Big data can help healthcare providers gain valuable insights from large volumes of patient data. By processing data at large scale and high speed, issues can be identified in real-time to make evidence-based decisions. Healthcare has undergone technology-driven changes due to digitization and data growth. Big data enables precision medicine by detecting meaningful patterns in vast amounts of data. It also allows for improved research and individualized treatment through comprehensive analysis of linked data sets. However, privacy and security of patient data must be ensured according to regulations like HIPAA.

1. Big Data in Healthcare
Hospital and healthcare providers can use big data to expand the
scope of their projects and draw comparisons
over larger populations of data. Because big data involves the
use of automation and artificial intelligence, data can be
processed in larger volumes and higher velocity to uncover
valuable insights for Management.
Big data enables management to proactively identify issues with

2. real-time access to the data so that decisions can be base more
on hard evidence and facts, rather than emphasizing on
guesswork and assumptions about customers, employees, and
vendors. Applying analytics to big data creates many
opportunities for healthcare businesses to gain greater insight,
predict future outcomes and automate non-routine tasks.
Healthcare industries have gone through massive technology
driven transformations over the past decade. This is a result of
the significant advancement in digitized, disruptive, open
sourced and pervasive healthcare information technologies and
peripherals in application, that are continuously producing huge
volumes of diversified data. In a recent literature review,
Agrawal and Prabakaran1 suggested that big data are an integral
part of “the next generation of technological developments” that
reveal new insights from vast quantities of data being produced
from various sectors, including health care. (Shah J Miah,
Edwin Camilleria, and H. Quan Vub).
Healthcare requires a lot of analysis and less room for error,
with big data and analytics procedure can be game changer.
Healthcare busines requires to analyze, store, and continuously
update patient’s data and these tasks cannot efficiently be
achieved without the help of big data.
According to Pastorino, the use of big data in health care can
provision the design of solutions that improve patient care and
can generate value and new strategies to overcome dynamic
challenges in healthcare organizations. This is attributed to big
data in health care providing an opportunity to detect
meaningful patterns, which in turn produce actionable
knowledge for precision medicine and various healthcare
decision-makers. (Shah J Miah, Edwin Camilleria, and H. Quan
Vu)
Harmony Alliance stated that opportunities offered by big data
“will only materialize when healthcare systems move beyond
the mere collection of large amounts of data. Linkage of
previously separated data sets and their analysis using
appropriate big data analytics offer new ways to accelerate

3. research and to identify the right treatment for individual
patients. Access to large data sets that paint a more
comprehensive picture of patients allows patient-relevant
outcomes to be measured more accurately.”
Big data is becoming crucial in this time of Covid-19, where
data need to be collected from different corner of the globe.
Data are collected in a big amount and need to be processed in
real time so the decision-makers can have enough information
to work on. Today’s world is interconnected, and pandemic are
coming quick and fast, therefor real time data from all over the
globe need to be processed and analyze through different
organization like OMS and CDC. Big data and analytical
procedures made these tasks feasible by its vast capacity to
store and process data in real time through the cloud system or
other form of technologies.
Big data have introduced new opportunities during the digital
revolution for enhancing healthcare service. The main issue
which always arise in Healthcare business is the privacy and
data security of patient, which is dictated by the HIPAA Act,
which is the Privacy Rule, a Federal law, that gives you rights
over your health information and sets rules and limits on who
can look at and receive your health information. The Privacy
Rule applies to all forms of individuals' protected health
information, whether electronic, written, or oral. The Security
Rule is a Federal law that requires security for health
information in electronic form. ( https://www.hhs.gov/hipaa/for -
individuals/guidance-materials-for-consumers/index.html).
In recent days, many companies where hacked and data bridge
affected a lot of business. This can become problematic
especially in healthcare business. Big data has so many
advantages, however one of the disadvantages is the data
security. Cloud computing is to place computing, storage, and
other resources in the virtual network rather than the local
servers, which enables users easily and quickly to access
computing resources and storage resources that they need.
Because the statistical analysis of data can find the correlation

4. between different data, the law of disease occurrence in
seemingly unrelated data, effectively realize the prevention of
disease and help doctors make accurate diagnosis and treatment,
the medical cloud has shown vigorous vitality (Xiaohan Hu)
To solve the trust problem generated by each node in the
medical cloud system during the interaction process, a dynamic
access control model based on trust evaluation was proposed.
The model uses entropy weight method and fuzzy theory to fit
the comprehensive interaction trust value of nodes, add the role-
based two-way selection mechanism and third-party real-time
monitoring mechanism for dynamic access control. Give the
specific procedures and methods. Through simulation and
comparison experiments with the classic Eigen-Trust model and
RBAC, we can see that the model proposed has great advantages
in dynamic controllability, time complexity and trust accuracy.
( Xiaohan Hu, Rong Jiang, Mingyue Shi and Jingwei Shang
School of Information, Yunnan University of Finance and
Economics).
Big data may be very effective especially in accounting for
healthcare business. The accounting for healthcare business is
complex due to many regulations and different insurance
policies. Revenue recognition is complex due to contractual
adjustments or high non collectable revenues.
With big data and analytical procedures, these tasks can be
simplified and help to project a pretty accurate revenue forecast
and adjust quickly to different changes in insurance policies.
Big data is a crucial player in today’s healthcare business. With
the technology’s development and the interconnected world, we
live in, health issues should be based on facts, real time data so
we can be able to prevent future pandemics, or at least have
enough information to be able to manage any outbreak in any
place on the globe. This can only be achieved with the help of
Big data and analytical procedures.
Reference

5. · Big Data in Healthcare Research: A survey study Shah J Miah
a , Edwin Camilleria , and H. Quan Vub
· A privacy protection model for health care big data based on
trust evaluation access control in cloud service environment
Xiaohan Hu, Rong Jiang, Mingyue Shia,b,c and Jingwei Shang
School of Information, Yunnan University of Finance and
Economics, Kunming, China bKey Laboratory of Service
Computing and Safety Management of Yunnan Provincial
Universities, Kunming, China cKunming Key Laboratory of
Information Economy & Information Management, Kunming,
China
· Big Data in home healthcare: A new frontier in personalized
medicine. Medical emergency services and prediction of
hypertension risks