Big Data Analytics in Health Care
Name
Institution
Date
,BIG DATA ANALYTICS IN HEALTHCARE 2
Contents
Background, Motivation and Relevance......................................................................................................2
Background..............................................................................................................................................2
Motivation...............................................................................................................................................6
Relevance................................................................................................................................................7
Sources of Knowledge.............................................................................................................................7
Mind Map................................................................................................................................................8
Scope, Objectives and Risk..........................................................................................................................9
Scope.......................................................................................................................................................9
Objectives................................................................................................................................................9
Steps ensuring aims of the healthcare system are achieved...................................................................9
Task List.................................................................................................................................................11
Schedule of activities.........................................................................................................................11
Risk Log..............................................................................................................................................14
Bibliography...............................................................................................................................................16
Background, Motivation and Relevance
Background
The study will largely focus on big data analytics in the United Kingdom healthcare
system. The study will particularly revolve around big data analytics in healthcare in the UK.
The UK national health system is currently facing numerous challenges which have been
initiated by internal and external factors. The UK health system has encountered numerous
difficulties due to population increase, life expectancy escalations and high medical costs
(Capgemini 2017, p.1). Additionally, chronic ailments have also gone up significantly over the
last decade. A big number of individuals are now living longer but suffering from ailments that
require regular hospital visits.
, BIG DATA ANALYTICS IN HEALTHCARE 3
This has initiated an overload in the UK healthcare system with approximately 243
million visits recorded yearly, which are approximately 460 appointments in one minute
(Capgemini 2017, p.1). Making use of the vast data will have a positive impact on the social and
economic outcomes for the UK population. It is estimated that more than two million UK
residents will be suffering from four or more chronic ailments in the coming 2 decades due to the
current sedentary lifestyle (The Guardian 2018, p.1). This further creates the needs to assesses
the UK healthcare system and necessitate the incorporation of big data analytics.
The Big data analytics concept refers to the grouping of data whose type, speed, size, and
complexity calls for the adoption and invention of updates software and hardware for successful
storage, analysis, and visualization of data (Wang, Kung and Byrd, 2018, p.7). In healthcare, data
production is guided by velocity (data seed generation), volume, and variety (Kankanhalli, Hahn,
Tan and Gao 2016, p.234). Data is divided among several healthcare systems, researchers, health
insurers, and government agencies. Additionally, each data repository is isolated from others and
incapable of availing data transparency (Belle et al. 2015, p.1). Veracity is also incorporated into
velocity, volume, and variety based on its significance in translational research development
(Datafloq 2019, p.1).
It is worth noting that healthcare data is inherently complex (Shahbaz et al. 2019, p.6).
However, the realm can be developed through big data solutions. Traditional medical research
approaches primarily prioritized on investigating ailments based on physiological changes using
singular data modality (Belle et al. 2015, p.1). Although the approach in comprehending diseases
was paramount, the methods ignored interconnectedness and variation defining the medical
mechanisms. Following years in technological improvements, the medical fields have become
accustomed to the current digital data era (Shahbaz et al. 2019, p.7). Through new technologies,