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HEALTHCARE DATABASES AND DECISION-MAKING
Module 9 – Healthcare Big Data and Analytics
Big Data in healthcare denotes a massive volume of data generated at a high velocity by
digital healthcare technologies and may contain patients’ health record, operational and
financial information. These data sets are too huge to be processed by routine technologies
and thus needs special tools, like RStudio to analyze and reveal underlying trends that
otherwise may remain hidden. RStudio, an integrated software suite that facilitates
voluminous data manipulation, calculation, and graphical display and is the subject of this
module. Sifting through this massive amount of data for revealing the hidden trends can lead
to improving patient care, lowering healthcare costs, and preventing healthcare fraud and
abuse.
Module 9 Objectives:
After completing this module, you should be able to:
1. Assess sources and complexities of healthcare Big Data.
2. Evaluate the use of RStudio in analyzing healthcare Big Data.
3. Evaluate role of Big Data in improving patient care.
Module 9 Readings
Big Data in Healthcare: All You Need to Know Big Data in Healthcare: All You Need to
Know | Digital Authority Partners.
Big Data Analytics and Intelligence: A Perspective for Health Care Chapter 1 – Big Data
Analytics and Intelligence: A Perspective for Healthcare, pgs. 20-34; Chapter 2 – Big Data
Analytics in Healthcare: Need, Opportunities, Challenges, and Future Prospects, pgs. 36-44.
What is R https://www.r-project.org/about.html.
Module 9 Resources
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How Big Data is Changing Healthcare https://www.talend.com/resources/big-datachanging-healthcare/.
Bid Data in healthcare: management, analysis, and future
prospects https://journalofbigdata.springeropen.com/articles/10.1186/s40537-0190217-0.
Benefits and Challenges of Big Data in healthcare : an overview of the European
initiatives https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859509/.
Big Data in Healthcare Explained https://www.impactmybiz.com/blog/big-datahealthcare-explained/.
Discusssion
Big Data in healthcare is a recent development seen only after the implementation of Health
Information Technology (HIT) as Electronic Health Record (EHR) and Health Information
Exchange (HIE). While EHR systems collect and store health information, the HIE exchanges
it between providers. Evaluate the contribution of both these technologies to healthcare Big
Data at present and in future. Since Big Data cannot be analyzed by ordinary data processing
application software, which two specific techniques would you recommend for analyzing it
and why? Analyze the information that could be revealed by these and how it be used for
improving healthcare quality in terms of patient outcomes and healthcare services delivery.
Your initial post comprising a minimum of 250 words should be submitted by Saturday
midnight, followed by a minimum of two (2) responses to classmates’ posts comprising at
least 150 words supporting, challenging, clarifying, or adding to the existing information. 2
credible sources should be used to support your ideas. Follow APA 7
Assignment
Analyze the purpose(s) R is used for healthcare Big Data analytics. What features of R would
be attractive to you as a healthcare data analyst and relevant to managerial decision-making?
Provide reasoning behind your choices. What is the difference between Programming
(Command-line) and GUI (Graphical User Interface) versions of R and which of these would
you prefer and why? Assess how your choice affects user experience in the efficacy and
effectiveness of the data processing. How to improve any identified shortcomings?
Your APA formatted assignment comprising 2-4, double-spaced, typed in 12-point Times
New Roman (or 11- point Calibri) excluding the Cover and Reference pages. 2 credible
sources should be used to support your ideas. Follow APA 7 format.
Copyright © 2020. Emerald Publishing Limited. All rights reserved. May not be reproduced in any form without permission from the publisher, except fair uses permitted
under U.S. or applicable copyright law.
Chapter 1
Big Data Analytics and Intelligence:
A Perspective for Health Care
K. Kalaiselvi and A. Thirumurthi Raja
Abstract
Big Data is one of the most promising area where it can be applied to make
a change is health care. Healthcare analytics have the potential to reduce the
treatment costs, forecast outbreaks of epidemics, avoid preventable diseases,
and improve the quality of life. In general, the lifetime of human is increasing
along world population, which poses new experiments to today’s treatment
delivery methods. Health professionals are skillful of gathering enormous
volumes of data and look for best approaches to use these numbers. Big data
analytics has helped the healthcare area by providing personalized medicine
and prescriptive analytics, medical risk interference and predictive analytics,
computerized external and internal reporting of patient data, homogeneous
medical terms and patient registries, and fragmented point solutions. The
data generated level within healthcare systems is significant. This includes
electronic health record data, imaging data, patient-generated data, etc. While
widespread information in health care is now mostly electronic and fits under
the big data as most is unstructured and difficult to use. The use of big data
in health care has raised substantial ethical challenges ranging from risks for
specific rights, privacy and autonomy, to transparency and trust.
