A Human-centric future depends on building a Community Data Commons NOW.
Why now? There are at least three good reasons: we are no longer accidentally well, we have no business knowing as little as we know today and since when was average good enough?
Let’s begin with the “no longer accidentally well” assertion.
For billions of years, humans and our environment have co-existed and co-evolved. Environmental pressures optimized human physiological adaptations to improve human performance and in turn improve survival. We evolved to be stronger, smarter, faster and became the upright mammals that we are today. However, this naturally slow and parallel process of human-environmental evolution has been interrupted. Today machines and technology advance our environments at a pace humans are woefully incapable of. Thus as we move into an increasingly machine-assisted future we will need to build and maintain the infrastructures necessary to ensure a human-centric future. This means providing the technical foundation to ensure machines and technology are in the service of humans.
This may sound obvious, but recent history suggests that without a deliberate plan, we’ll fail miserably in ensuring a human-centric future. While technology-enabled business models have had relatively free reign to advance in the pure pursuit of profit we’ve witnessed a growing paradox: while technology advances, human health erodes!
Machines converted farm foods to factory foods and brought us trans fatty acids and refined carbohydrates at scale. Technology is converting activity-based employment into knowledge-based employment and providing humans with many hours spent in front of screens. Indoor lighting enables a twenty-four-hour photo period essentially eliminating day and night on demand. Heating and air conditioning has largely eliminated the seasonal variations our forefathers were exposed to. These are changes that our human physiology or operating system is ill-equipped to adjust to in a timely manner.
Recall, a few decades ago, mankind did not have the internet. We had not yet made the technological advancements that would redesign our environment at a pace that our biology had no hope to keep up with. Today our chemistry has no idea that we carry a smart phone. No internal biological adjustments have been made to process trans fatty acids or manage the effects of inter-continental travel. We lack a detection mechanism to trigger updated versions of biology on an as needed basis. In fact, our bodies were built using a biological operating system that expected the food, water and living patterns of hundreds of years ago to continue for centuries more. Furthermore, updating our genetic material requires many centuries of environmental exposure (assuming we rely on mother nature to provide the genetic updates). Clearly, the science hoping to speed this up with direct genetic manipulations is the subject for other papers. Here we focus on the fact that we are no longer accidentally well and the vast human opportunity inherent in this fact.
What does it mean to no longer be accidentally well? Our parents did not need pay much attention to how they fed us, how we moved or how well we slept. Trans-fatty acids and refined carbohydrates were not part of their vocabulary. Many of us were relatively free to accidentally access the full potential of the genetic material we were given at birth. Today this is no longer the case. Societal defaults for nutrition, activity and sleep (to name a few) are set in the sub-optimal direction. In short, many young people today are sedentary for many hours and consume refined carbohydrates in excess. They are not accidentally well. Wellness requires a concerted effort to achieve our best health, academic, social and other human outcomes.
This profound miss-match of evolutionary pathways: ultra-slow biological adaptation in the face of ultra-rapid tech-enabled environmental change is associated with a rampant decline in population health across the globe. CNN recently reported that Colon Cancer rates are increasing in young individuals less than 50 years of age[1]. The risk of a person born in the 1990’s is twice the Colon Cancer and four times the Rectal Cancer risk of a person born in the 1950’s. The study authors assert that this rise in rates cannot be attributed to more colonoscopies as the survival in this group is not improving. Between 1980 and 2014, a period of less than four decades The global burden of high blood pressure has doubled and the global Diabetes burden increased four fold [2]. A short time of four or five decades is far too limited a period to blame the genetic disposition of communities for these dramatic shifts in health expression.
Perhaps more importantly, the key take away should be that our ability to rapidly change our technology-enabled environments provides us with unprecedented control over managing the conditions that drive human adaptations and thus drive human performance. Our target need not be the historic achievement of accidental wellness. While humans control environmental co-occurrences, our opportunity to optimize human performance becomes immense.
However, with great power comes great responsibility. We’d better know what we are doing.
We have no business knowing as little as we know today.
Why don’t we know more? We’ve yet to optimize the data streams needed to supply robust human intelligence at the pace of change. We need to do a better job of digitizing, analyzing and reporting back the specifics that are driving human health expression in a timely manner. Recall the landmark suggestion that zip code is more important than genetic code in predicting health outcomes. This underscores the vast opportunity to design urban living conditions that optimize human performance.
The connections to physical health may be most obvious but our responsibility to know more crosses all the domains of human functioning. Take academic performance for instance. Pew Research suggests that our students lag in academic performance when compared to their peers globally. Using an education-centric approach to uncover the reasons for this leads to offering solutions to adjust class size, teacher quality and early childhood education. What if the core issue is not educational but physiological? Young developing brains may need robust access to fish and vegetables in order to assemble the building blocks to mature the complex neuro-circuitry to support higher order math and science. The connection between nutrition and cognition is mounting [3]. Does the diet of a three-year-old predict her IQ by the time she is eight? Kids are only young once and there are indeed a lot of moving parts impacting performance. Today, perhaps more than ever, achieving their best human-centric future depends upon a level of intelligence we have yet to deliver on.
Part of the good news is that human health expression is sufficiently complex and updating our intelligence regarding the parameters that drive health is likely to remain the job of humans for the foreseeable future. IBM Watson and other assisting technologies can analyze yesterday’s data to provide directional recommendations, but humans will be the source of updated data regarding the real world effects of advancing any recommendations. Furthermore, the responsibility to provide up these data updates need not sentence society to life-logging or the other intrusive approaches. Today data tools are able to fill-in missing data effectively enabling us to provide short check-in periods by intermittently using apps and devices to digitize our health expressions.
