ITC93001 Report On Application Of ‘Big Data' And ‘IoT’ In Healthcare Sector

Introduction

In current times, the Internet of Things (IoT) has emerged as a promising technology as it enables several heterogeneous objects to connect and increase information availability (Kranenburg, 2008). Xu et al. (2014) added that IoT has found large scale implementation and applications in various industries: energy, healthcare, security, and military- to name a few. Ge et al. (2018) surveyed eight domains to understand the application of IoT and ‘Big Data’. One such domain is the healthcare where IoT has gained prominence. 

The need for such developments in the healthcare sector could be attributed to several factors including the increased need for healthcare coverage, increasing healthcare costs, and changed reimbursements trends (Zillner & Neururer, 2016).  In this report, the application of the Big Data in healthcare is examined by conducting a brief literature review, which is followed by a critical analysis of the application of Big Data in healthcare. 

Literature Review

Healthcare is a sector which has a direct influence on the lives of people. However, there are several inefficiencies in the system (in term of information availability) which has resulted in multiple studies being conducted on big data analytics in the domain (Ge et al., 2018). The need for the studies could be attributed to the fact that the Big Data in healthcare is expected to assist in the prediction of the outcome of epidemics and diseases, prevent disease development and premature deaths, and improve treatment and overall quality of life (Fatt & Ramadas, 2018). 

In the healthcare sector, there are six important stakeholders which have different interests: The first stakeholders are the patients who are interested in getting high quality yet affordable healthcare. Zillner and Neururer (2016) highlighted that currently, there is limited data available about the health conditions of the patients. The second stakeholders are the hospital operators who are interested in optimisation of their income from treatments i.e. improved care and processes, improved resources utilisation, and automated routines. The third stakeholders are the physicians and clinicians who are interested in automation of routine process so that they can dedicate more time to important activities like looking after patients. These stakeholders are also interested in accessing, aggregating, analysing, and presenting health data that enables them to make informed decisions about treatment. The fourth stakeholders are the payors (governmental and private healthcare insurers), who are currently using payment systems based on simple information exchange with the healthcare providers. The payors are interested in understanding more about the treatment procedures- so that they can decide if the treatment should be covered in the scheme or not. The fifth stakeholders are the research companies (life science, pharmaceutical, clinical research, and biotechnology) who are interested in getting high-quality information in volume so that they can integrate the information from multiple and heterogeneous sources to improve the overall healthcare for patients.  The sixth stakeholders are the medical product providers who are interested in using clinical data so that they can increase their learnings about the performance of their products in comparison to the performance of the products by the competitors. These learnings will enable them to develop strategies to strengthen their market performance and increase their revenue (Zillner & Neururer, 2016).  

Manogaran et al. (2017) argued that the underlying reason why IoT has gained prominence in healthcare is due to its applicability in managing Big Data in term of volume, variety, value, veracity, validity, variability, viscosity, virality, visualisation and velocity.  Qiu (2017) argued that the above benefits of the Big Data are useful in the healthcare as gathering and analysis of real-time medical information minimises the errors and limitations associated with the traditional medical treatment. Another application of IoT is that the Big Data about the medical information about the patient can be stored on cloud platforms (Hossain & Mohammed 2016). The detailed and easily available information enables the healthcare organisations to apply the information in developing new services and solutions as well as optimising the existing services and solutions in the areas of nutrition, medicinal devices and products, health insurance, medical facility, and remote monitoring. This improves the overall healthcare for patients. 

Ge et al., (2018) argued that the application of Big Data lifecycle and processes in a domain can be observed across four aspects- storage, cleaning/cleansing, analysis/analytics, and visualisation. The above-mentioned four aspects will serve as the theoretical framework to analyse to understand the penetration of IoT and Big Data in the healthcare domain.