Keywords: Patient predictions; electronic healthcare records; telemedicine;
medical imaging; patient engagement; predictive analysis; enhance security
1. Introduction
The concept of enormous data generated from various sources has been accepted
and implemented by a lot of information technology-based organizations nowadays. It helps various organizations to understand that capturing and storing all the
Big Data Analytics and Intelligence: A Perspective for Health Care, 1–16
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K. Kalaiselvi and A. Thirumurthi Raja
data that is being generated within the organization can be beneficial in the future
and can get useful insights. Few of the most important advantages that can be
gained with the help of using these generated data after analyzing are that it helps
in increasing the speed and quality of work in the working environment. Since big
data enables the working environment faster and agile it gives the particular organizations a competitive edge and uniqueness from other business organizations.
The implementation of big data analytics in any organizations lets them take
a step forward in securing their important data. Hence the data can be used in
later stages to identify new opportunities. This helps in building a better organization and takes an appropriate business decisions which will help in attaining
more profits and making the customers much happier. The various importance
of big data include as follows. Another important feature of big data is that it
not only helps in understanding enormous data but also helps in reducing the
cost incurred in various ways. By implementing big data technologies and various
data manipulation tools it helps in achieving cost advantages. It also ensures that
a large amount of collected data can be stored securely in order to ensure privacy
protection. A large amount of data can be securely stored and it can be used to
identify more efficient ways of doing business. Secondly, it helps in taking faster
and better quality decision. With the help of rapid speed analytical tools, various
resources and data can be combined to analyze new sources of data. Most of the
modern businesses are able to analyze the contents and format of information as
and when it is generated and make decisions by analyzing it (Panagiota, Korina,
& Sameer, 2019). It also helps in identifying new products and services that can be
manufactured to gain more profit and attract more customers. By understanding
customer needs and satisfaction through analytics it makes a huge percentage of
customers more satisfied.
Since big data and its analytical tools were introduced it has positively helped
in healthcare sector in order to save lives more and more. A vast quantity of information collected from various sources over the internet are collected and stored
so later on it can be analyzed various analytical tools. The analyzed information
can be later on applied to healthcare sector. By using data sets collected from
various sources to analyze healthcare situations it has helped to prevent and cure
diseases (Ahmed, Fathima-Zahra, & Ayoub, 2018). This also helps the doctors to
understand the medical history of the patients. These generated reports can be
used to understand if there is any possibility for serious illness. Treatment at an
early stage consists of less procedure and can help in reducing the cost incurred
by the patients. This also helps the insurance-based business companies or organizations to understand a better picture of patient’s medical history in order to give
tailored custom insurance packages.
This has also helped the healthcare area by providing personalized medicines
and medical risk interface to generate external and internal reports of the particular patient data. The data generated at various levels within healthcare systems
are significant. The sources of these data are mainly from electronic health records
(EHR), imaging data, patient-generated data, etc. While widespread information in
health care is mostly electronical and fits under the big data since most of the information are in unstructured format hence making it time consuming to understand
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Big Data Analytics in Health Care
Fig. 1
3
Various Applications of Big Data in Health Care.
and make useful information out of it (Uthayasankar, Muhammad, & Zahir, 2017).
The uses of big data in various sections of the society have increased at an unexpected rate. This has also increased the various challenges and risk involved. These
challenges are faced mainly with regards to rights, privacy, and trust.
The application mainly dependent on the healthcare section takes to help technologies that solve the issues based on computer diagnosis systems. The important task in this section is to upgrade the performance of the system to execute
the user required computing. Fig. 1 represents the various applications of big
data in healthcare industry. Most widely used areas in which these enormous data
can be implemented are mostly EHRs, to improvise security and privacy of the
patients, patient predication, medical imaging, patient engagement, and telemedicine. These are the few areas where big data and analytics are used.
