People like to joke sardonically, “When you have a hammer everything looks like a nail.” But the flip side is that when you have a hammer you can build yourself a house on a hill, a fence for your vegetable garden and a bench by the front door, where you can sit and eat a homegrown tomato and look at the view.
A hammer can help create a whole world. From fire to telescopes, technology has always created tools that transform how we see the world and how we live. New tools mean new questions, new answers and new science. If you don’t have a telescope, you don’t think to ask about Jupiter’s moons. And if you don’t have new technologies for collecting and analyzing massive amounts of data, you won’t think to tackle something as ambitious as precision health — a vision of a world with better health.
Building a better world
At Stanford Medicine, the vision of precision health is to anticipate and prevent disease in the healthy and to precisely diagnose and treat disease in the ill. It’s a vision of a future where traditional medicine and population health work hand in hand. And it’s a future where the practice of medicine itself becomes grist for the research mill — where data from the sick and the well together inform traditional medicine — and where one-size-fits-all health-care guidelines are refined to fit the needs of groups of people and even of individuals.
“The United States spends more of its GDP on health care than any other country in the world,” says Lloyd Minor, MD, dean of the Stanford University School of Medicine. “Yet by standard outcome measures such as longevity and infant mortality, the U.S. ranks below many of the most industrialized nations. At Stanford, we’re building a future that can change that, optimizing outcomes for both individuals and whole populations. Instead of racing to cure diseases, we can prevent them before they strike. And by focusing on wellness, we can make a dent in health-care costs. At Stanford, we call this vision precision health, where we focus on helping individuals thrive based on the many factors that together make each person unique, including their genetics and their environment.”
One example of precision health at Stanford is the Children’s Health & Air Pollution Study-San Joaquin Valley program. A collaboration with four public universities and a private consultant, CHAPS simultaneously treats patients and studies their health. The program brings together researchers in immunology, lung biology, developmental biology, population health sciences, health policy and the law. So when people who wheeze come to Stanford for help, they don’t just get a nod and an inhaler. Instead, researchers and clinicians collaborate to discover if a patient has asthma or something else and, if it is asthma, what factors have led to its development. Each patient’s illness contributes to databases about asthma that will help prevent and treat asthma in others.
Precision health is part of a wider movement to tailor both medical care and prevention. A year ago, President Obama announced his ambitious Precision Medicine Initiative. Obama’s initiative will begin by targeting individual genetic strains of cancer. Longer term, the initiative will enroll a million Americans willing to share nearly everything about their health and their daily lives, including information from their genomes, proteins and microbiomes, personal medical records and wearable sensors. New tools from computer science and statistics will manage and analyze the resulting gigantic data sets and help explain why people get ill, how to prevent illness and which treatments work best for whom.
The trick is to find ways to integrate these massive amounts of data into a clear signal doctors and public health experts can use. Making the vision of precision health a reality will require enormous creativity and skill, and Stanford Medicine is home to a nearly perfect combination of such expertise.
“This campus is rich in resources to play in this space,” says Stanford cardiologist and chair of medicine Robert Harrington, MD. “We’ve got great statistics; we’ve got great informatics; we’ve got great computer science; we’ve got great engineering.”
Even at this early stage, Stanford Medicine is moving decisively into the field. It has built alliances with tech companies. It has held a series of town hall meetings and lectures over the past year to discuss and frame the future of precision health at Stanford. And it has formed the Precision Health Committee, composed of hospital and school leaders as well as research and clinical faculty, to plan future research and faculty hires. The school also recently founded the Department of Biomedical Data Science, chaired by professor of biomedical data science and of genetics Carlos Bustamante, PhD.
The merging of medicine and public health
A major goal of precision health at Stanford is to marry two disciplines that have long held disparate perspectives on health and illness: traditional medicine and public health. Public health primarily keeps people healthy, while medicine primarily treats people after they become sick. And public health helps whole populations, while medicine helps individuals.
Professor of cardiology Euan Ashley, MRCP, DPhil, whose medical research focus is on individual patients, says, “The fundamental concept of precision health is the idea of defining disease better in order to target it more precisely. And how do we define disease better? We do it with new technology. If you look at the history of medicine, we’ve always defined disease according to the state-of-the-art tools of the time.” For many years, cardiologists defined heart disease according to the sounds they could hear through a stethoscope, he says. “But when someone invented the electrocardiogram, we started to define heart disease according to the electrical signals from the heart.”
