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Big data is quickly expanding to a number of industries, and healthcare is no exception. With the use of big data, all kinds of medical records and studies can be digitized and easily analyzed. However, using big data in the healthcare space comes with its own set of challenges that anyone involved in the industry should be aware of.
The U.S. government and other private organizations have poured billions of dollars into digitizing medical records, but so far the data has basically just stayed where it is. Next to nothing has been done to analyze and actually use that data, in large part because the data is incredibly difficult to use and interpret. Medical data is often stored in databases, which tend to not be easily compatible with each other. Some of the best and most useful information is often added to records as freeform notes, which can be hard to digitize and interpret. Medical records also pass through multiple people’s hands, from nurses to techs and doctors, before making it to the digital world, meaning it is relatively easy for errors or discrepancies to enter someone’s personal information. One of the biggest pushes for big data in healthcare is …
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