2. Big Data Overview
The term big data describes a huge amount of information which can be in any
raw format are extracted from various sources in its raw format without making
any changes. The users require a computing system that can be powerful enough
to organize it and manipulate these data according to the needs of the user. Few
examples of these sources are mobile, internet, social media, etc. Later stages of
these raw data are used for further processing and can be used to make strategic
decisions. With the help of big data and its analytical tools it enables by providing
useful decisions that can be taken for future references. It also helps in understand
data that were collected decades ago find solutions accordingly. Usually any problems related to data are solved by understanding its scope and impact.
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K. Kalaiselvi and A. Thirumurthi Raja
The data collected from big data can be mainly of three types or format. The
three types are Volume, Velocity, and Variety. Volume mainly extracts the information from various channels, which includes websites that helps in establishing mass
communication and interaction and information generated based on machine-tomachine processing. In the early stages of big data, the main issue was related
to storage. Since the advancement in time and technology this burden has been
able to be reduced. Velocity refers to the process of collecting data, whereas the
third model refers to variety. In this process data can be in various formats of
structured, numerical information, and financial transactions. The main difference
between big data and data analytics is that big data analytics is the mechanism of
collecting large information for a particular task whereas big data is objective for
the progression of collecting data that is in raw format and needs further changes
to be made to understand and make meaningful information’s out of it. The tools
that are used for analyzing are referred to as analytical tools.
Few fields where big data mainly works are as follows: The information’s stored
in various flights are stored in black box. The data generated from this source
are huge and mainly stored in its original format as it is. The information in the
black box is regarding the communications made within and with the technical
staff. Various sites such as Face book and Twitter contain the information and the
views posted by people from all around the world. These can be either text, photos,
audios, or documents. Another source of big data is from Stock Exchange. The
data produced from stock exchanges are stored in servers so that in later stages it
can be used for various organizations to understand the market situations. It holds
information mainly regarding the price of public shares, financial transactions that
take in various business organizations that help the investors to understand how
profitable a business is. Power Grid Data is also a source from where data can be
extracted. Base station is like a data base storage unit since it consists of information regarding the power grid. Search Engine Data is one of the main sources of big
data that are widely used by enormous number of researchers. The data generated
from various search engines can be incorporated with existing problems to solve it.
3. Big Data Applications in Health Care
3.1. Various Sources of Data, Methods, and the Challenges Faced
The data retrieved from hospitals and other healthcare industry are difficult
to be controlled. It requires a lot of effort and modern techniques to conduct
experiments on these data. To conduct experiments, it is important to understand
the data, its contents, its source, and format. It is also important to organize it
according to various needs. The various difficulties faced can be solved if observational designs are optimized as much as possible to understand the data. The
main aim of conducting experiments is to understand the collected data (Etta &
Leah, 2019). These data are compared to understand if they are linked and corelated with each other in nature. The process of staffing at different levels of the
organization is analyzed to understand the outcome expected from the patients to
see if there exists some relation between the data.
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Big Data Analytics in Health Care
5
Correlational designs are mostly limited from conducting experiments and from
determining the relation between outcomes of two levels. Nurse staffing at different levels is the most important factor that help in predicting outcomes for correlational designs. These factors consist of information regarding the environments
like nursing care or other services. The data collected from statistical methods can
be controlled by various factors that are associated with staffing levels. These factors include the size of the hospital, academic affiliation, or location of the hospital. By carefully selecting the variables and data for processing will help in getting
maximum correlation outcome (Etta & Leah, 2019; Uthayasankar et al., 2017).
Reviewing the variables will help in understanding the factors that influences various stages of staffing. The host factors influence elements like important decisions
that are to be taken by the organization, quality of nursing care and clinical outcomes.
3.1.1. Levels of Staffing. Staffing levels are set by administrators of the particular organization and these factors are influenced by various forces such as
budgetary considerations and features of local nurse labor markets. The administrative department helps in forming the departmental, work hours, shifts, and
other incentives not only to the one level but also to the sub-levels (Antonio,
Luis, Maribel, Guilherme, 2019). The practice of the nurse is influenced by the
workforce design used in assigning work for a particular project. Few of the other
factors that influence the working environment are environment, methods of
communication, and the support services available.
There are various variables that contribute toward improving the care and needs
of the patient. These factors are inclusive of how serious the patient’s health condition is, if any previous medical conditions and family medical history. The health
situation of the patient can get worse or better during the stay in the hospital.
