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Manik Chaudhari
REFERENCES
1. Hian Chye Koh and Gerald Tan, “Data Mining Applications in Healthcare” :
Journal of Healthcare Information Management — Vol.19, No.2, 2011.
2. Young Moon Chae, Seung Hee Ho, Kyoung Won Cho, Dong Ha Lee b, Sun Ha Ji,
“Data mining approach to policy analysis in a health insurance domain” :
International Journal of Medical Informatics Volume 62, Issues 2–3, July 2001,
Pages 103–111
3. K.Srinivas, B.Kavihta Rani, Dr. A.Govrdhan , “ Applications of Data Mining
Techniques in Healthcare and Prediction of Heart Attacks” : (IJCSE) International
Journal on Computer Science and Engineering , Vol. 02, No. 02, 2010, Pages 250255
4. Sandhya Joshi, Hanumanthachar Joshi, “Applications of data mining in health
and pharmaceutical industry” : International Journal of Scientific & Engineering
Research, Volume 4, Issue 4, April-2013 915 , ISSN 2229-5518
5. Mary K. Obenshain , MAT, “Application of Data Mining Techniques to Healthcare
Data” : Infection Control and Hospital Epidemiology, Vol. 25, No. 8, August 2004
DATA MINING AND HEALTHCARE
• Healthcare industry today generates large amounts of
complex data about patients, hospitals resources, disease
diagnoses, electronic patient records, medical devices
etc.
• The large amounts of data is a key resource to be
processed and analyzed for knowledge extraction that
enables support for cost-savings and decision making.
• Data mining
- provide healthcare professionals an additional
source of
knowledge for making decisions
• The decisions rests with health care professionals.
DATA MINING STRATEGIES
Figure : Data mining techniques
HEALTHCARE DATA MINING
APPLICATIONS
There is vast potential for data mining applications in
healthcare.
1. Treatment effectiveness
2. Healthcare management
3. Customer relationship management
4. Fraud and abuse
1. TREATMENT EFFECTIVENESS
• “United Healthcare has mined its treatment record data to
explore ways to cut costs and deliver better medicine”[1] .
• “In 1999, Florida Hospital has launched the clinical best practices
initiative with the goal of developing a standard path of care
across all campuses, clinicians and patient admissions”[1].
2. HEALTHCARE MANAGEMENT
• “In Seton Medical Center, for maintaining and improving
the quality of healthcare , data mining is used to
decrease length of stay, avoid clinical complications,
develop best practices, improve patient outcomes and
provide information to physicians”[1].
• “Blue cross also use data mining applications to improve
outcomes and reduce expenditures through better
disease management”[1].
• “Data mining is also used for hospital infection control or
an automated early- warning system. Global spread of
SARS virus is an example of early warning system”[1].
3. CUSTOMER RELATIONSHIP
MANAGEMENT
• “The identification of usage and purchase patterns and the
eventual satisfaction can be used to improve overall customer
satisfaction”[1].
• “Customer Potential Management Corp. has developed a
Consumer Healthcare Utilization Index, based on millions of
healthcare transaction of million patient” [1].
- “OSF Saint Joseph Medical Center uses this Index to get
right
message and services to the most appropriate
patients at
strategic times and as a result more
effective and efficient
communication and
increased revenue”.
• CRM help to promote disease education, prevention and
wellness services.
4. FRAUD AND ABUSE
• “Utah Bureau of Medicaid Fraud has mined the mass of data
generated by millions of prescriptions, operations and
treatment courses to identify unusual patterns and uncover
fraud”[1].
• “ReliaStar Financial Corp. has reported a 20 percent
increase in annual savings, Wisconsin Physician’s Service
Insurance Corporation has noted significant savings,3 and
the Australian Health Insurance Commission has estimated
tens of millions of dollars of annual savings”[1].
• “Texas Medicaid Fraud and Abuse Detection System, which
recovered $2.2 million and identified 1,400 suspects for
investigation in 1998 after operating for less than a year”[1].