This chapter provides better understanding and use-cases of big data in healthcare. The healthcare industry generates lot of data every day, and without proper analytical tools, it is quite difficult to extract meaningful data. It is essential to understand big data tools since the traditional devices don't maintain this vast data, and big data solves the major issue in handling massive healthcare data. Health data from numerous health records are collected from various sources, and this massive data is put together to form the big data. Conventional database cannot be used in this purpose due to the diversity in data formats, so it is difficult to merge, and so it is quite impossible to process. With the use of big data this problem is solved, and it can process highly variable data from different sources.
TopIntroduction
Information Technology plays a vital role in today’s industries by acting as a business enabler. The amounts of data currently generated by the businesses are massive and increasing exponentially. Especially the data produced in the healthcare industry is quite huge due to various forms of data such as audio and video files, images and other types of data, which are very crucial and valuable. Because of the ongoing substantial increase in the data, the traditional storage devices slowly become obsolete due to their limitations in computing. Thus, the concept of Big Data has evolved to overcome the boundaries of the legacy storage system. Big Data is just raw data collected from different sources, which will not be able to perform any analytics or decision making for the businesses.
Healthcare industry needs to collect and analyse a vast amount of data for enhancing the efficiency and effectiveness of medical treatment and share new treatment methods within the medical fraternity promptly. Hence, the data has to be analysed efficiently within minimum time. To compute and validate the vast amount of data, Big Data Analytics is needed. Moreover, Big Data Analytics will be very useful in the healthcare industry for developing countries to increase the quality of treatment by curing the diseases quickly and prevent the recurrence of the diseases. Big Data Analytics can discover the disease pattern and disease outbreaks. Some of the Big Data analytical tools in the healthcare industry can reduce the cost, prevent the disease and get the potential benefits. The combination of Big Data and Analytics in healthcare can prevent risk portfolios faster and detect fraud.
According to Technopedia Target (2019), Big Data is defined as large volume of data, which are in the formats of structured, unstructured and semi-structured, which is complex for existing machine and software technologies to analyse. The cost effective, enhanced insights and decision making is the main target for the Big Data. As per Health IT Analytics (2020), Big Data in healthcare refers to electronic health data sets that are so large, complex, and difficult to manage with traditional software and/or hardware; nor can this be managed with traditional or common data management tools and methods.
Characteristic of Big Data
Big Data has specific characteristics illustrated by ‘Five Vs’ (Vartika et al., 2020). They are Volume, Velocity, Variety, Value, and Veracity, which is symbolically known as five V’s.
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Volume: The amount of data in healthcare, which are in the forms of reports, scan images and X- rays.
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Velocity: Velocity is the speed at which data is collected from healthcare. This also includes comments via Social media as user views, posts in case of epidemic natural disaster, RFID tags, sensors, smart metering.
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Variety: The data, which is collected from the analysis of patients for effective treatments. The formats in which the data are produced are variety. The three formats of Big Data are structured, unstructured and semi-structured. Structured data is in common spreadsheet format which is easy for computing whereas Unstructured data are such as Electronic Medical Report, CDSS, Physician prescription, image, texts, audio and videos and are complicated for processing (Revanth Sonnati, 2017).
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Value: The data, which are produced in healthcare from social media sometimes, can be of fake news. The patients should always provide genuine data, which is very important for analysis. The patients’ data collected are still of high value, and it should be of quality for the medical industry. Electronic Medical Report and Electronic Health Record are valuable for better analysis.
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Veracity: Health is the main factor for everybody in this world. In healthcare, all the data generated are precious and vital because it has the patients’ report history. In case the data loss happens, the patient’s life may become miserable. It should be kept very careful to get better results. The medical reports have some specific information, which should be of trustworthiness.