RAJIV GANDHI UNIVERSITY OF HEALTH SCIENCE,

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1


RAJIV GANDHI UNIVERSITY OF HEALTH SCIENCE,

BANGALORE, KARN
A
TAKA.



APLLICATION FOR APPROVAL OF PROJECT PROPOSAL



1

Name of the Candidate & A
d
dress

SANTOSH


J

KANCHYANI

PADMASHREE

COLLEGE
OF HOSPITAL
ADMINISTR
A
TION

#23, ABOVE SBI BANK,

NAGARBHAVI CIRC
LE,

BANGALORE
-

560072.

2

Name of the Institution

PADMASHREE COLLEGE
OF
HOSPITAL
ADMINISTR
A
TION

3

Course of study and subject

MASTER OF HOSPITAL

A
D
MINISTRATION

4

Date of admission to course

06
-
09
-
20
10

5


TITLE OF THE TOPIC:
-

“TO ASSESS THE NEED
FOR


INTRODUCING


A

DATA


MINING

DEPARTMENT


IN

A S
E
LECTED

HOSPITAL
.


2


6.

DEFINITION
AND SCOPE OF THE STUDY:



The healthcare environment is generally perceived as being 'information rich' yet
'knowledge poor'. There is a wealth of data available with
in the healthcare systems.
Howe
v
er, there is a lack of effective analysis tools to discover hidden relationships and
trends in data. Knowledge discovery and data mining have found numerous
applications in business and scientific domain. Valuable knowledge
can be discovered
from application of data mi
n
ing techniques in healthcare system.



There are wide range of users affected by emerging technologies in health care and
a wide range of services these technologies can offer. On the side of health care
pr
ofessionals, healthcare organizations worldwide are currently undertaking massive
transformations and additions to their IT infrastructure. Health care professionals use
health technologies to comply with changing regulations, improve patient care, and
pro
vide improved support for office staff, clinicians, and patients.



In health care, there is massive data, and this data has no organizational value until
co
n
verted into information and knowledge, which can help control costs, increase
profits, and m
aintain high quality of patient care.



There is a tremendous opportunity for data mining methods to assist the physician
deal with this flood of patient information and scientific knowledge. Data mining and
m
a
chine learning can potentially he
lp all physicians in a variety of ways, by helping
interpret complex diagnostic tests, by combining information from multiple sources
(images, clinical data, proteomics, scientific knowledge), by providing support for
differential diagnosis, by suggesting
treatments and providing patient
-
specific
prognosis.


Another relevant trend that will increasingly dominate medicine in the next
decades is
the

push towards “evidence
-
based” medicine (based largely upon the results
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-
ba獥d
medicine (based upon the individual physician’s knowledge and experiences). Due to
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3




Future Directions



Data mining applications in healthcare can have tremendous potential and
usefulness. However, the success of healthcare data m
ining hinges on the availability
of clean healt
h
care data. In this respect, it is critical that the healthcare industry
consider how data can be better
captured,

stored, prepared, and mined. Possible
directions include the

standardization of clinical vocab
ulary and the sharing of data
across organizations to e
n
hance the benefits of healthcare data mining applications
.Further, as healthcare data are not limited to just quantitative data, such as physicians’
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7.

OBJECTIVE OF STUDY:

1.

To assess the opinion of the consultant and staff on the need and importance of
data mining in a hospital.


2.

To assess requirement of such a department.

8.

RESEARCH

M
ETHODOLOGY
:





This is descriptive study.

Primary

data will be collected by distributing structured
questionnaire among physicians and staff.


4



9.


R
EVIEW OF LITERATURE:



Data Mining for Healthcare Management (DMHM) has been instrumenta
l in
detecting patterns of diagnosis, decisions and treatments in healthcare. Data mining has
aided in several aspects of healthcare management including disease diagnosis,
dec
i
sion
-
making for treatments, medical fraud prevention and detection, fault detec
tion
of medical devices, healthcare quality improvement strategies. Data mining was
initially a su
c
cess in the healthcare industry as it was used to detect fraudulent claims
processing. However, since then large collections of transactional data and also d
ata
due to mergers and acquisitions has provided businesses enough opportunities to
analyze and extract informative hidden patterns to reduce costs.
1





Johnson

has suggested that, at a higher level, data mining can facilitate
comparisons acros
s healt
h
care groups of things such as practice patterns, resource
utilization, length of stay, and costs of
different hospitals. Recently
Sierra Health
Services has used data mining extensively to identify areas for quality i
m
provements,
including treatmen
t guidelines, disease management groups, and cost management.




