Freeing the “Doc in a Box”

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The American healthcare system is set up to care for a certain subset of the population – sick people – people with chronic disease, acute illness, acute injury, and complex disorders like cancer or metabolic issues.

The problem is, this set up doesn’t create market incentives to care for the well effectively, or to identify those at risk for disease and efficiently and reliably intervene, at scale.

To reconcile this cognitive dissonance between sick-care and health-care, government agencies like CMS, are now funding population-based care strategies. The idea is, the healthcare system should anticipate patient needs at the population level, stratify those needs by risk, and disseminate preventative interventions locally, based on traditional indices like blood tests and screening protocols and emerging metrics like ICD-10 z-codes to identify social determinants of health.

Now that the federal government is redefining the relationship between communities and health systems, it seems logical to anticipate future opportunities to redesign one of the most outdated physician roles – the “doc in the box.”

But the baffling thing is, that is not what is happening.

Despite CMS’ new Accountable Health Communities Model and the NIH’s recent Precision Medicine Initiative, it seems the latest innovations in healthcare delivery are aiming to do what we are already doing – better – to map the genome, decipher codes in our blood, and screen with increasing precision to identify disease earlier and decrease associated health complications and systems costs.

But the building-based, physician-centric, model of medicine America has relied on for decades, maybe even centuries, isn’t serving us well anymore. The hands-on, face-to-face, one-on-one, physician-patient relationship is changing and the bedside, fee-for-service paradigm doesn’t fit how patients access information and more importantly, doesn’t pay for keeping patients well.

Thinking outside the “doc in a box”

In the future, instead of caring for thousands of people in a primary care panel, I think physicians will “care” for hundreds of thousands of people across a grid. And they will provide that care, in teams.

The grid will be color-coded by risk factors. Incorporating data from smartphone usage, credit card spending behaviors, typographical maps of cities that chart access points for public transit, healthy food, parks and recreation, public learning, and other staples of public life. Those access points will be rated by the degree of mobility they generate – socially, economically, and physically. High-rated areas will become models for low-rated areas, and low-rated areas will be first in-line for public resources to re-engineer the environment people live and grow in. This model places mobility, equity, and the capacity to maximize human potential at the center of innovations that create and sustain health.

It also positions physicians among a team of professionals who operate integrated public systems. Those systems will be powered by data algorithms that understand the connections between human physiology and the lived experiences that nurture or threaten that physiology, to ultimately predict risk rather than simply identify existing disease, early.

If future systems can predict risk at scale and are oriented to respond those risks with mitigating resources or information that informs and supports patient decisions, then in the future, physicians will also be expected to be architects of resource distribution, partners in city planning, advocates for social justice, and champions of equity.

There will likely always be a need for physical care of patients with ailments that require  treatments best administered at the bedside. But the advent of technology to provide remote care, analyze multi-variant data that predicts human behavior, and supports patient and provider decision-making with rapid access to information and resources, shifts the future of medical practice outside of buildings.

With a new legion of ancillary providers, it is time to free the “doc in the box” and expand the vision of medical care to include the future of physician practice.

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When Science Fails: The Promise and Limits of Precision Medicine

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For centuries, humans have used science to explain their world. From the principles that suspend the planets in orbit to the relational pull of predator and prey, we turn to science to both examine and rationalize the experience of life. But does our reliance on science have a limit, particularly in medicine, where the “why” of disease can often escape scientific explanation?

For example, historically, medicine has poorly understood why one person gets sick and another doesn’t, particularly for complicated illnesses like cancer, diabetes, or heart disease, where multiple factors contribute to risk. Similarly, it’s been difficult to pinpoint why one medication works well for one person but not another.

And in the case of social determinants of health, medicine has yet to chart the physiology of disadvantage. That means, while we know poor people tend to be sicker, we don’t fully understand how poverty and discrimination manifest physiologically to produce disease; although there are exciting theories about stress hormones and organ function.

And so the why has evaded us, until now.

In January 2015, President Obama invested $215 million in a national Precision Medicine Initiative to use what science knows about the human genome to personalize the way doctors diagnose and treat disease.

The idea is that by using a wide range of biomedical information — including molecular, genomic, cellular, clinical, behavioral, physiological, and environmental parameters, physicians and scientists will have new tools to understand disease and determine the treatments that work best for each individual’s illness and DNA.

With such a sizable investment from the Obama administration and the partnership of trusted institutions in the scientific community including the National Institutes of Health (NIH), National Cancer Institute, and the Food and Drug Administration, this Precision Medicine Initiative promises to improve the diagnostic strength and treatment success of modern medicine. The significance of that promise cannot be underestimated.

But as we turn to science to answer the elusive why, we have to be mindful of where science has failed in the past. This is to set reasonable expectations but also to avoid repeating past mistakes. So as we move forward, here are 2 things to keep in mind.

First, as we narrow our focus from the population to the individual, it may be easy to overlook the way certain diseases are disproportionately prevalent in certain communities. If we then, limit our evaluation to the individual, their DNA, and their illness, we may miss the aggregate data that compels us to also investigate disease at the community level, where local resources and public policy may profoundly shape disease patterns and prevalence. Which is to say, while some disease is best explained from the lens of a microscope, other disease is best appreciated with a panoramic view of the environmental conditions in which that disease persists.

Second, to capture enough data to understand the human genome, the NIH and its collaborators are aiming to enroll 1 million American volunteers in the Precision Medicine research cohort. But a study published in 2014 found that non-whites account for less than 5% of clinical trial participants. More specifically, of the 10,000 clinical trials reviewed in that data, only 150, or less than 2%, focused on a racial or ethnic minority population.

So, if the Precision Medicine cohort is anything like the clinical trial cohorts from the past, women, minorities, and the elderly may be underrepresented; not to mention undocumented “non-Americans” who are generally excluded from scientific research. That means, while some patients will receive care uniquely tailored to them, women, minorities, the elderly, and the undocumented, may get care that was studied, tested, and developed, mostly for young white men. So as we endeavor to improve our understanding of human biology and disease, we have to make demonstrated efforts to enroll those science has historically forgotten.

Probing the human genome for the answers to medicine’s greatest questions will almost certainly lead to innovations and improvements in the health of our population. But as with most innovations, without careful and thoughtful execution, the impact may be limited. In Precision Medicine, we risk continued exclusion of certain populations from the benefits of science. This is when science fails, when it is unable to capture the breadth and meaning of the human experience. So if Precision Medicine does not couple its inquiry into DNA and disease with an equally rigorous examination of the biologic imprint of social stress, poverty, and discrimination, we may be no why-ser, than when we started.