Today, state-of-the-art tools are just as exciting, Ashley says, but now they include things like whole-genome sequencing. “We can now sequence someone’s whole genome for less than a thousand dollars,” he says. “And we can define diseases in great detail, which lets us target subgroups of patients with specific therapies in areas like cancer or cystic fibrosis.”
Throw in more data — such as which proteins a person’s cells express and which bacteria make up the microbiome in their gut — and you are well on your way to knowing everything about their health that you need to know to define diseases and identify treatment targets. Or at least that’s the enthusiastic view of many researchers.
But there’s another point of view from a contingent of researchers equally passionate about the future of health and medicine. Professor of medicine Mark Cullen, MD, says, “I think it’s fantastic that we are cracking the genome, but I would like to crack the life-ome.” Cullen is an expert in population health sciences, an emerging field that expands beyond public health. It not only draws information from large populations to improve the health of groups but also uses the information to help individual patients and to make basic research discoveries.
Cullen says you can learn more about how long people will live from their ZIP code than from their whole genome. For example, the average life expectancy for a child born in Atwater, California, is 87 years, but just 8 miles down the road in the city of Merced, life expectancy is only 78 years.
In the past, Cullen says, public health and medicine were divided by differences in practice and funding. “Physicians had to integrate everything in the patient’s chart with everything they learned in school, and that became the basis for treatment. Physicians and hospitals also received huge reimbursements for taking care of individuals.” Meanwhile, public health experts had to prevent illness in millions of people through national vaccination programs or food subsidies. Per-person funding was typically modest. The groups dealt with different data and lived in different economic worlds.
Then came big changes. With the creation of networked electronic medical records, individual doctors suddenly had access to all the details in a patient’s record. “And while they were at it,” says Cullen, “they could theoretically look at 25 million more records if they were relevant to that one patient.” Population health experts’ eyes lit up at such volumes of data. “So far,” he says, “no one has solved the problem of how to use all that population data at the bedside, but the data are there. And it’s a scramble among the smartest people in the best health-care systems to figure out how to do that most effectively.”
Next came major changes in health-care economic policies. Medicare, for example, began pegging reimbursements for providers to how all the patients in a system were doing, not just individuals. New rules from Medicare include conditions for which up to 30 percent of the reimbursement will depend on population outcomes, says Cullen. “All of a sudden, hospitals like Stanford had to be able to demonstrate that they were controlling diabetes and getting blood pressure down in everyone, not just in one person.”
One model for the melding of medicine and public health is cardiology, which intensively treats cardiovascular disease when people are ill but also prevents disease — with smoking-cessation programs, changes in exercise and diet, and daily aspirin and statins. This two-pronged approach has been so successful that the annual rate of cardiovascular deaths in the United States since the 1960s is down 70 percent.
Precision health aims to achieve similar results in other areas of health. Dean Minor envisions a world where we understand the immune system as well as we understand heart disease. “From four simple tests — total cholesterol level, total triglycerides, LDL and HDL cholesterol — we get a remarkable amount of information about our risk for heart disease,” says Minor. Those four tests tell us not only how likely we are to develop heart disease, but to some extent what we can do about it. “At Stanford, we hope to have an immune system profile that’s analogous to the lipid profile within five years.”
Precision health asks how you apply all the information that’s becoming available — about our genetics, physiology, environment and preferences — to the health of smaller groups of people and individuals. “That’s what I think we’re trying to get at,” says Harrington, who chairs the Precision Health Committee at Stanford Medicine, “and that’s really different from how we currently practice medicine.”
The good, the bad and the data
Putting precision health into practice depends on gigantic databases queried and managed by experts in computation and informatics. But whether that data comes from genomics, biosensors or electronic medical records, it presents challenges that Stanford researchers are tackling one by one.
Some of the richest data comes from the accumulation of years of patient records. But a combination of bias and outright errors can make it difficult to extract useful information from electronic medical records. Some mistakes are just mistakes: A medical-coding error can turn asthma into chronic obstructive pulmonary disease.
