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Big Data in Oncology Spotlight


IP Blog | Dave Melin | August 5, 2015

This week in health care trends, our big data in oncology spotlight includes rising drug costs, hospital quality care measures, health spending slowdown, and genetic variations and cancer risk.

The articles below are from our dedicated Big Data in Oncology e-magazine. You can follow us on Flipboard or Twitter, or just watch for the links to this and our other magazines in our regular weekly BioBlog emails. (Don’t get our emails yet? Subscribe here!)

big data cancer buttonCan Big Data and Analytics Cure Cancer?

“Big data” is transforming oncology — but as this article notes, it would all be meaningless without a little help: “The need for Cognitive Computing lies in the fact that much of the ‘Big Data’ being created every second is unstructured, in the form of pictures, videos and text. Here, an intelligent computing system is needed to mine, and make sense of all the increasingly available data. Without such a system, the data is worthless.”

New Cocktails to Test Limits of Cancer Drug Pricing

As cancer drug costs continue to rise, this article spotlights the epicenter: combination drugs. “The real promise lies in combining treatments, either by using two checkpoint medicines together or by adding a different kind of drug. Both approaches will drive up prices.”

In Pursuit of Hospital Quality: Creating Effective Performance Measures and Transparency in Health Care

In the quest to ensure high quality care for all patients in hospitals around the country, this article argues that “to expand and sustain progress, efforts that have been taken by the public and private sectors need to be properly targeted and refined” and big data is part of the solution.

Health Spending: The $2 Trillion Question — or Questions

There is predicted to be a $2 trillion slowdown in healthcare spending. This article goes beyond the simple “what” and “why” of this slowdown and instead asks, “How can we develop and apply policies to address what is probably a different combination of drivers of health spending growth in each set of local market circumstances — perhaps tailoring them differently according to different populations and different configurations of payers and providers?”


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