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How to do big data in healthcare

Many healthcare organisations like to talk about data analytics. However, here are eight pieces of expert advice to help you actually do it.

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Healthcare is replete with big data analytics use cases that offer measurable results, including reduced hospital readmissions, better medication management, improved strategic planning and heightened fraud detection.

That's all well and good, but for one key factor: How do you start? Most healthcare data remains unstructured, proprietary and siloed — and creating a clinical data warehouse is a complex task that time-crunched healthcare CIOs can't always justify.

Fortunately, there are lessons to be learned from healthcare's big data implementations. Here's some advice from providers who have been there, done that and lived to tell the tale.


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Data in the hand for life's rich demand

Speaking at the recent Oracle Industry Connect, the Mayo Clinic's James Buntrock recalled a time when organisations simply added applications, databases and point-to-point interfaces between them. The result? A plethora of disconnected data warehouses. Rather than focus on apps, Mayo takes a data-centric approach, Buntrock says, treating data as a critical asset for research, clinical and other needs. Getting this right means aligning IT and business objectives, he says, as well as supporting informatics and data mining in addition to traditional business intelligence.

Credit: Thinkstock


  • Data in the hand for life's rich demand
  • Sharpen stones, walk on coals, improve business acumen
  • Nothing's free - but, done right, it's guaranteed for a lifetime's use
  • You, leadership alone are not the everything
  • More than a simple prop to occupy government regulators' time
  • Take the Road, Recognise the Path Before Your Eyes
  • You can reach your destination, but there's still some way to go
  • Data Analytics a Compass to Help You Along


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