WSJ – Big Data Treasure Trove From Routine Medical Checkups


Today’s WSJ featured an excellent article on ‘Big Data Treasure Trove From Routine Medical Checkups’ that notes how the “rise of electronic health medical records helps doctors make a better diagnosis.

This past week, Intelligent Response highlighted how Big Data and Healthcare – a Case Study for Massive Disruption how healthcare reform’s timing, specifically with the emergence of Big Data and predictive modeling, can vastly change our healthcare system.

Journalist Amy Dockser Marcus of the Wall Street Journal highlights how the mining of electronic health medical record data is already helping Physicians make better diagnoses of specific patients and, modeling that data to advise & treat other prospective patients.

The WSJ notes that “some early data-mining results are starting to influence care at clinics through published papers, presentations at conferences and a push by federal agencies interested in finding ways for academic centers and hospitals across the country to learn from big data.”  In short, Big Data and predictive analytics are enabling the identification of patterns, that would ordinarily not be visible to individual Physicians.

As one example, the article provides an interesting example of analyzing a population of 71,000+ patients with sore throats, and how the data could be modeled to avoid 230,000+ “unnecessary Doctor’s visits”.  While this example is significant on one hand, and relative simple on the other, it demonstrates promise about how unknown medical problems, can become known; and how unstructured medical problems, can become structured medical problems; and how be integrating disparate data sources onto a unified data platform, can enable predictive modeling

To read the full article in the Wall Street Journal, click here.

By Nick Mavrick

You can find Nick Mavrick on Google+

Intelligent Response specializes in managing and securing Strategic Marketing and Digital Advocacy projects from start to finish in Washington DC.

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