Exploring Big Data's Impact and Future in Healthcare Systems

This report delves into the application of big data in the healthcare industry, examining its various aspects and scope. It begins by defining big data analytics and its importance, then explores data gathering and sorting processes, along with the tools used for analysis, such as Hadoop and R. The report discusses how big data is used to improve healthcare management, understand patient demands, and gather consumer feedback. It also covers the advantages of using big data, including increased efficiency and more accurate services, while addressing the ethical issues and compliance requirements. The methodology includes a review-based approach using secondary data from journals and articles. The expected outcomes include outlining the use of big data, highlighting its advantages and identifying potential issues within the healthcare sector. The report concludes with a comprehensive project plan, including deliverables, a work breakdown structure, and a Gantt chart, along with a detailed reference list.

Running head: BIG DATA IN HEALTH CARE
BIG DATA IN HEALTH CARE
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Table of Contents
1. Project Domain.........................................................................................................................2
2. Purpose and Justification..........................................................................................................2
3. Research questions...................................................................................................................3
4. Conceptual framework:............................................................................................................3
5. Methodology............................................................................................................................3
6. Ethical issues............................................................................................................................5
7. Compliance Requirements.......................................................................................................5
8. Expected outcome....................................................................................................................5
9. Project plan...............................................................................................................................5
10. References................................................................................................................................8

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Title: Big Data Analytics in Health Care
Project type: Review Base
1. Project Domain
The use of new technologies such as big data is applied is different industry. One
of application of big data is in health industry (Ta, Liu & Nkabinde, 2016). The use of big
data in health care industry is increasing efficiency of the whole health care process.
Apart from that the use of data management provides more accurate services to the
patients and the consumers of health care sector (Groves et al., 2016). The big data is the
application through which the collection of data can be achieved. The tools used in the
big data analytics will help to sort out data accordingly which will fetch the useful
information that will help in the modification and the improvisation for the health care
system. Apart from that the feedback of the consumers can be taken and the useful
feedbacks can be generalized for the implementation through the big data analytics
(Zhang et al., 2017). The paper will discuss the different aspects and the scope of using
big data in health care industry. Scope of project and methodology used for the project
will be discussed.
2. Purpose and Justification
 Understanding the concept of big data.
 Getting familiar with the data gathering and the sorting process of the big data.
 The tools used in analysis of the information collected by the big data.
 The process of using the big data in the health industry.
 Impact of using big data in the health care industry.

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 Advantages of using the big data in health care industry
 Issues and challenges of using the big data in the health care industry.
3. Research questions
 What is big data analytics?
 How big data analytics is used in different aspects of health care industry?
 What are other implications of big data analytics in health care industry?
 What are the possible issues those can happen during the application of big data in
health care industry?
4. Conceptual framework:
Use of big data analytics in the health care management will improve the
management of the information regarding health care (Dimitrov, 2016). Apart from that
the demand of the patients can be understood from application of the big data in health
care management (Kruse et al., 2016). The preferences of the consumers can be gathered
through the surveys (Perrons & Jensen,2015). The feedback can also be taken in this form
(Wyber et al., 2015). After the collection of the information, the data and the information
can be sorted through different big data tools like Hadoop, R. The analysis will indicate
the demands of the consumers and on the basis of that certain modifications can be made
(Mathew & Pillai, 2015). It can be said that use of big data analytics will help the health
care management to adopt the dynamic requirements of the patients and the consumers of
the health care industry.
The analysis of the data and information can be done through different big data
tools like Hadoop. However, while using the big data , there are two aspects of the usage
of big data- technical usage and business management use. The technical implementation

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of big data can be done through the implementation of the tools. Apart from that the
business management usage of big data is about implementation of the big data for
managing the different aspects of the business. In the implementation of big data in
health care management, the business aspect of the big data is needed to be concerned.
5. Methodology
5.1 Research methods
Research method indicates the process through which the research is conducted. It
is a logical process that will help the research to progress in an organized manner.
5.2 Data Collection
Data can be collected in two methods- Data collection through primary method, data
collection through secondary method. In the primary data collection method, collection of
data is done from the surveys conducted on the users or consumers. On the other hand in
the secondary data collection, data is collected from the secondary sources like journals,
articles.
As it is a review based research, secondary data collection is used in this research.
The data regarding the application of the big data are collected from the different articles
and sources.
5.3 Analysis of data:
Analysis of data can be done through quantitative and qualitative data analysis. In
the qualitative data analysis, evaluation of the data is done on basis of information taken
from the journals and articles. This is a theoretical approach to the data analysis. In the
quantitative evaluation of the data, the analysis is done on the numerical data. In this

