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Introduction
Information science involves accumulating, storing, processing and applying big data. Clinical informatics is the scientific discipline that enhances human health by implementing information technology and knowledge management to prevent disease, deliver more efficient care and make translational research effective (Health Care Information and Management System Society, 2017). In essence, clinical informatics is information science, as it serves as a bridge between big data and its various applications.
Big data refers to large information sets that exist in structured (organized), unstructured (unorganized) or mixed formats (Kruse et al., 2016; Wang and Krishnan, 2014). Big data also reflect accumulated real-time information, their sources and information quality assurance maintenance. These characteristics have been described as the four V paradigm – volume, velocity, variety and veracity (McAfee and Brynjolfsson, 2012; Heudecker, 2013; Kayyali et al., 2013; Kruse et al., 2016). Big data sources span a wide spectrum and include information from social media, global positioning system signals, digital videos and pictures, sensors and navigation devices. It is difficult to accurately determine data quantity generated annually across the healthcare sector owing to information complexity from heterogeneous sources and their structured and unstructured formats in which these data exist (Lesueur, 2016). Nonetheless, approximately 500 PB (1 PB =1,000 TB or 1m GB) of data were generated by electronic medical records (EMRs) in 2012; a volume that is expected to reach 25,000 PB by 2020 (Hersh et al., 2011).
Artificial intelligence (AI) and machine learning are big data applications. Devices such as the Amazon Echo (Alexa) and Apple Siri represent AI applications with voice recognition. Additionally, IBM Watson, an AI platform, is used in the Memorial Sloan–Kettering Cancer Center, New York, to help oncologists optimize cancer care. This platform allows large dynamically curated data sets to be analyzed while also providing recommendations for personalized treatments (IBM, 2016).
The digital revolution involves informatics and big data, the transition from analog/mechanical technology to digitally operated devices, which started between 1950 and 1970 and continues today. Digital revolution drivers in the healthcare sector and in society include: computer’s increased speed and storage capability at cheaper prices (a phenomenon described as Moore’s law) (The Economist, 2016); cloud computing technology (The Economist, 2016); changes in patient behavior as they become more proactive in...