One of the biggest barriers to ensuring a human-centric future, is engaging humans to participate in the deliberate monitoring and co-production of this evolution. Previous posts expanding on the role of longitudinal personal health records are found here and here. In short, this is a by-the-people for-the-people responsibility to co-produce to human health intelligence at the pace of change. However, many Health systems still treat individuals as a cost center. Patients are given apps and devices to avoid unnecessary clinic visits or avoid re-admissions. Driving adoption while treating individuals as cost centers often proves problematic. With a by-the-people, for-the-people approach we can enlist the community as micro-health workers to gather the digital exhaust (data from wearables and apps) to provide high definition into the health expression of the group.
The data from both the healthy and the unhealthy are tremendously valuable in informing what is reasonably possible in terms of realistic health achievement. Engagement can be further fostered by linking participants in a cross-generational collaboration model. The more tech-savvy are linked to less tech-savvy in a mentoring and mentee model. In this way seniors find it irresistible to help students gain the insights needed to protect their generation from any unnecessary poor health outcomes. Seniors prefer a micro-health worker role to being treated as a cost center.
Remarkably, seniors are also the last of the accidentally well. They lived at a time when environmental co-occurrences dictated that Diabetes Type II could not exist at all in young people in any community. During this time, Diabetes Type II was called Adult-onset Diabetes and was considered a chronic disease of aging. Knowing this, seniors can well be treated as a national treasure; the last of the accidentally well from whom we should seek to learn as much as possible before they leave the planet. The group leaving the planet harbors the final truths regarding human health expression during their lives. These final truths provide valuable feed-back loops offering real world corrections to algorithms designed with limited data to predict the health futures of humans.
Furthermore, the concentration of more tech-savvy-ness within the younger generation is also an enduring property of all future generations. Our children are wildly skilled digitally but given the march of technology, they are likely to look as slow and awkward to their children as we do to ours. Working together, we can uncover the locally relevant co-occurrences that drive health expression well beyond average.
Since when was average good enough?
Since the dawn of medicine apparently. That is not to say that medicine has not delivered a series of outstanding accomplishments. However, average is the bar by which we quantify much of health. Lab value ranges are determined by the range of values that occur commonly among asymptomatic individuals. Take lipids for instance; the range of values within a given population is wide and medicine is restricted for those outside of normal or outside the average range. If a patient’s value falls within the often wide normal range they are not necessarily free of impending illness, they simply don’t qualify for medication at this time. This approach does little to define optimal. Living our lives targeting average for decades is unlikely to provide access to an individual’s full health potential. Achieving abnormal lipids and the right to be prescribed medication is likely to arrive many years earlier for those targeting normal than for those who had the tools to target optimal.
Defining optimal is the work of large multi-dimensional data sets and data crunching services like IBM Watson and others. Once we iterate successfully towards mass participation and gather the data to define optimal, we can reap the benefits of scaling outliers. Soon then labs will report lipid panels with highly personalized optimal range complete with insights regarding the most successful crowd-sourced strategies to move your markers throughout the decades of our lives. Given the technological advances today, this should be a near-term reality. We have no business knowing as little as we know today about what drives optimal at the personal level.
Moving from average to optimal is also the work of crowd-sourcing approaches to smart cities. Traffic patterns, workplace design and urban living can be optimized for a human-centric future. In these efforts the personal citizen record is in many ways similar to the longitudinal health record. Both are owned and managed by individuals. The personal citizen record helps ensure current transit intelligence is available in personally relevant ways at the pace of change.
Now rather than a transit decision, imagine facing a decision about shoulder surgery within a smart city approach. The three facilities locally have executed hundreds of similar surgeries last year. The range of outcomes spans a wide spectrum: low mobility and chronic pain to high mobility and little pain. A new comer with the benefit of a robust data commons might scan for the three hundred patients most similar to himself, line up the co-occurrences that drove the best results and deliberately target an outlier or exceptional outcome. Today’s search engines and data access do not yet provide for this level of intelligence to be available to the individual. The technology to do so is ready. Our job is to make it happen.
Today each of us has a role and increasingly a responsibility to assemble a longitudinal health record. New technology, the blockchain will help to make this an easy, secure and trans-global activity for all of us. Our human-centric future may well provide for societal performance that exceeds that of our accidentally well forefathers. Let’s get beyond knowing as little as we know today. Let’s pull up our selves and participate in a community data commons designed to replace average with optimal and deliberately scale outlier achievements. Using blockchain-based approaches, we can both achieve an exceptional human-centric future and spread it trans-globally. More to come.
References:
1) Colorectal Cancer Incidence Patterns in the United States, 1974–2013 Rebecca L. Siegel Stacey A. Fedewa William F. Anderson Kimberly D. MillerJiemin Ma Philip S. Rosenberg Ahmedin Jemal JNCI: Journal of the National Cancer Institute, Volume 109, Issue 8, 1 August 2017, djw322, https://doi.org/10.1093/jnci/djw322 Published: 28 February 2017
2) Projections of global mortality and burden of disease from 2002 to 2030.
Mathers CD, Loncar D. PLoS Med, 2006, 3(11):e442.
3) Nyaradi A, Li J, Hickling S, Foster J, Oddy WH. The role of nutrition in children’s neurocognitive development, from pregnancy through childhood. Frontiers in Human Neuroscience. 2013;7:97. doi:10.3389/fnhum.2013.00097.