Fortunately, algorithms can flag inconsistencies that suggest an error. A person with chronic obstructive pulmonary disease, for example, would likely have a history of pneumonia, a record of an antibiotic at some point and probably an X-ray on file. If those associated conditions, tests and treatments aren’t there, it’s a sign that there’s something wrong with the data.
More insidious, says Nigam Shah, MBBS, PhD, associate professor of medicine, are systemic biases in the data. Medical records serve several purposes, he explains. They help doctors communicate with one another, allow hospitals to get paid, provide documentation in case of a lawsuit and record patient progress. “These uses are not always compatible with each other,” Shah says. “Billing is the one that usually dominates. And that can introduce certain biases.”
For example, says Shah, suppose a researcher wants to know how many men develop urinary incontinence after prostate cancer surgery. In theory, billing codes would show that. But because doctors get paid the same whether the patient has incontinence or not, most physicians don’t take the time to add the code for incontinence. Shah has a clever workaround: “If a patient is incontinent, you bet they will tell their doctor, and the doctor will probably type it out in their note, writing, ‘Patient complains of incontinence.’ And there are only a few ways to misspell ‘incontinence,’” says Shah.
Using EMRs, researchers can also study the practice of medicine itself — for example, looking at what influences physician prescribing practices, how insurance coverage affects patient outcomes, and what factors promote or discourage “upcoding” — practitioners’ tendency to code for more expensive procedures or diagnoses.
But even the best data comes with a tangle of questions and problems. One problem is protecting privacy. While identifying information — such as names, addresses and medical record numbers — can be removed, personal genomic information raises special questions because it is as specific as a Social Security number. Regular announcements of successful hacks of customer accounts at Target and Home Depot, and even the personal email account of CIA director John Brennan, suggest we can’t completely control who sees our data. Shah and others are exploring ways to corral health and medical data so its power can be exploited only for good.
The future of precision health
A hammer is a great tool, but sometimes you want a smaller hammer for fine work. Does this patient need aspirin? How much? Is this patient’s heart attack a result of a genetic defect, or decades of trans-fat-laden doughnuts?
“The way things are now,” Harrington says, “when I’m taking care of patients who’ve had a heart attack, I give them all aspirin. I don’t say, ‘Well, are you one of those aspirin nonresponders, or are you one of those aspirin hyper-responders?’ I just say, ‘The evidence says that by treating a population with aspirin we lower the risk of dying by about 25 percent.’” But that’s not good enough. “We should have systems in place to guarantee that 100 percent of the people who should get aspirin are getting aspirin,” he says. “And if we don’t know what we’re doing, we should be studying that,” he says.
The precision health approach can be applied to public health as well. For example, a major way to improve the health of populations is through better nutrition. But how? To find out, Sanjay Basu, MD, PhD, has been studying ways to improve nutrition for vulnerable populations. Basu, an assistant professor of medicine at the Stanford Prevention Research Center, has found that a one-size-fits-all food assistance payment for groceries is just as inappropriate as when physicians give every heart patient the same dose of aspirin.
For example, simply receiving food assistance funds may not be enough. For some people, a van that takes them shopping once a week, and actually gets them to the store, is much more helpful than a food voucher for a market they can’t get to. So, whether treating heart attacks or preventing them with better nutrition, it’s the precision health approach — looking at what individuals need — that helps people eat better and stay healthy.
Minor sees an opportunity for precision-health thinking to be incorporated into research at all seven of Stanford’s schools. Law and business, for example, can inform the development of policies to help populations become healthier, while engineering is helping to develop devices for monitoring health to both prevent and treat disease. Already, says Minor, nearly a third of all faculty at Stanford’s School of Engineering are conducting research related to biomedicine, often in partnership with the School of Medicine. One device in development will monitor breathing and heart function of children with asthma while they sleep, delivering an alert as many as 48 hours ahead of a serious asthma attack. Early treatment saves kids from a trip to the emergency room, which is better for the kids, better for their parents and better for already overburdened emergency departments.
“Our vision,” says Minor, “is that a doctor can tailor every therapy specifically to what’s known about a patient: their genetics, their metabolomics, all their -omics, their imaging, everything about them. At Stanford, we want to live in a world where health-care providers aren’t left on their own to somehow aggregate all that information. Instead, information technology helps a doctor to confidently tell the patient, ‘You are going to benefit most from doing the following.’ We know it will take a sea change in training the doctors of the future, but the benefits will be massive.”