Analysis of Health Big Data Analytics: Current Perspectives, Challenges and Potential Solutions

The article analyzes the research article titled “Health big data analytics: current perspectives, challenges and potential solutions” by Kuo et al. (2014). The paper discusses the characteristics of big data in healthcare, its challenges, and potential solutions. It also presents a framework to guide healthcare workers in analyzing health big data. The study greatly contributes to the advancing BDA in healthcare.

Running head: WEEK 6 DISCUSSION
Week 6 discussion
Name of the Student
Name of the University
Author note

1WEEK 6 DISCUSSION
The assignment deals with the analysis of the research article, titled, “Health big data
analytics: current perspectives, challenges and potential solutions” by Kuo et al. (2014). The
article is focused on the big data use in the health care. The objective of the paper is to discuss
the characteristics of the big data of health and its challenges. The researcher aims to identify the
solution for health big data analytics to design the pipelined framework to guide the heath care
workers. The health care providers face challenge to extract data from the health information
systems such as CPOE, EHRs, PACS and CDSS, that are generating huge volume of data. The
author discusses and analyses various data sets such as OASIS, and UHDDS. The framework
developed by the author enables the users to characterise the health big data and specific factors.
It will enable the users to investigate analytic challenges and solutions in the data process
pipeline. The author has well addressed research questions by developing the framework based
on solutions for challenges in the area of data aggregation, maintenance, integration, analysis,
and interpretations. The findings are relevant as the data aggregated are from the old and new
literature. The data incorporated by the author in this regard is sourced from research conducted
from 2005 to 2015. The study greatly contributes to the advancing BDA in healthcare.
Nurses are frontline carers of patients and play vital role in collection of health data.
Intense use by the nurses and clinicians will lead to major breakthrough and innovations. This is
based on the evidence from big changes already occurred through use of big data (Brennan &
Bakken, 2015). It includes pairing of the big data with a single lead EEG for cardiac monitoring.
The next thing is the storage of the medical imagery, health records, to digital storage method
(Sensmeier, 2015). Further, innovations may include application of predictive technology in
more areas using artificial intelligence. It would be easier to predict people who may be sick.
However, the privacy issues are out weighting the advantages. The nurses must be tech savvy

2WEEK 6 DISCUSSION
enough to preserve the confidentiality of the information. The health care providers too believe
in overhaul to the current privacy regulations. However, fraud detection system in big data can
overcome and outweigh this drawback (Brennan & Bakken, 2015).
The local health authorities can use the secondary source of health data to get the
magnitude of health issue. Data includes patients health records, personal health records, health
databases, and survey reports. However, the confidentiality must be maintained and misconduct
must be addressed. The examples of the secondary health data sources are Disability and Health
Data System, CDC wonder, West Virginia Annual Surveillance Data for Reportable
Diseases,and in Austraaliaa, the Handbook for the Management of Health Information in Private
Medical Practice are some examples of secondary sources of health data. For instance, CDC
wonder produces customised table on the cancer statistics, AIDS, birth, STDs and others
(LaTour et al., 2013).

3WEEK 6 DISCUSSION
References
Brennan, P. F., & Bakken, S. (2015). Nursing needs big data and big data needs nursing. Journal
of Nursing Scholarship, 47(5), 477-484. DOI: https://doi.org/10.1111/jnu.12159
Kuo, M. H., Sahama, T., Kushniruk, A. W., Borycki, E. M., & Grunwell, D. K. (2014). Health
big data analytics: current perspectives, challenges and potential solutions. International
Journal of Big Data Intelligence, 1(1-2), 114-126. Retrieved from:
https://sci-hub.tw/https://www.inderscienceonline.com/doi/abs/10.1504/
IJBDI.2014.063835
LaTour, K. M., Eichenwald, S., & Oachs, P. (2013). Health information management: Concepts,
principles, and practice. Ahima. ISBN: 1584261420, 9781584261421
Sensmeier, J. (2015). Big data and the future of nursing knowledge. Nursing
management, 46(4), 22-27. DOI: 10.1097/01.NUMA.0000462365.53035.7d