Uncertain Health in an Insecure World – 43

“Inter-not of Things”

Like many of you, my Twitter feed is deluged with tweets from very sophisticated denizens of the #bigdata and #analytics domains. For those of us who cannot distinguish a CEO from an SEO, it’s hard to keep up with the related buzz feed.

BTW, a SEO is a search engine optimizer.

And those analytics folks are way smart. They can take ALL that big data and fit it into mathematical models – algorithms – that can predict something useful about what is likely about to happen before it actually does. 

An excellent recent article on the topic by Jennifer Bresnick in HealthITAnalytics neatly defined big data analytics as “joining of two or more previously disparate sources of information, structured in such a way that insights can be drawn from the comparison or examination of the new expanded data set.” I really like when people make complex things simple!

In healthcare, ubiquitous electronic health records (EHR’s) contain oodles (a technical term still not owned by Google) of structured and unstructured big data. Some of this structured personal health information is routinely entered into the EHR by healthcare workers – patient demographics, vital signs, drug allergies, lab test results, etc.

BTW, it is my casual observation that there are still more healthcare workers than sex workers on Twitter, but one wonders how long that will last.

Other more complex structured data is laboriously captured and entered by busy physicians who must populate required clinical data fields and reconcile medications between patient visits or after clinic hours. All this is then washed over by a tsunami of unstructured data streaming in from bedside monitors and other medical devices in and around the environment of care.

So far, the healthcare industry has found it very difficult to bring disparate big data sets together to improve business practices or patient outcomes. The same 5,000 U.S. hospitals that generate over US$850 billion in annual revenues has yet to crack the big data analytics ‘nut’. Why is that? Is it EHR vendor incompetence? Is it a paucity of highly qualified personnel in this health IT domain? Is it the failure of policy-makers to align population health goals with early adoption? Of course it is!!

But we can now add the Internet of Things (#IoT) to the mix. The explosion of smart phones and #wearables make up a “nebulous network of collection nodes”. These things, almost any device with a charger or batteries, are Internet-connected to a larger network. Once these uniquely identified things start storing information in The Cloud, supported by the free apps that allow for real-time consumer interface, then you have the IoT! Personalization of these things is possible… Hell, it’s encouraged!

BTW, a Premium LindedIn package quickly reveals most of your personal attributes and professional talents to other world-wide invitees… How far off is it until the IoT knows your pulse?

   

The global exemplar of the IoT shaping healthy behavior changes may be found in a place as unexpected as post-Apartheid South Africa, where a company called Discovery has been innovating on the healthcare insurance pitch. CEO Adrian Goree outlined this novel platform in the current McKinsey Quarterly. Discovery’s Vitality™ program logs in Next+ and Fitbit data on 70,000 member fitness workouts per day via mobile apps and smartphones, rewarding their customers with 25% discounts on a total of $100 million of healthy foods. Vitality™ and other nudge incentives have eased Discovery’s access to global healthcare insurance markets in China, Europe, the U.S., etc.

Until better natural language processing algorithms are developed to digitize medical chart wording, the richly nuanced histories told by patients to their doctors, then entered into the EHR, are hard to use. As such, the phenotyping of patients’ individual disease manifestations is much more difficult than is the genotyping of their DNA. The Salt Lake City-based John Huntsman Cancer Institute – steward of the Utah Population Database (UPDB) – has asserted the importance of population genotyping to medicine. But one without the other is not nearly as powerful as both.

BTW, did you know that the popular Ancestry.com genealogy website is owned by the Church of the Latter Day Saints – the Mormons? So, the UPDB in SLC contains mostly LDS info... That makes me want to sing & dance!

My oft-favorited Twitter follower and newly LinkedIn colleague is Dr. Morten Middelfart, the CIO at Genomic Expression. Morten is flat-out brilliant, as his recent Oxford University lecture on “the magic” of big data analytics for solving chronic disease mysteries revealed on Twitter bit.Iy/1CHOIEp His Denmark-based firm has clearly demonstrated how Cloud-based RNA seq analysis and related algorithms can accurately model frequently ineffective therapies (see below).

The names that we give to the social media tools that monitor our collective information – the data-ome – are purposefully designed to be comfy, often bordering on the banal. Twitter… Facebook… the Internet of Things…

And the advent of peaceful & serene Cloud and open-architecture computing by the cute yellow Hadoop elephant should not be misunderstood as either light and fluffy, or dumb like Dumbo. 

To a hammer, everything is a nail!

What remains unproven is whether the power of Internet of Things tools can be harnessed, or not. 

We in the Square are not yet persuaded that IoT data are truly powerful, because “… big data is only as smart as those who generate it”.