On June 2, 2015, Hagen Finley and I jointly presented a webinar for O’Reilly Radar…”The Internet of Living Things, what makes sensoring and monitoring data emanating from our bodies unique, and why we should elect to participate in this seemingly Orwellian mistake of open-sourcing our personal health data”.
We are at a threshold in the history of personal data. Sensors and apps are making it possible to generate digital data signatures of important aspects of healthy living, such as movement, nutrition, and sleep. However, we are rapidly losing the opportunity to erect a Linux-like open “living-well” data system steeped in open commons principles. We can either join together to ensure enlightened open source and crowdsourced discovery practices become the norm for our living-well data footprints, or we can passively allow this data to be sequestered into one of the walled gardens offered by health systems, funded research, or big business.
Why this is important?
Living-well data provides the map by which vast amounts of preventable human suffering can be prevented. Everyone can benefit from the health journeys of those who lived before us because our modern societies are no longer “accidentally well.” Decades ago, parents had no need to question the nutrition a child was offered or concern themselves with how much activity a child engaged in. No deliberate use of devices was needed to track these important health contributors. Reasonable access to whole foods (farm foods) and reasonable amounts of activity were provided, as it were, by default — in other words, by accident. This resulted in remarkably low rates of chronic disease. Today, communities cannot take those healthy choices for granted — we are no longer accidentally well.
In modern times, we must make deliberate choices to achieve adequate levels of activity, nutrition, and sleep. Over the decades of our lives, those choices provide an effective backbone for living well. Without those deliberate decisions, the default is set for dangerous amounts of sedentary behavior, over use of refined carbohydrates, and many more unhealthy norms. Together, we will need to build and maintain a robust living-well data repository or reference data base that collectively informs our general habits in dynamic and timely ways in order to achieve optimal living for ourselves and our families.
Open commons data principles
The Linux and open source community grew out of a keen appreciation for crowd-driven innovation and negative experiences associated with the cost and limits of vendor products. Perhaps, more importantly, the open approach to software development fostered a spread and advancement of skills for all participants. Today, many health-tracking apps and devices are offered as siloed vendor and point solutions. Many users are seduced by the lure of ultra-user-friendly smart phone interfaces: why not let the Googles, Apples, and Facebooks solve our data integration problems for us?
While we wait for the Internet mega-corporations to dazzle us with slick new wearables and health apps, we are rapidly losing the opportunity to erect a parallel (Linux-like) open living-well data system steeped in open commons principles. Could the open source health data community launch a movement to inject more open data/system management principles into Google, Facebook, and Apple, and avoid the walling off of our living-well data stream? Learning how to optimize our health will depend on it.
In the past, individuals had limited access to their sickness and treatment data by conscious design. American payer and provider systems walled off that information, ostensibly due to concerns including a patient’s lack of sophistication to grasp, interpret, and/or respond appropriately to that data. Although there are situations where sharing raw medical data with patients and the public could result in misunderstandings, limiting access to a patient’s own data also fosters and reinforces the patient’s dependence on specific health professionals. As a result, individuals struggle to use alternate sources for health care and seldom gather the incremental skill to improve their own healthy behaviors.
We have much to learn from each other. The digital exhaust of both healthy individuals and those burdened by poor health provides the young a wealth of information to help navigate an ever-widening set of living choices. Understanding why one group fails to become ill or manages to postpone chronic diseases that afflict another group is a small task given the plethora of apps and devices that could convert human experience into explorable data streams.
Health care payers and providers have yet to claim they should curate and interpret our wellness data. However, a greater threat may loom on the horizon in the form of Internet services from companies like Google and Apple, who are jockeying for position in the race to ingest, store, and perhaps “own” access to our wellness data.
Why do we need each other? Can’t we rely on research to provide directives for living well?
In short, traditional research cannot hope to keep up with the pace of modernization. Science advances slowly while technology re-invents our lives at a dizzying pace. Resources for research are limited and scientists cannot study all things. Therefore, scientists pick and choose research topics based on criteria that might matter: prestige; funding stream; and, hopefully, health impact. In the end, the landscape of all scientific knowledge is made up of peaks and valleys. Peaks of isolated knowledge driven by the concentrated study of well-funded academic pedigrees surrounded by vast valleys widely devoid of scientific understanding. Consequently, health knowledge is not democratized across all human suffering. Instead, only the peaks of suffering benefit from diagnosis and effective treatment. In addition, our legacy scientific research systems strive to reach the gold standard of Randomized Controlled Trials (RCT)-level evidence. This level of rigor is woefully expensive and burdening.
These legacy RCT systems used to be the only systems we had. Consequently, they shaped our understanding of illnesses that could be reduced to a narrow causative agent. However, the RCT approach is relatively poor for interpreting complex multifactorial events such as those that form the basis for living well. Today, we can augment the RCT approach with big data tools and uncover correlations across a multitude of possible contributions from both health and sickness data.
Manufacturing uses technology to track and optimize engine performance
GE needs access to data about its jet engines’ functioning and broken parts to determine the engineering specifications for the best performance and longevity. For example, real-time jet engine tuning parameters can suggest a different fuel mixture is required when the weather changes. In that model, all the engines on all the planes can benefit from those insights immediately — in real time.
If our living-well data gets sequestered, waiting for the scientific or business community to determine what issues are worthy of research funding, we risk this critical longitudinal data will gather dust or be used selectively. Humanity should expect — or even demand — the basic information necessary to defining living well to be open and explorable by almost anyone. Living-well research is uniquely suited to an open source- or crowdsourced-driven research and discovery model.
For example, http://www.bluezones.com/ has uncovered an association between longevity and incremental daily meal size: largest at the bottom/breakfast, medium-sized meal midday/lunch, and smallest meal before retiring/dinner. Understanding such mundane, yet potentially high-yield details is not likely to attract funding from the National Institutes of Health (NIH) or a high-value IPO startup.
Within the walled garden of medical knowledge, translating scientific discoveries into public health action often takes 17 years. That may be acceptable in the case of high-risk treatments or drugs, but it doesn’t make sense to burden low-risk living-well insights with the same research testing rigor. The safety margin is relatively wide for living-well choices.
Pulling the best performance from personal biology will, by necessity, become a group or team sport. Open data practices can provide the repository to enlist our collective selves in the task of rapidly acquiring and spreading the skills needed to ensure optimal health throughout the decades of our lives.
Each of us has a responsibility to ensure unhampered access to the data that explains the health implications of our cumulative living choices. A keen curiosity and basic skills to query living-well repositories must be as accessible as the water we drink and the air we breathe.