There is vast potential for data mining applications in healthcare.


1.
Healthcare management
.
To aid healthcare management, data mining
applications can be developed
to better identify and track chronic disease states and
high
-
risk patients, design appropriate interve
n
tions, and reduce the number of hospital
admissions and claims.



2.
Customer relationship management.

While customer relationship
management i
s a core a
p
proach in managing interactions between commercial
organizations typically banks and retailers and their custo
m
ers, it is no less important in
a h e a l t h c a r e c o n t e x t. C u s t o m e r i n t e r a c t i o n m a y o c c u r t h r o u g h c a l l c e n t r e, p h y s i c i a n s ’
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d e 灡 r
t
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3
.

T r e a t m e n t e f f e c t i v e n e s s
.

Data mining applications can be developed to evaluate
the effectiveness of medical treatments. By comparing and contrasting causes,
symptom, and

courses of

treatments, data mining can deliver an
analysis of

which
cou
rses of action prove effective.

For example, the outcomes of patient groups treated
with different drug regimens for the same disease or condition can be compared to
5


determine which
treatments

work

best and are most cost
-
effective.


4.
Fraud and abuse.

D a t a m i n i n g a p p l i c a t i o n s t h a t a t t e m p t t o d e t e c t f r a u d a n d
a b u s e o f t e n e s t a b l i s h n o r m s a n d t h e n i d e n t i f y u n u s u a l o r a b n o r m a l p a t t e r n s o f c l a i m s
b y
p h y s i c i a n s,

l a b o r a t o r i e s, c l i n i c s, o r o t h
e r s. Among other things, these applications
can highlight inappropriate prescription or referrals and fraud
u
lent insurance and
medical claims. For example, the Utah Bureau of Medicaid Fraud has mine the mass of
data generated
by millions of prescriptions,

operations and treatment courses to identify
u
n
usual patterns and uncover fraud.
2





Da t a mi n i n g a s a p r o c e s s f o r a n a l y z i n g d a t a f r o m d i f f e r e n t p e r s p e c t i v e s a n d
s u mma r i z i n g i t i n t o u s e f u l i n f o r ma t i o n c a n g e n e r a t e i n f o r ma t i o n t h a t c a n b e u s e d t o
i
n
c r e a s e

r e v e n u e, c u t c o s t s, o r
b o t h.
Da t a mi n i n g i d e n t i f i e s t r e n d s wi t h i n d a t a t h a t g o
b e y o n d s i mp l e a n a l y s i s. T h r o u g h t h e u s e o f s o p h i s t i c a t e d a l g
o
r i t h ms, n o n
-
s t a t i s t i c i a n
u s e r s h a v e t h e a b i l i t y t o i d e n t i f y k e y a t t r i b u t e s o f b u s i n e s s p r o c e s s e s a n d t a r g e t
o p p o
r
t u n i t i e s.
Dat a mi ni ng r ef er s t o ext r act i ng or “mi ni ng” knowl ed
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3







Th e r e s e a r c h f o u n d a gr o wi n g n u mb e r o f d a t a mi n i n g a ppli c a t i o n s, i n c lu d i n g
a n a ly s i s o f h e a lt h c a r e c e n t e r s f o r b e t t e r h e a lt h po li c y
-
ma ki n g, d e t e
c t i o n o f d i s e a s e
o u
t
b r e a ks a n d pr e ve n t a b le h o s pi t a l d e a t h s, a n d d e t e c t i o n o f f r a u d u le n t i n s u r a n c e
c la i ms.
4





