WIKIMEDIA COMMONS, DADEROT
There should be one day each year where we turn to face the small town of Framingham, Massachusetts, and join in a global standing ovation of thanks. Never heard of Framingham? Almost everything we know about heart disease and health risk factors has come from the very public contributions of the Framingham community.
The Framingham Heart Study (FHS) began in 1948, when more than 5,000 residents of the town were enrolled in a long-term public health study. In 1971, the FHS Offspring study was launched. In 2002, the third generation of Framingham residents and family members was enrolled. The studies are observational, meaning data is periodically collected and aggregated, but there is no intervention by the physicians. All subjects receive standard preventative health and wellness care, a robust history is recorded for each, and a physical is performed every 2 years; all...
This shared data has taught us fundamental lessons about the risks of smoking, of “bad” and “good” cholesterol, of high blood pressure, and of diabetes. More recently, the data has been used to answer questions that the FHS founders never would have thought to ask. By looking at relationships and friendships over time, new research teams have begun to explore how obesity, alcohol consumption, or mood trends can move through a community. From these newer studies, we are beginning to learn about social influences on health.
But more than any of these individual insights, there is a greater lesson to be learned from the FHS: large-scale collection and sharing of healthcare data can go a long way towards advancing our understanding of health and disease, and sometimes it can answer questions we didn’t even know we had.
The big picture and the “big data”
All of the lessons learned from the FHS program are possible because of the structured collection of health information—great things can happen when health information is shared, collected, aggregated, and studied in the right way.
First, any tool that supports the collection and standardization of health information can provide immediate individual benefits—the simple act of measurement provides awareness and motivation for the individual often leading to healthier decisions.
Second, sharing health information and finding ways to measure our data and experiences against others’ can provide perspective—how people are tracking over time, and how they compare to people like themselves. More recently, we have learned a lot about the value of online peer-to-peer health communities—the more engaged a user is, and the more she contributes to the community, the greater the benefit she herself enjoys.
Third, sharing health data can benefit the public health—allowing research organizations to aggregate health data across a growing subset of the population can provide novel insights into broader health correlations and trends. The computational sciences behind social network analysis and the greater availability of “big data” allow health and wellness patterns to be studied in ways never before possible. We can track contagion, we can track mood, and we can find patterns of health and illness that may inform research agendas, accelerate drug development, and alter public health policy. In short, our ability to overcome today’s emerging healthcare challenges would be severely hampered without such openness.
A public laboratory for healthcare research
The benefits of sharing healthcare data are exemplified by the FHS. But the FHS was a controlled environment: data was shared, but it was not truly public, and to this day, permission must be sought from the FHS review committee to access this data for research. More recently, it’s been argued that to maximize the fullest potential of such health research efforts, these and other data should be placed in open-access databases available to scientists all around the world.
In keeping with a more “public laboratory” model, we are now beginning to see small pilot public health research studies launch in conjunction with various health tracking sites and devices. These studies run the gamut from “quantified self” sites allowing you to collect data on weight, diet, sleep cycles, activity levels, or mood; to patient communities like PatientsLikeMe allowing patients to place their disease history, current symptoms, and narrative experience into the cloud. But where these pilots will take us is largely unknown. The data collection itself serves to unify patient communities, and if the data can be structured, there is every reason to believe that we can produce more and more Framingham-like experiences.
Of course, such projects will no doubt come with tremendous risks as well—health and wellness information gets at the heart of the most personal and vulnerable elements of being human. In the abstract, this data reveals our imperfections, casts a light on disease, and may stigmatize the afflicted. In the concrete, this data impacts our employability, insurability, and financial security. The fact is that we have no track record from which to predict whether broader public sharing will end up doing more good than harm, and we are still grappling with ensuring the anonymity and security of these data.
So while some, such as journalist and author Jeff Jarvis, argue that the greater good of humanity depends on pushing “publicness” as far as it can go, at this moment, I am a fair bit more guarded. When it comes to healthcare data and information, there is too much at stake to blindly promote a public laboratory for research. For now, my suggestion is to take ownership of your health, ensure that you have access to your data, and begin to digitize and track your own health story—this can only help when confronting an unexpected injury or illness—but hold off on placing your data in the “cloud” and be cautious when sharing your data with third-party companies to aggregate and publically mine.
At this point, it is impossible to balance known benefits against unknown risks. But if you ask me again in 2 or 3 years, I bet my perspective will have changed.
Brian S. McGowan is an independent consultant and author focused on solving the healthcare quality crises. He has worked as a medical scientist and educator and he is the author of the forthcoming fall 2012 release of #SOCIALQI: Simple Solutions for Improving Your Healthcare.