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With increasing volume and velocity comes increasing variety. This third “V” describes just what you’d think: the huge diversity of data types that healthcare organizations see every day. Again, think about electronic health records and those medical devices: Each one might collect a different kind of data, which in turn might be interpreted differently by different physicians—or made available to a specialist but not a primary care provider. The challenge for healthcare systems when it comes to data variety?
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Big data first and foremost has to be “big,” and size in this case is measured as volume. From clinical data associated with lab tests and physician visits, to the administrative data surrounding payments and payers, this well of information is already expanding. When that data is coupled with gr...
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The way care is provided to any given patient depends on all kinds of factors—and the way the care is delivered and more importantly the way the data is captured may vary from time to time or place to place. For example, what a clinician reads in the medical literature, where they trained, or the...
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Velocity in the context of big data refers to two related concepts familiar to anyone in healthcare: the rapidly increasing speed at which new data is being created by technological advances, and the corresponding need for that data to be digested and analyzed in near real-time. For example, as m...
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Last but not least, big data must have value. That is, if you’re going to invest in the infrastructure required to collect and interpret data on a system-wide scale, it’s important to ensure that the insights that are generated are based on accurate data and lead to measurable improvements at the...
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