NOW FOR AN ORIGINAL PAPER ASSIGNMENT:Assignment: New Operating Systems

Information technology (IT)-related challenges such as inadequate integration of healthcare systems and poor healthcare information management are seriously hampering efforts to transform IT value to business value in the U.S. healthcare sector (Bodenheimer, 2005; Grantmakers In Health, 2012; Herrick et al., 2010; The Kaiser Family Foundation, 2012). The high volume digital flood of information that is being generated at ever-higher velocities and varieties in healthcare adds complexity to the equation. The consequences are unnecessary in- creases in medical costs and time for both patients and healthcare ser- vice providers. Thus, healthcare organizations are seeking effective IT artifacts that will enable them to consolidate organizational resources to deliver a high quality patient experience, improve organizational per- formance, andmaybe even create new,more effective data-driven busi- ness models (Agarwal et al., 2010; Goh et al., 2011; Ker et al., 2014).

One promising breakthrough is the application of big data analytics. Big data analytics that is evolved frombusiness intelligence anddecision support systems enable healthcare organizations to analyze an im- mense volume, variety and velocity of data across a wide range of healthcare networks to support evidence-based decision making and action taking (Watson, 2014; Raghupathi and Raghupathi, 2014). Big

ung@rowan.edu (L. Kung),

data analytics encompasses the various analytical techniques such as descriptive analytics and mining/predictive analytics that are ideal for analyzing a large proportion of text-based health documents and other unstructured clinical data (e.g., physician’s written notes and pre- scriptions and medical imaging) (Groves et al., 2013). New database management systems such as MongoDB, MarkLogic and Apache Cassandra for data integration and retrieval, allow data being trans- ferred between traditional and new operating systems. To store the huge volume and various formats of data, there are Apache HBase and NoSQL systems. These big data analytics tools with sophisticated func- tionalities facilitate clinical information integration and provide fresh business insights to help healthcare organizations meet patients’ needs and futuremarket trends, and thus improve quality of care and fi- nancial performance (Jiang et al., 2014; Murdoch and Detsky, 2013; Wang et al., 2015).