The Facebook Model for Socialized Health Care

The Facebook Model for Socialized Health Care

5
SHARE

Screen Shot 2015-02-26 at 5.06.17 PMAs government involvement in U.S. health care deepens—through the Affordable Care Act, Meaningful Use, and the continued revisions and expansions of Medicaid and Medicare—the politically electric watchword is “socialism.”

Online, of course, social media is not a latent communist threat, but rather the most popular destination for internet users around the world.

People, whether out of fear for being left behind, or simply tickled by the ease with which they can publicize their lives, have been sharing every element of their public (and very often, their private) lives with ever-increasing zeal. Pictures, videos, by-the-minute commentary and updates, idle musings, blogs—the means by which people broadcast themselves are as numerous and diverse as sites on the web itself.

Even as the public decries government spying programs and panics at the news of the latest massive data-breach, the daily traffic to sites like Facebook and Twitter—especially through mobile devices—not only stays high, but continues to grow. These sites are designed around users volunteering personal information, from work and education information, to preferences in music, movies, politics, and even romantic partners.

So why not health data?

The latest fad asserting itself in the internet of things—that is, the wide world of wireless devices which, to whatever extent, incorporate internet connectivity for one reason or another. Digital meters are broadcasting residential utility usage; cameras use GPS to help photographers document where photos are taken; cars are learning when and where they are likely to need refueling.

Now, wearable technology like watches, ankle-bracelets, and similarly low-profile accessories are integrating apps to measure everything from how many miles a wearer has walked (with GPS-guided precision), to how a user’s heart-rate and blood pressure fluctuate over time.

How much longer until we see these apps and devices being networked into the places where that information can be put to the greatest use: doctors’ offices?

The mistake currently made in the wearable technology market is assuming that the wearer is the best person with whom to share all the valuable information these devices measure and record.

For any given early-adopter of such technology, the application of such data is more of a novelty than a life-saver. Critics of wearable health-tech have pointed out as much; knowing precisely how high their too-high blood pressure is doesn’t provide any additional motivation to change aggravating behavior, and so on.

While well-intentioned consumers snatch up fashionable, phone-syncing pedometers and sleep-trackers, there is no associated benefit other than a moderate uptick in awareness of such statistics. Before these devices go the way of the Walkman, their greater potential deserves a shot at making them ubiquitous in modern healthcare.

The Facebook model for utilizing all of the various data being offered up by its billions of users offers a limited glimpse into what social-media sharing could do for health data. Facebook combines expressed user interests, with a history clicks and views, to better target content (and advertisements) likely to be of interest to users.

Does someone tend to click more often on stories featuring cute animals? That user is going to see those stories in their news feed more often. Did that user click on a web-ad for ironic t-shirts? Start loading the virtual shirt cannon, because Facebook knows, cares, and has a whole host of additional ads for that behavior.

This kind of application for Big Data has historically been a commercial exercise; targeting ads increases sales conversions, because the ads are smarter. Healthcare needs the same kind of targeted approach to overcome obstacles like regional variances in cost, medication, and even access. The technology is already available; what is missing is a drive to actually take advantage of it to prove its merits.

The oversharing trend does not have to be a solely social act, nor an overwhelmingly banal one; sharing pertinent information with care professionals—as automatically and unconsciously as people are already “tweeting” nothings to one another—could be a boon to emerging healthcare technology and data aggregation.

Direct sharing, to, say, a primary care physician, has merit on an individual basis. Providing accurate baseline measures for key health indicators would virtually eliminate the need for more invasive tests and studies by seamlessly measuring and reporting such metrics around the clock—attentive doctors (or better yet, systems for monitoring such data) could very well identify a problem before the patient.

Preventative medicine indeed.

Scaled to a population, the benefits are even more numerous and potentially powerful. Rather than a single doctor helping a single patient prevent the onset and worsening of an illness, suddenly a whole cross-section can be tracked to identify outbreaks (like the trans-national Ebola crisis of 2014), more precisely identify group risk-behavior (like a disregard for hand-washing), and improve care-access through a hyper-specific, need-based approach (a specialty clinic for geriatric care in a remote area may in fact be the missing link in the community’s overall health system).

When University of Cincinnati Health Informatics Professor Victoria Wangia decided to research the potential for Big Data (through the use of Geographic Information Systems, or GIS) to improve prescription medication use research,  the study showed a gaping void of application. The science and the systems exist, the study found, yet collaboration between health scientists and GIS professionals to implement this technology were scarce.

The President’s Precision Health Initiative is built on the idea that volunteers will donate their DNA to a massive database and allow scientists to better analyze and target vulnerable genes responsible for diseases like cancer. This is building on the existing notion that personalized medicine—accounting for the genetics of patients—will drive cutting-edge treatments to be developed.

While a genetically-engineered cure for cancer certainly sounds impressive, the fact is that this initiative is making a leap to new (and even undeveloped) technology before fully integrating existing systems. Both the collective behavior of social sharing, and the technology for analyzing and interpreting social data, are already widely in place. As Dr. Wangia pointed bout, the trick is to actually merge the two—which does not necessitate a whole new system.

Edgar T. Wilson is a healthcare and policy analyst.

 

Leave a Reply

5 Comments on "The Facebook Model for Socialized Health Care"


Guest
Mar 12, 2015

It is helpful. Thanks sharing.

In the future, many good tools assist to keep track our health.

Guest

Good stuff.

I feel that healthcare can be improved markedly through data analytics, social trend metrics and (perhaps most importantly) pulling in knowledge from the crowd to assist in healthcare decision making.

Joe

Guest
Feb 27, 2015

Great Article!
Internet of things will transform human interactions a transform the social fabric, the way internet transformed the way we live, work and play back in the 1990s.

Social media will play a key role in connecting the unconnected and enable faster awareness of changes in state of a person of device. Lot of the experience and speed will be derived form Bigdata analytics.

Thanks

Guest
civisisus
Feb 27, 2015

PM Anderson would probably have cautioned about interpretation of health data what he cautioned about reductionism in physics: more is different. That is, not necessarily better/more accurate/more productive of the health you’re after.

We’re a considerable distance from anything like the applicability ET Wilson anticipates, and the positively creepy enthusiasm of Silly Valley enthusiasts like Tom Goetz may strangle the whole show in its crib anyway