he focused on health care, energy, commerce, and transportation issues. He has also clerked for a federal magistrate, was appointed as a municipal commissioner on environmental issues, and has served as consultant to Wall Street firms on financial issues. He has been a featured industry speaker on issues such as pharmaceutical safety and health care cost containment. Ron earned his juris doctor from The Ohio State University Moritz College of Law and a bachelor of arts from Miami University of Ohio. He is also a “40 Under 40” award recipient. He is admitted to practice law in New York, Illinois, and the District of Columbia.