Health Care Big Data Paper

The health care system of the United States has a number of challenges, the most commonly stated ones are the ever increasing cost of care, low quality performance, and inaccessibility (McCarthy & Hart, 2011). Various attempts have been made through the years to tackle these challenges, one of which has been the introduction and use of Information Technology (IT) in health care (Naylor, Kudlow, Li, & Yuen, 2011). The Health Information Technology for Economic and Clinical Health (HITECH) Act initiative led by Centers for Medicare & Medicaid Services (CMS) and the Office of the National Coordinator for Health IT (ONC) that provide incentives to health care providers who employed meaningful use of EHR since 2009, has been one of the significant
Demchenko, Zhao, Grosso, Wibisono, & Laat (2012), have described the five primary characteristics of health care big data as five V’s: Volume, Velocity, Variety, Veracity, and Value. Volume refers to vast amounts of health-related data created and accumulated continuously. In 2011 alone, the U.S. healthcare system has reached 150 exabytes, and soon will reach the zettabyte (1021 gigabytes) scale and, not long after, the yottabyte (1024 gigabytes) (Raghupathi & Raghupathi, 2014). Velocity applies to the constant flow of new data accumulating at unprecedented rate, variety pertains to the level of complexity of the data, veracity measures includes questions of trust and uncertainty with regards to data and the outcome of analysis of that data, and value evaluate show how good the quality of the data is in reference to the intended results. (Herland, Khoshgoftaar, & Wald,
Big data also comes in two distinct forms: data at rest - datasets are analyzed after they are collected at some point later in time, and big data in motion - datasets that are processed and analyzed in real time or immediately when they come in (Yan, 2013). The various sources of health care data include clinical data, patient data in Electronic Patient Records (EPRs), machine generated/sensor data, such as from monitoring vital signs, social media posts, emergency care data, news feeds, and articles in medical journals (Raghupathi, & Raghupathi,