Fortune magazine recently published a long article about the escalating interest on the part of Big Tech in the enormous cache of data controlled (managed?) by large health systems (see: Tech's Next Big Wave: Big Data Meets Biology). Below is an excerpt from it. This is only a small fraction of the article so navigate to it if you are interested in the topic:
...[T]here’s a...powerful catalyst [for Big Tech's interest in healthcare]—one so gargantuan and infinitesimal at the same time that it sounds like the answer to a riddle. And that’s data. More specifically, it’s your data: your individual biology, your health history and ever-fluctuating state of well-being, where you go, what you spend, how you sleep, what you put in your body and what comes out. The amount of data you slough off everyday—in lab tests, medical images, genetic profiles, liquid biopsies, electrocardiograms, to name just a few—is overwhelming by itself. Throw in the stuff from medical claims, clinical trials, prescriptions, academic research, and more, and the yield is something on the order of 750 quadrillion bytes every day—or some 30% of the world’s data production. These massive storehouses of information have always been there. But now, thanks to a slew of novel technologies, sophisticated measuring devices, ubiquitous connectivity and the cloud, and yes, artificial intelligence, companies can harness and make sense of this data as never before.
“It’s not the data,” says Eric Topol, director of the Scripps Translational Science Institute. “It’s the analytics. Up until three-to-five years ago, all that data was just sitting there. Now it’s being analyzed and interpreted. It’s the most radical change happening in health care.” The quest to retrieve, analyze, and leverage that data has become the new gold rush. And a vanguard of tech titans—not to mention a bevy of hot startups—are on the hunt for it. Alphabet's....life sciences arm Verily is aiming to create a “baseline” of human health by tracking all kinds of biometric information from 10,000 volunteers...Apple just released an iPhone feature offering users in several big health systems instant access to their own medical record—an effort that joins its ongoing heart study with Stanford, testing if wearables can detect serious cardiac conditions (see: Apple Getting Traction with Its App to Access EHR Records with iPhones).
As this article makes abundantly clear, access to the mountain of health data is only the first step in the process of extracting more value from it. Analytics is the next step. Here's a definition of healthcare analytics from the Wikipedia (see: Health care analytics):
Health care analytics is a term used to describe the healthcare analysis activities that can be undertaken as a result of data collected from four areas within healthcare; claims and cost data, pharmaceutical and research and development...data, clinical data..., and patient behavior and sentiment data....Health care analytics is a growing industry in the United States, expected to grow to more than $18.7 billion by 2020. The industry focuses on the areas of clinical analysis, financial analysis, supply chain analysis, as well as, fraud and HR analysis.
I have blogged about healthcare and diagnostic analytics in the past (see, for example: Much of the Future for Pathology and Lab Medicine Rests with Analytics; Analytics May Be the Secret Sauce to Propel CVS-Aetna Forward; Eric Schmidt Discusses the Potential Value of Predictive Analytics in the ER). Regarding healthcare analytics in general and diagnostic analytics in particular, the development of these fields must take place in collaboration with the IT companies that have the special expertise to analyze the data using techniques such as deep learning, big data, and neural networks. Such a collaboration between these two parties will not be easy because of what I envision as "points of contention" that I intend to discuss in upcoming blog notes.
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