Leveraging Big Data and Predictive Analytics in Healthcare: A Report

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Management challenges in creating value from business analytics

Abstract
In the past 10 years, the technology of big data has been gaining the attention of people at a very
high rate and the major drawback for the industries is in gathering the information on the way
leveraging this technology into their business interest and benefits. Although, during the
literatures acknowledgment of the need of these subjects, some small amount of tasks have been
addressing them by the organizational approach. In this report, the dos and don'ts of the business
analytics are talking about[1]. After going through this report, a learner would be able to perform
the tasks such as, using the predictive study of business analytics in the healthcare sector,
comparing the BI tools, having the information about the methods to be used for the predictive
study, techniques for the representation of visualizing the multidimensional data, methods for the
betterment of logistical management and ways to secure data and concerned associated with the
privacy of analytics. The predictive analysis has turned out to be beneficial for every party that
has shown its involvement in the healthcare that includes Health care Insurer, Healthcare
industries, doctor and patient. In the case of the healthcare insurer, the predictive analysis can
help in identifying frauds in the insurances [1].
Source [1]
In the case of the healthcare industries, the predictive analytics has a compatibility with the
management systems that are used in hospitals, tracking systems that are created for the patients
and hence creating a powerful consumer bond managing process [2]. In the case of the doctor
and physician, the predictive analytics has the capability to support the estimation of the LOS,
rates of mortality, a factor that is responsible for potentials risks, and the readmission rates.
Keeping all this in mind, the doctors would be having the abilities to select the most appropriate
treatment that can be done for the patient. At last, the patients would be getting good quality
treatments at reasonable costs. As per the past studies that are done in this field, 87 percent of the

fatalities in hospitals in the United States are prevented by the help of the predictive tools that are
used in those hospitals. There are many tools that are used in the field of business management.
As per the older studies that were done in past in the same field, the analytics displays the 6th
phase of the diagnostic paradigm which is differentiated via a huge amount of volume of data
which is supported by the arrays of tool for gaining, proceeding, and visualization of data.The
earlier studies were done in the past on the same topic, also state that the Operational Research
community must ignore the habit of isolating yet must be addressing the challenge and
opportunity that are being given by “new data architectures, real-time analysis, and data
visualizing” [2].
The Delphi Study which was done with professionals that were chosen among big data and
business analysis group of organizations or the individuals or any kind of professional body. The
basic aim of this study was to the exploration of the problems that are being faced in the field of
big data and predictive analysis as well as to know the area of concern among the professional,
hence developing a width of information around the 2 major research queries [3]. The Delphi
Study is defined as a survey method that takes the use of a group of qualitative and quantitative
methods to collect the point of views of the experts with respect to any specific kind of issue or
situation. This is the reason why this study can identify as well as prioritize a group of challenges
associated with the management, that are faced by industries in developing their ability of

business data analysis [3].
Delhi Study Process.Source [3]
The studies that have been done in the past in the same field have told about 3 different activities
such as data display, data reductions, and verification of the data. The data displaying procedure
included the workshop professional who was responsible for the review of the represented
quality data while the workshop to build the cluster via any organizational notes was going on.
This created a segment of the initial data representation and data minimization components [4].
The considerable cluster and individual organizational note were then converted into
spreadsheets and then free went through reviewing process by 3 procedures prior to the
workshops. The main aim of these processes was to pull and remove redundant components,
summarizing and categorizing the limitation code, to minimize the data while moving forward.
There are 31 items that are identified in the Delphi study which are represented in Appendices in
priority of needs along with the details of the components that are provided to the responders.
Some of the main issues that are to be tackled along are:
(1) Managing data quality [4].

(2) Using analytics for improved decision making.
(3) Creating a big data and analytics strategy.
(4) Availability of data.
(5) Building data skills in the organization.
The 31 items were then coded from the Delphi study as per the model mentioned above. The 3
processes that were discussed above were also coded the components and then talked about the
major aspects of the separations in order to track the arrival of the codes. Where the maximum
number of the components is settled in comfort in a given sector, it is pretty established that there
is some span construct. Although, the maximum number of the components received a proper fit
below a unit construct. The earlier studies done in the same field shows that, on the basis of the
average rank per sector that ‘values’ and ‘market’ are 2 of the most important concerns, that the
industries face while changing the big data and analysis into business values.
In order to do the exploration of the key role of the business analysis methods in a better way, the
three case industries were investigated. The research design of this researched was considered to
be one of the best researches that are compatible in case of contextual providence of information
of an already present reality that is needed [4].
Source: [4]
This approach also lets the researched to obtain deep and rich information and involvements into
the emergent phenomenon. Therefore the main goal of this research is to obtain a deep
knowledge with respect to the changes and implications for the organization that searches to
develop values from the data [4].
One of the most important problems related to the big data that was found out in this whole study
was that the indication of the evolution phase organizations is at, in the big data and business

analytics journey. Many industries are now present on a reaction ‘baseline analysis' phase rolling
along with the problems of the information themselves and which sometimes without responding
to these problems logically, which is in an appropriate way. This thin line of interest enforces the
punctuality and answers how relevant this paper is, with respect to the identification of the major
suggestions for developing a ability of doing analysis over business which is as an extension,
again enforced by the industrial concerns that are determined in the Delphi study that highlighted
the concerted industrial try, and is highly needed in order to respond to these challenges while
converting the big data and analysis in business values.
Where this via any medium does clear not represent the complete enlistment of the problems or a
complete guide to understand the abilities that technology of big data and data analysis has, the
mentioned paper does mentions some of the earliest superficial information to a comprehending
as well as a finite enlistment of the problems and suggestion that might surely provide a route to
the people who are trying to pursue this field of big data and analysis, around the a bracket of
fields, providing the ways of creation of the values from this technology of big data and analysis.
The theme coming out via the studies done in the course of this report has majorly reflected the
determined in the case study that indicates that the saturating process of the theories has been
done.
The whole report has largely contributed by an explanation on a theory of data as well as
business values. The studies are done and the case has identified features that may have the
ability be used to create the model of the high volume of analysis values development which
might have the ability to be directed towards the test the hypothesis. The information for this
kind of model is generally obtained from the studies done over the manager of the organizations
along with the data formation which is created by the help of the outcomes of these researches.
On the other hand, studying the analysis of a business development as a revolutionary procedure
creating on a point of view of the organization, which is created on the basis of the resources that
are provided, gives a proper method of conceptualizing the ways of an organization gain the
ability to enhance the ability of analysis and transform into a data-driven organization. At last, a
short but necessary contribution can be made to the Delphi study methods in creating a light and
less visible load way of work in prioritizing more than one item.

References
[1] Meena, S., D., and Revathi, M., 2015, Predictive Analytics on Healthcare: A Survey.
International Journal of Science and Research. 4(9). Pp. 1495-1498.
[2] Gowthami, K. and Kumar, M., R., P., 2017, Study on Business Intelligence Tools for
Enterprise Dashboard Development. International Research Journal of Engineering and
Technology. 4(4). Pp. 2987-2992.
[3] Habibi, A., Sarafrazi, A. and Izadyar, S., 2014, Delphi Technique Theoretical Framework in
Qualitative. International Journal of Engineering Science. 3(4). Pp. 8-13
[4] Ylijoki, O. and Porras, J., 2016, Conceptualizing Big Data: Analyzing Case Studies.
Intelligent Systems in Accounting Finance & Management. 23(4). Pp. 1-16