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].