In the era of electronic health records and the transition toward pay for performance, health care organizations have begun leveraging analytics to identify opportunities to improve patient outcomes, reduce costs and increase efficiency. Vast amounts of hospital system data are available for pattern recognition and future trend prediction using complex analytics. Patient information once recorded and stored physically in paper charts is now stored in electronic databases. However, extracting and applying the data proved more difficult than we would have hoped. Comparable to the complexities of medicine, not all electronic databases are created equal. Most physicians are familiar with electronic health record (EHR) applications that use OLTP (online transaction processing) electronic databases. OLTPs organize data for storage and retrieval and offer users reading and writing privileges typically through a single software application. While this allows real-time data access for...

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