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Healthcare and Analytics: Taking the Pulse of Big Data

By   /  April 8, 2013  /  2 Comments

by Anjul Bhambhri

In two of my recent posts, I discussed the potential impact big data can have on energy management and business, explaining how customer and device data yield results that can provide an organization with a strategic advantage, either in service or offerings, over its competitors. As we now know, big data is the newest and most valuable natural resource to any organization, no matter which industry. This is particularly true in healthcare, where patient data analysis can very likely be a matter of life and death.

Not unlike typical business applications, where the ultimate goal is to provide improved customer service, big data technology is playing a large role in healthcare institutions to analyze enormous volumes of patient data and ensure a higher level of personalized care. Through the use of analytics tools that collect, synthesize and analyze historical and real-time data, physicians and healthcare providers not only obtain a more holistic view of patient health, but are also given the opportunity to monitor patient condition more closely, and conduct in depth research into diseases and drugs more efficiently.

For instance, using big data technologies, providers can now consider a number of factors, including test results, past visits and environmental elements, when addressing specific patient needs and determining a course of care. The Premier healthcare alliance is using a big data platform to gain insights on, measure and improve patient health and safety while also reducing the overuse of procedures, readmissions, unnecessary ER visits and hospital-acquired conditions. Through this work, patients have a greater certainty they will receive the most effective treatment possible and that their care will follow nationwide best practices.

At institutions like UCLA Ronald Reagan Medical Center doctors are using real-time sensor data to prevent and react to sudden changes in condition for patients suffering from traumatic brain injuries (TBIs).  The technology targets rapid rises in brain pressure to predict potentially dangerous changes and alert caregivers. Similarly, at the University of Ontario Institute of Technology in conjunction with Toronto’s Hospital for Sick Children, neonatal intensive care specialists are using data from monitoring equipment to track the condition of premature babies. Doctors and nurses are now, for the first time, able to spot and prevent potentially life-threatening infections up to 24 hours earlier.

Going further, there is also an increase in the use of big data within the medical research community, as it provides researchers and scientists with more insights into unstructured and structured data they wouldn’t have normally been able to access and analyze. This in turn allows them to generate a better understanding of what causes diseases and what can treat or cure them. An example of this is the work currently being undertaken at the State University of New York (SUNY) at Buffalo. Using analytics technology, researchers at SUNY are studying the more than 2,000 genetic and environmental factors that may contribute to multiple sclerosis, a chronic neurological disease that affects approximately 400,000 people in the US. Through big data, the scientists are aggregating and analyzing medical records, lab results, MRI scans and patient surveys to develop algorithms containing genomic datasets to uncover critical factors that speed up the disease’s progression in patients. The insights gained will help doctors better target individual treatments.

Regardless of your organization’s role – energy management, finance, marketing, healthcare – understanding and making the most of available data is essential to success, both on a business level and a personal level.

About the author

Anjul Bhambhri has 23 years of experience in the database industry with engineering and management positions at IBM, Informix and Sybase. She is currently IBM’s Vice President of Big Data Products, overseeing product strategy and business partnerships. Previously at IBM, Anjul focused on application and data lifecycle management tools and spearheaded the development of XML capabilities in DB2 database server. In 2009, she received the YWCA of Silicon Valley’s “Tribute to Women in Technology” Award.

  • In theory, this works pretty well. The huge stumbling block is the disconnect between primary and secondary care. Patients entering hospital come without complete medical history. Patients leaving hospital go back to primary care without complete hospital information. Also, some the apps you mention are really more CEP than Big Data, but it is the fashion to call everything Big Data these days.

  • Omg! Superbly compelling info. Now i’m book-marking this blog at once. Many thanks!

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