⦁⦁ The quality of care provided can results in appropriate execution of assess-
ments and also to improve patient’s health situation to get expected outcome
and prevent unexpected events. For example, the care provided by the nurses,
the examinations done by the doctors to understand the patient’s health condition, the medicines or drugs prescribed by the doctors are factors that help in
measuring the quality of the care.
⦁⦁ One main factor that is used to measure the quality standards is by giving more
importance to safety issues. For example, it is very important to measure the
accuracy of medical administration. If the doctors identify the patients’ health
problems at an early stage it will be much more beneficial and result in rapid
improvement of patient’s health condition.
3.1.2. Outcomes. Capturing and analyzing the patient information helps in
generating a summarized report so that it can be used in later stages for better
understanding. Even though it has resulted in great success still this method is very
challenging because it requires a lot of practical understanding and financial considerations. Medical records of patients are used widely in this area as secondary
source of data. To understand the outcomes most of the researchers usually use
summarized versions of patient records maintained by hospital. These data contain
useful healthcare records that explain mainly about how diseases are treated and
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K. Kalaiselvi and A. Thirumurthi Raja
also regarding the procedures undergone by the patients before date of discharge.
The quality and reliability of these documentations can be different depending on
various organizations and the way they maintain it. The form of maintaining electronic medical record helps in keeping information regarding assessment conducted.
Analyzing these documents or records will help in improving the performance of
the healthcare organization. Wider application of information technology in these
types of organizations will be helpful in various ways. This also leads to making
users search for data sources that can be trusted to improve performance.
If the healthcare settings are compared accurately it will help in understanding the
various risks the patients may face in the future. Eventually these reports are taken
for better understanding so that efforts can be increased with the help of risk adjustment methods. The methods of understanding risk are classified into two stages. The
first section understands to identify the population of patients that are risk. These
can be either categorized by age, gender, or various other related factors. The next
stage aims at collecting information that are valid and can be analyzed to understand
the population. With the help of risk adjustment, it is easier to find the mechanism
for staffing, and also improve the outcome expected. From various studies conducted
previously, it helps to understand the importance of staffing and safety outcomes. By
providing better quality care by the hospitals it helps in understanding how various
serious health issues can be avoided but it also helps in classifying the nursing care.
Whereas the positive outcomes cannot be expected if the staffing level is too low. Few
factors like psychosocial methods to cure problems and improve care, and the level of
self-care capability can be used in later stages for improving the results.
3.1.3. Conclusion. A difference can be seen in healthcare sections where staffing is less when compared to institutions where staffing is more. Most of the
researches that were conducted suggest that if nurses appointed are less than
required it creates unwanted dangerous situations for both patients and nurses.
Therefore, it is necessary to appoint necessary staffs as required to provide quality health care. Studies also suggest that increasing the staffing quantity alone will
not be enough to improve the outcome generated.
3.2. Electronic Health Records. Needs and Advantages
3.2.1. Introduction. The most important task of EHR is to help in understanding the medical background of patients with the help of electronic mechanism rather than using traditional techniques of maintaining papers or folders.
This helps in reducing time consumed to get the information. It also helps to
make the record easily available whenever required to access it. With the introduction of maintaining EHRs has saved money and also helped in accessing it at
multiple locations (Cano et al., 2017; Wang & Hajli, 2017). While the receptionist
is trying to register the appointment for the patient meanwhile the billing clerk
can access the same file using the electronic chart.
By maintaining various pre-defined templates of coding, it can help to easily
identify the history or details of the physical exam. A research conducted to understand EHR shows that it has improved the method of maintaining documents.
EHRs also help in providing a mechanism for taking decisions and to set alerts.
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Big Data Analytics in Health Care
7
3.2.2. Importance for Improving Efficiency and Productivity. One of the main
aims of maintaining EHR is that it helps to retrieve information’s regarding the
patients whenever required. Lab results can be gathered from decades ago with
less amount of time, thus saving time spend in visiting the labs and also reducing
the money spent. It also helps in reducing duplicated tests (Wang & Hajli, 2017).
A study conducted shows that using computerized method of entering records
have resulted in reduction of duplication.
EHRs are more efficient because it helps in reducing paperwork and have the
capability of submitting health claim automatically to the respective insurance
organization. EHR supports the doctors and other medical staffs in taking decision. Although EHRs appear to improve overall office productivity but still it
may increase the work load in data entry.
