Predictive Analytics in Healthcare Service Delivery

Predictive
analytics

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Table of Contents
Introduction...........................................................................................................................................2
Theories and practices that are established in the field Of Predictive Analysis.....................................2
Conclusion...........................................................................................................................................10
References...........................................................................................................................................11

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Introduction
In today’s era, predictive analytics is gaining continuous importance as the
environment is also changing rapidly. The use of predictive analytics in health care service
delivery plays an important role as it supports the doctors to take the decisions by analysing
large set of data. It helps in understanding the trend and then providing prediction regarding
the future uncertainties that might be faced by the patient. In choosing any data collection
instrument, nowadays focus is first given on the prediction. It is a difficult task to reliably
analyse the information especially in health care sector as it is directly related with the life of
a person (Ganjir, Sarkar and Kumar, 2016). In health care industry, predictive analysis
translates opinion based decisions into informed decisions. It analyse the data according to
the trends and then make assumptions so that decisions could save patients and healthcare
enterprise. It makes use of technology as well as some statistical method so that massive
information could be analysed and outcomes could be predicated. It has the potential to make
use of big data so that health of patient could be improved that too at low cost.
Theories and practices that are established in the field Of Predictive
Analysis
Predictive analytics is used for making predications for all the future events. There are
various tools that are available for making predications like statistic modelling and data
mining. Predictive analysis works on gather the information from various sources and then
analysing the data. It is used in every field from health care sector to insurance and property
management. In this report, the focus so on healthcare service delivery. Predictive analysis
plays a crucial role in understanding the information and then taking decisions. In health care
service delivery, predictive analysis is used as it offers ways through which goals could be
accomplished (Ganjir, Sarkar and Kumar, 2016). It uses various theories and models to
predict the outcome of illness. Predictive analysis sis very useful in health care department as
it undertakes are the shortcomings that can arise so that precautions could be taken
beforehand. It is beneficial as it build up new policies so that gap can be resolved.
Predictive analysis is one of the core activities in the scientific field as it hypothetically
checks the entire situation rather than just making empirical predications. In the healthcare
industry, the wide adoption of digital and mobile technologies has made important to predict

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the future consequences. Predictive analysis is important in health care sector, as it reduces
cost of treatment by predicting all the outbreaks so that diseases could be prevented. It in
general, improves the overall quality of life (Harris, May and Vargas, 2016). The
application of predictive analysis in healthcare has a positive impact as it works on saving the
life of patients. In case of healthcare, it is difficult to gather huge amount of data as it is
costly and time consuming process. Thus, improved technology that is predictive analysis is
used that improves the decision making power by making predication of all the critical
insights (Harris, May and Vargas, 2016). It predicts the critical situation before making it
too late, the predication analysis make sure that methods and treatments are adopted faster so
that patients health could be empowered (Kankanhalli, Hahn, Tan and Gao, 2016).
It is true that there is a huge need of predictive analysis in healthcare as it safes the overall
cost and assures than quality of service is offered. It predicts the health status of patients so
that staffing could be improved. It removes the possibility of risks by removing unnecessary
costs (Kankanhalli, Hahn, Tan and Gao, 2016). Prediction is a widespread application that
includes demographic, medical history along with the designing future steps that need to be
taken. Predication makes the health care facilities easy to use by integrating eth system and
improving the overall outcome.
Predictive analysis along with machine learning is one of eth most important concept in the
health care analytics (Malik, Abdallah and Ala’raj, 2016). Predictive analysis improves the
overall service delivery as it worked on all the previous care therapies so that supply chain
efficiency could be boosted. It is a useful approach especially in health care sector as
predications are converted into actions (Malik, Abdallah and Ala’raj, 2016). The predictive
modelling works on three main steps. The initial step is defining the problem that could occur
then gather the data that is necessary to design an approach. The second step is refining the
process by checking it under certain cases. The last step is assuring that this model is used in
real world practices. Predictive analysis covers evidences of the past health issue,
recommendations and the actions that need to be taken.
Predictive analytics make use of technology and some statistical ways through which
information is analysed and the outcome of patient’s health is determined. In medicine field,
predication ranges in predicting infections to determining the disease so that future wellness
is identified (Malik, Abdallah and Ala’raj, 2016). Predication modelling makes use of