Page 208 - Big Data Analytics for Intelligent Healthcare Management

8.2 HEALTHCARE BIG DATA AND BLOCKCHAIN OVERVIEW 201

Body checkup report

Traditional
patient
data
Images

Electronic
medical records
Sound file (EMR) Lab tests

X-ray images
Diagnoses

Medications
FIG. 8.3
Electronic medical record (EMR).

the expected amount for 2020 is 2314 exabytes. However, with a 48% rate of annual increase, it is
8
expected to enter the yottabyte (one yottabyte ¼ 1000 bytes) range. A survey [22] reported that
the healthcare analytics industries are growing at an exponential rate with a compound annual growth
rate (CAGR) of 27.3% and this is anticipated to reach 29.84 Billion USD by 2022 from 8.92 Billion
USD in 2017.
Besides physical data breaching, medical data can be breached during medical signal processing
and sharing [23]. Therefore, a context-aware big data processing is highly needed where before data
processing the type (personal, nonpersonal, sensitive, etc.) of data must be well-analysed was men-
tioned by Reddy et al. [24]. Panigrahi et al. [25] mentioned big data security aspects in detail. That
study deals with the different use of cloudlets for big data and focuses on the details of cyber foraging
systems to manage different characteristics of healthcare big data.
According to a report by Guardian [26], 26% of consumer’s medical records were breached in the
United States. A similar source reported 10 of the biggest healthcare data breaching incidents listed by
United States Department of Health and Human Services Office for handling civil rights. Anthem Blue
Cross, a giant health insurance company, breached 80 million healthcare data on January 29, 2015. The