Da t a mi n i n g i n h e a l t h c a r e ma n a g e me n t i s u n l i k e t h e o t h e r f i e l d s o wi n g t o t h e f a c t
t h a t t h e d a t a p r e s e n t a r e h e t e r o g e n e o u s a n d t h a t c e r t a i
n e t h i c a l, l e g a l, a n d s o c i a l
co
n
straints apply to private medical information. Health care related data are
voluminous in nature and they arrive from diverse sources all of them not entirely
appropriate in structure or quality. These days, the exploitation

of knowledge and
experience of n
u
merous specialists and clinical screening data of patients gathered in a
database during the diagnosis procedure, has
been widely recognized
.
5


6





Application of data mining methods can help physicians and health man
agement
organizations to monitor efficiently the utilization of drugs by chronic patients.
Aut
o
mated identification of patients at risk of suboptimal treatment or over utilization
can help a physician in better controlling such patients
.
6






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a瑡

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7





10



LIST OF REFERENCES

1.


http://w
wwusers.cs.umn.edu/~desikan/pakdd2011/tutorial/dmhm2011.html

(
accessed on 01/06/2011
)
.

2.

H
ian Chye Koh and Gerald Tan
,

䑡ta

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ⰠI

g潵牮o氠潦o䡥a汴档are fn景
r
m
a瑩潮o䵡湡geme湴n


噯氮s ㄹⰠ
乯⸠㈬O灰pSS
-
㘸S

E
桴h瀺p⽷睷⹳汩摥獨sr
e⹮e琯呯浭y㤶⽤慴9
-
浩湩ng
-
a灰汩ca瑩潮o
-

-
桥a汴档a牥

acce獳敤渠〱⼰㘯㈰ㄱ⸠

7


3.

Olugbenga Oluwagbemi , Uzoamaka Ofoezie, Nwinyi,Obinna, “ A Knowledge
-
Ba獥搠䑡瑡t䵩湩ng py獴e洠景f 䑩ag湯獩ng 䵡污r楡ioe污瑥搠Ca獥猠楮i䡥a汴档are
Management”,
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e爠pc楥湣e g潵
r
湡氬l噯
氮l㌴3

I
乯k㐠
I
䵡y

㈰㄰
K

E
e灲楮瑳⹣潶pna湴畮n癥牳rty⹥摵⹮g⼴㘯ㄯN
-
彇桥n条_
-
彡浡欮摯c

acce獳s搠 潮
〱⼰㘯㈰ㄱO




Nai
-
Wen Kuo,


In景f浡m楯渠呥c桮潬潧y 䅰灬楣a瑩潮猠景f 䝥物r瑲楣 C潮獵o瑡瑩潮t
Se牶楣e 楮 呡楷in

I

I
n
ternational Journal of
Advancements in Computing
Technology
, Volume
3, Number 1, February 2011
, pp
-
49
.

(
www.aicit.org/ijact/ppl/05
-
IJACT2
-
279039IP.pdf
-

United States
)

accessed on
01/06/2011.



5.
Rajkumar.
Asha
,

Sophia Reena

G
,
“Diagnosis

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䑡瑡

††


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楮i湧

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o
rithm” ,

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p畴敲⁓c楥湣e a湤⁔nc桮潬潧yI

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-

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䑩獥a獥
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-
䅬g潲楴桭⹰摦h

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獳敤

潮‰㈯〶O㈰ㄱ


†††


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K

o⹓⸠
, “
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I

6th International Advanced Technologies Symposium (IATS’11),


-
ㄸ 䵡y
2011, Elazığ, Turkey


-
ㄲN

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⸠K
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8


11

SIGNATURE OF CANDIDATE


:


1
2

REMARKS OF PROJECT
SUPERVISOR

:


13

NAME AND DESIGNATION OF


:

13.
SUPERVISOR :


MS. RESHMA LOBO
,

MHA










PRINCIPAL











PADMASHREE COLLEGE OF







HOSPITAL ADMINISTRATION










BANGALORE.


13.2

SIGNATURE

:

13.3


CO
-
SUPERVISOR

(if any)

:

13.4

SIGNATURE

:

14




14.1
NAME OF THE PRINCIPAL

:

MS. RESHMA LOBO
,

MHA








PRINCIPAL








PADMASHREE COLLEGE OF






HOSPITAL ADMINISTRATION









BANGALORE.

14.2

REMARKS OF THE PRINCIPAL

:



14.3 SIGNATURE

:


9