Health Informatics and Big Data

Big data offers enormous potential for improving healthcare delivery, many of the existing claims concerning big data in healthcare are based on anecdotal reports and theoretical vision papers, rather than scientific evidence based on empirical research. Big data have learned through the various paradigms of health information technology (HIT) implementations. Though the role of HIT in reengineering the healthcare system has been well discussed and the benefits to improved processes and patient safety have been demonstrated, there is still much room for HIT outcomes-based research to demonstrate its value. HIT has also brought with it issues such as human computer interaction, technology-induced errors (e-iatrogenesis) and workaround issues, which have the potential to grow as innovations continue to be introduced into healthcare at rapid rates.

Big data analytics is the process of examining big data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions. With big data analytics, data scientists and others can analyze huge volumes of data that conventional analytics and business intelligence solutions can't touch. Consider that your organization could accumulate (if it hasn't already) billions of rows of data with hundreds of millions of data combinations in multiple data stores and abundant formats. High-performance analytics is necessary to process that much data in order to figure out what's important and what isn't. Enter big data analytics.

  • Big data Analytics
  • Big Data Experiences
  • Big data Medical Devices
  • Big Data Medical Records
  • Big data Processing
  • Big Data Systems

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