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Big data analytics for healthcare improves patient care, operations
This article is part of the Pulse issue of September 2017, Vol. 5, No. 5
Over the past few decades, the healthcare industry has been exposed to a number of technology trends that have changed the way hospitals view and interact with data. Cloud, the internet of things and big data analytics have all offered opportunities to capture more data and deliver new insights while maintaining a low-to-moderate infrastructure. Despite the incredible progress in artificial intelligence and machine learning, some healthcare professionals are looking to maximize the use of their existing data analytics systems before shifting gears to AI and advanced analytics. With the abundance of data collected within hospital systems, executives often look to big data analytics for healthcare to support improvements in patient care, safety and operations. That's usually done by delivering dashboards and actionable insights to physicians, nurses and administrative staff. The data is available, and the tools are often widely accessible and hold a tangible return on investment. However, implementing analytics with stale and ...
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APIs are new to some in healthcare, but other industries use them regularly. Interoperability will benefit if healthcare can get beyond its legacy systems.
EHR interoperability might swing in favor of cloud installations rather than on-premises approaches. Also, legacy systems may be left in the dust of patient data exchange.
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APIs are useful in improving EHR interoperability. From that perspective, electronic medical records that are certified by the ONC must adhere to API criteria.
As the amount of patient data in hospitals continues to grow, healthcare big data analytics can help improve patient safety by providing valuable insights in near-real time.