The United States, in particular, and the world, in general, faces a healthcare crisis of enormous proportions. The cost of care is already rising, but the combination of an aging population and changes to diet and lifestyle leaves a growing percentage of the population susceptible to chronic health conditions, such as heart disease and diabetes, which further drive healthcare costs. By 2020, the United States is expected to spend $4 trillion annually on healthcare -more than the GDP of all but a handful of nations.
Healthcare, then, is ripe for innovation. Much comes from academia, which lets data scientists, economists and medical professionals collaborate more freely than they might in a corporate setting, but new ideas do come from the private sector as well.
The Future of Health and Wellness Conference held earlier this month at the Massachusetts Institute of Technology highlighted the results of some of these collaborations. Collectively, they won't address the 30 percent of wasted healthcare spending-some $800 billion per year-that the Obama administration hopes healthcare reform can eliminate, but they do demonstrate progress in understanding how patients age, cope with stress, change our behavior and interpret the information that doctors give them.
1. Reality Mining: Using Data to Influence Healthy Behavior
Using smartphones to collect information about what people are doing and how they are behaving, which Alex "Sandy" Pentland, director of the MIT Human Dynamics Laboratory, describes as "passive monitoring from the things you carry around every day," results in a data set that's "hugely richer than anything you've ever seen before." It's an extension of data mining known as reality mining, and its predictive capabilities seem to know few limits.
For security purposes, information is shared using an "answer architecture" that makes yes-or-no queries of the open personal data store ( openPDS) on a user's smartphone, Pentland says, much like the SWIFT platform banks use to exchange information. In this manner, and in accordance with the U.S. Consumer Privacy Bill of Rights and the European Union Directive on Privacy and Electronic Communications, the data belongs to the individual.
Societal patterns and habits inherent in these data sets can predict behavior, such as the likelihood of residents of a certain neighborhood developing diabetes or alcoholism. ( Predicting behavior from verbal and visual cues, it turns out, is rather easy; technology that Pentland and his team have developed is used by two large health insurers to screen callers for signs of depression.)
However, if exposure to external forces drives behavior changes, Pentland says, then getting to the root of the problem means changing exposure. Through its research, Pentland's lab reports that social influence-knowing that others are being rewarded for good behavior such as riding a bicycle to the office-is more than three times as effective as simply receiving that reward on an individual basis.
Sign up for CIO Asia eNewsletters.