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Can Big Data Analytics Save Billions in Healthcare Costs?

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In a world where healthcare information exists in many different sources and formats (images, video, text, numerical data, multimedia, paper, etc.), it’s no surprise that the massive amount of healthcare data is incredibly complex and difficult to sort, organize, and decipher.

Procedures and terms can be identified differently from one department to the next. A claims department, for instance, may categorize a procedure by a mix of numbers and letters, whereas the doctor refers to the procedure by a term more commonly known to the patient and a more advanced medical term in his or her vernacular.

Big Data Analytics To The Rescue

According to McKinsey, big data analytics can help make sense of complex healthcare data and can enable more than $300 billion in savings per year in U.S. healthcare alone.

This year, at the Healthcare Information and Management Systems Society (HIMSS) Annual Conference, over 40,000 healthcare IT professionals, clinicians, executives, and vendors from around the world will convene to discuss how analytics and other cutting edge IT methods can improve the quality, cost-effectiveness, access, and value of healthcare.

One of the highlights of this year’s event will come from the American Society of Clinical Oncology (ASCO) a nonprofit, professional oncology society is transforming care for cancer patients with its new solution, CancerLinQ. ASCO CEO, Kevin Fitzpatrick, will share the ways the organization is unlocking knowledge from the medical records of the 97% of cancer patients not involved in clinical trials, enabling better, more data-driven decision making.

Dinesh Vandayar, Vice President SAP Personalized Medicine, will also lead a discussion around the newly released SAP Foundation for Health and applications like SAP Health Engagement which help support deeper insights and connect health data silos.

Eager to learn more? Connect with me before, during and after the event on Twitter at @CMDonato and follow #HIMSS16.