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context. The surveys are done of the selected group of people in order to know their
feedback. The information collected from the surveys are analyzed in a proper way. On
the basis of the analysis the conclusion can be made.
In this research, the qualitative analysis of the data is adopted. The justification of
choosing this kind of analysis is that the research is review based and the exploration of
the different theories regarding this topic is discussed in this section.
6. Ethical issues
 No data is manipulated during the course of the research.
 The confidentiality of the organization and the individuals has been maintained
during the development of the project.
 The research is not biased, hence it can be assumed that the outcome of the
research would be neutral.
7. Compliance Requirements
The rules and regulations of the organization has been maintained during the
course of the research project. Apart from that proper steps for the development of the
project is maintained. No data has been manipulated during the course of the research.
The use of the necessary equipment has been used in a proper order.
8. Expected outcome
 The project will help to outline use of big data in the health care sector.
 The project will indicate the advantages of using big data in health care sector.

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 The project will also indicate issues regarding the big data in health care sector.
9. Project plan
9.1 Deliverables
9.2 Work break down structure

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9.3 Gantt chart

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10. References
Dimitrov, D. V. (2016). Medical internet of things and big data in healthcare. Healthcare
informatics research, 22(3), 156-163.
Groves, P., Kayyali, B., Knott, D., & Kuiken, S. V. (2016). The'big data'revolution in healthcare:
Accelerating value and innovation.
Kruse, C. S., Goswamy, R., Raval, Y., & Marawi, S. (2016). Challenges and opportunities of big
data in health care: a systematic review. JMIR medical informatics, 4(4).
Mathew, P. S., & Pillai, A. S. (2015, March). Big Data solutions in Healthcare: Problems and
perspectives. In 2015 International Conference on Innovations in Information,
Embedded and Communication Systems (ICIIECS) (pp. 1-6). IEEE.
Perrons, R. K., & Jensen, J. W. (2015). Data as an asset: What the oil and gas sector can learn
from other industries about “Big Data”. Energy Policy, 81, 117-121.

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Ta, V. D., Liu, C. M., & Nkabinde, G. W. (2016, July). Big data stream computing in healthcare
real-time analytics. In 2016 IEEE International Conference on Cloud Computing and Big
Data Analysis (ICCCBDA) (pp. 37-42). IEEE.
Wyber, R., Vaillancourt, S., Perry, W., Mannava, P., Folaranmi, T., & Celi, L. A. (2015). Big
data in global health: improving health in low-and middle-income countries. Bulletin of
the World Health Organization, 93, 203-208.
Zhang, Y., Qiu, M., Tsai, C. W., Hassan, M. M., & Alamri, A. (2017). Health-CPS: Healthcare
cyber-physical system assisted by cloud and big data. IEEE Systems Journal, 11(1), 88-
95.
Groves, P., Kayyali, B., Knott, D., & Kuiken, S. V. (2016). The'big data'revolution in healthcare:
Accelerating value and innovation.
Hilbert, M. (2016). Big data for development: A review of promises and
challenges. Development Policy Review, 34(1), 135-174.
Yue, X., Wang, H., Jin, D., Li, M., & Jiang, W. (2016). Healthcare data gateways: found
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Gudivada, V. N., Baeza-Yates, R., & Raghavan, V. V. (2015). Big data: Promises and
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Almalki, M., Gray, K., & Sanchez, F. M. (2015). The use of self-quantification systems for
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Mittelstadt, B. D., & Floridi, L. (2016). The ethics of big data: current and foreseeable issues in
biomedical contexts. Science and engineering ethics, 22(2), 303-341.
Yaqoob, I., Hashem, I. A. T., Gani, A., Mokhtar, S., Ahmed, E., Anuar, N. B., & Vasilakos, A.
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