In present era various public and private healthcare institutes are producing
enormous amounts of data which are difficult to handle. So, there is a need of powerful
automated Data Mining tools for analysis and interpreting the useful information from
this data. This information is very valuable for healthcare specialist to understand the
cause of diseases and for providing better and cost effective treatment to patients. Data
Mining offers novel information regarding healthcare which in turn helpful for making
administrative as well as medical decision such as estimation of medical staff, decision
regarding health insurance policy, selection of treatments, disease prediction etc., [8-
11]. Several studies identified with primary focus on various challenges and issues of
data mining in healthcare [12, 13]. Data Mining are also used for both analysis and
prediction of various diseases [14-23]. Some research work proposed an enhancement
in available Data Mining methodology in order to improve the result [24-26] and some
studies develop new methodology [27, 28] and framework for healthcare system [29-
33]. It is also found that various Data Mining techniques such as classification,
clustering and association are used by healthcare organization to increase their
capability for making decision regarding patient health. There are ample of research
resources available regarding Data Mining tasks which are presented in subsequent
sections with their advantages and disadvantages.