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Top1. Introduction
As the health industry is undergoing a digital transformation, adopting pervasive and remote healthcare (Pramanik, Upadhyaya, Pal, & Pal, 2018), it generates a massive amount of data on a daily basis. Compared to business and other industries, even though the health industry has been known to lag in adopting big data technologies, healthcare data, both in terms of size and nature, are nothing less than big data (Pramanik, Pal, & Mukherjee, 2019). With rapidly changing medical and clinical practices (Pramanik, Nayyar, & Pareek, 2019) (Pramanik, Pareek, & Nayyar, 2019), key stakeholders in healthcare are now forced to delve into understanding everything to know about big data and their associated benefits.
Suddenly, big data has become crucial for almost every operational, clinical, and management task (Bresnick, 2017). The healthcare people are now convinced of the benefits of big data and persuading themselves to analyse the data for extracting new insights that have given them the access to promising new threads of knowledge which are being transformed into innovative and purposeful actions (Groves, Kayyali, Knott, & Kuiken, 2013).
Several healthcare use cases are well-suited for incorporating big data technologies. The healthcare big data analytics has opened up many exciting avenues in different healthcare operations, including diagnosis and medical care, clinical decision support, population health management, etc. (Bresnick, 2017) (Pramanik, Mukhopadhyay, & Pal, 2021). The underlying value of healthcare big data has allowed healthcare and other related service providers to explore new opportunities and innovative service models. The striking advantage that healthcare big data bring in is that providing healthcare services is no more mere one dimensional, i.e., not dependent on just one or a few fixed variables, rather it endows a more holistic delineation of individuals or mass populations, by formulating positive correlations based on a diverse range of variables. This facilitates discovering new insights.
The success of healthcare big data is mostly dependent on the efficient collection and storage of massive quantities of disparate data acquired from diverse sources and also running it through an in-depth analysis (McDonald, 2017). Big data analytics helps to discover associations and understanding patterns and trends within the data (Raghupathi & Raghupathi, 2014). The effective utilization of healthcare big data and the knowledge obtained through analytical processes have the potential to save a significant amount of money and, most importantly, people’s lives (Lebied, 2018).
This paper provides a preliminary and overall understanding of healthcare big data and analytics. The organisation of the paper is shown in Figure 1.
Figure 1. Highlights and organisation of the paper