3.2.3. Application. The application of EHRs ranges from government sectors to financial sections of various industries. Few of the applications and the
expected outcomes from the particular industries are as follows.
The application of EHR’s in Government institutions (Sutherland et al., 2016)
are considered transforming in the section. It is the goal of the Government to
have a dependent and reliable EHR for future references. The introduction of
EHR has created an awareness of the potential benefits to help coordinate and
improve disease management in older patients. A survey conducted in the year
of 2007 showed that with the introduction of EHR has helped in avoiding the
malpractices.
3.2.4. Aggregated Data. Since decisions are to be taken based on the past
experiences, most of the organizations collect high quality data in raw format.
These data are mainly procured from the data collected from inpatient and outpatient data and details regarding the populations at risk. The healthcare data
after it is extracted need to be analyzed to gain meaningful information. In near
future large healthcare organizations will have to adopt electronic health recording systems and big data analytical tools to organize the data.
3.2.5. Integrated Data. The main disadvantage of maintaining paper-based
health records in that it can be used to combine other paper health records
and store as the same. Since this mechanism lacks the ability to integrate with
other paper forms of information EHRs base mechanisms are introduced. This
information can also be used with various other sections of the healthcare sector to take useful decisions. These applications include ability to combine and
integrate data.
3.2.6. Conclusion. In order to modernize the infrastructure in healthcare sector it is required to adopt and implement EHRs-based systems. A survey conducted to understand the importance of EHR shows that it helps to identify
patients with serious health condition and use various tools that are available to
save their life and get a better understanding of the population.
EHR system also helps to decrease the number of office visits. The introduction of EHRs has helped in improving in setting a standard of care to be provided
by nurses and understand population health. This has also helped in improving and advancing EHRs. In addition, it has helped in the process of collecting
genomic information for future linking to their electronic records.
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3.3. Enhancing Patient Engagement
3.3.1. Introduction. The healthcare industry like any other sector of the society works mainly to gain profit and survive in the business field. Since patients are
the most important factor in the healthcare institutions it is important to ensure
they are satisfied. Few of the methods to improve the business are by improving
the quality of care provided for the patients and the environment of the hospital.
This helps in engaging with more and more patience and understanding the rate
of staff required take care of the patient’s health.
One of the most important ways to increase this engagement rate is by combining the various outcome reports with hospital environment settings. Later stages
these data can be used for analyzing the outcomes and increase the care to provide
for the patients. The main challenge is to ensure that the privacy of the patients
is securely preserved (Patient-Centered Outcomes Research Institute, 2013). This
mechanism ensures that while collecting the data and the generated report can
only be provide directly to the patient to secure the privacy. Most of these types
of reports mainly consist of information regarding the patient’s health condition,
information describing the symptoms, etc. Finally, the future challenge is to maximize the implementation of these reports in clinical settings and staffing.
A previously conducted research suggests it is the patients that take decisions
regarding their health. Hence the systems that is being used in the healthcare
institutes needs to be developed in such a way that it provides the required freedom to the patients and enables to take appropriate decisions. At the same time, it
is important to ensure that these records can be accessed by the patients whenever
required. It also suggests that more steps need to be taken to improve data that
are provided.
With the improvement of the new technologies that is available and introducing appropriate changes in what the customers expects will increase the profit day
by day. Even though the time consumed for this is increasing when rapid progress
and advances are only limited. One of the most widely used mechanism that supports making patients more engaged in healthcare delivery is by using the reports
and the outcomes to measure the impact and improvement. These reports and
their outcomes are developed individually by using traditional techniques. The
reports generated after analyzing the records are used in later stages to take useful measures. This helps in giving a much better insight into how the patient can
improve their health. Analyzing these reports it helps to understand the patient’s
health condition and if there is any improvement. It enables to identify and judge
if the person is ready to go back to his daily activities. It also helps in establishing a
communication between the patient and the doctor to take appropriate decisions.
3.3.2. Patient-reported Outcomes. Most of the people who invest in a healthcare sector are mainly interested in improving and expanding the existing business. There are few techniques that are followed to increase the profit. One of the
techniques is by collecting patient data and generating report-based outcomes for
improving the care provided for patients. It also helps in getting feedback, introducing electronic data collection, and understanding the needs of the population
to help in taking decisions. Thus, from this it is clear that with the adoption of
patient-reported outcomes it has resulted in a lot of advantages.
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