James F. Jordan, President & CEO, Pittsburgh Life Sciences Greenhouse
Sr. Director, Health Care & Biotechnology Programs
Distinguished Service Professor in Health Care & Biotechnology Management
Carnegie Mellon University

It might come as a surprise to some that over the past 100 years, U.S. Presidents from both parties have been concerned about health care; how it’s offered, who receives it, how it’s priced, and how to measure its effectiveness. Franklin Pierce, Theodore Roosevelt, Franklin Roosevelt, Harry Truman, Lyndon Johnson, Richard Nixon, Jimmy Carter, Bill Clinton, George Bush, Barack Obama and Donald Trump — all put forth initiatives.

Historically, health care providers have been compensated on a fee-for-service basis. Quality measurements were based on the results of a procedure. Financial success was measured by the output of services and revenue. The system was motivated to measure at the procedural level (micro) versus the health systems level or at the level that really matters, population health (macro). Unfortunately, the unintended consequence of this practice is the promotion of volume over outcomes.

Why we need to shift to a value-based care model

The result of this type of behavior is evident when one tracks the average year-to-year growth in national health care expenditure (NHE) by decade. The table outlines the last six decades, and we can see double-digit growth through the 1980s and then a dramatic drop in 2010 through 2017.

Why did NHE growth slow down dramatically in the past decade? The Affordable Care Act (ACA), passed in 2010, seems to have influenced the slowing of growth. The details and debates on the components of the ACA, the pros and cons, are beyond this short article. However, the numbers are indisputable.

The ACA focuses and realigns the incentives of health care to be measured on a basis of value, which requires improving quality and increasing access, all while decreasing costs. This is the true definition of value-based health care.

So why must we continue on the path towards value-based care? The real concern is when we compare the growth of the economy as a whole, called gross domestic product (GDP), to the growth of health care expenditure. Over the same six decades, health care expenditure growth is simply outpacing the growth of our economy, consuming a larger percentage of our fi nancial output. In the last decade, while the rate of health care grew by 4%, GDP grew only 2.15% — nearly half the rate of NHE.

This inhibits us from investing in other activities as a nation, such as research and development to keep the U.S. competitive. To equate this to a personal budget, if electricity and rent take up a greater and greater percentage of your budget each year, it limits your ability to invest in an education, save money or increase discretionary spending.

Social determinants of health are critical to achieving value-based care

So now that we know why we need to achieve value-based care, how do we do it? To deliver value-based care, we must know more about patients. Understanding what causes disease in the body is a critical first step.

There are numerous types of diseases: infectious, hereditary, psychological and diseases of defi ciency. Our environment can trigger disease (called epigenetics) and can also be influenced by other social determinants, such as lack of education and poor individual behaviors. Social determinants of health are the conditions in which we are born, grow, live, work and age which are influenced by the distribution of money, power and resources at global, national and local levels.

For example, Chronic Obstructive Pulmonary Disease (COPD) is a progressive lung disease making it harder to breath and decreases one’s long-term health. Personal behavior, like smoking, and environmental influences, like lung irritants such as air pollution and chemicals in the work place, can causes this disease.

When you shift the paradigm of the health care system to value, and health care delivery is no longer motivated to focus on “health events,” a desire to incorporate social determinants of health and genetics becomes extremely important to value measurement. To effectively manage disease, you need to know all of the aspects that influence an individual, and that requires the ability to amass a large amount of data and analyze it efficiently. This is where big data and data analytics will play a critical role in helping us to transform health care as we know it.

Advanced Information Technology: Leading the way to value-based health care

In 2017, consumers spent $333 billion on prescription drugs. There has been a national outcry to decrease drug prices, but why are they so expensive in the first place? One of the reasons is the process of how drugs are discovered. Do you recall from your high school education the scientific method? It’s basically a six-step process: (1) ask a question, (2) research, (3) construct a hypothesis, (4) test the hypothesis, (5) analyze the data and draw a conclusion, and (6) share the results to start the learning cycle again. This is what a typical drug development process looks like. It’s costly because of the long learning cycles and high failure rates. But what if we could shorten timelines with better input? And what if we could determine failure sooner to decrease costs and redirect resources?

This is just what big data, machine learning and artificial intelligence (AI) are striving to do. Increased data allows the application of data analytics to improve the efficiency in care delivery, and the application of AI makes our decisions more timely and more accurate. Machine learning uses multiple AI algorithms to parse and learn for itself. Evidence of this eventuality can be seen today in drug trials whose hypotheses are constructed by applying AI to known patient-derived trial data.

Few people appreciate that the biotechnology, diagnostics and pharmaceuticals sectors are linked in decreasing the cost of prescription drugs and making drug discovery and commercialization more efficient.

Biotechnology uses living cells as tools to mirror the workings of normal and diseased cells to increase drug discovery and predict early failures. Why is early failure prediction so important? Because the cost of failure is inevitably spread into the price of marketed drugs.

Another data-driven trend is precision medicine (PM). PM uses genetic and molecular profi ling data to match a patient with the treatment that provides the most therapeutic benefit. Using these tools, we can uncover disease patterns with the goal of getting the right treatment to the right patient, catching disease earlier, treating it more effectively, and saving the system money.

Will industry champion a health care paradigm shift?

Not only is advanced technology like AI and machine learning transforming health care, but also industry is combining to advance new ways of looking at the health care system as a whole.

Many large companies self-fund their health insurance. Instead of paying an insurance company to cover their employees, these companies assume direct financial responsibility for the cost of enrollee medical claims.

In January 2018, Amazon, Berkshire Hathaway and JP Morgan Chase announced a major collaboration to build an independent, nonprofit health care company. Haven is focused on improving outcomes (including access and quality) and reducing costs.

Why is this important? Today’s health care delivery is a kluge of historic system architectures and internal cultures that are frequently hard to change. By partnering and funding health care delivery, Haven is not burdened by infrastructure, not burdened by cultures, and will only fund those activities that optimize outcomes. Although it’s too early to know, could this be the catalyst that changes the face of insurance and health care delivery?

One thing we know, the past will not be our future

Presidents for 100 years have been concerned about health care, and in 2010 a convergence of economic pressures and political forces passed the ACA legislation. This legislation has had impact and was intended to evolve over time. It established goals focused on outcomes, allowing time, technology and disruption to avail themselves and continuously improve the system.

Our most recent continuous improvement cycle recognizes that social determinants of health may be one of the biggest contributors to improvement. Although advanced technologies can help gather new information and improve decision-making, our historical infrastructure and cultures can deter disruptive change. Will the large, self-funded companies and partnerships such as Haven be that irritating grain of sand in the oyster that produces a pearl? Time will tell.