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Data Mining Applications in Healthcare. Manik Chaudhari. References. Hian Chye Koh and Gerald Tan, “ Data Mining Applications in Healthcare” : Journal of Healthcare Information Management — Vol.19 , No.2, 2011.
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Data Mining Applications in Healthcare ManikChaudhari
References • HianChyeKoh and Gerald Tan, “Data Mining Applications in Healthcare” : Journal of Healthcare Information Management — Vol.19, No.2, 2011. • Young Moon Chae, SeungHee 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 InformaticsVolume 62, Issues 2–3, July 2001, Pages 103–111 • 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 250-255 • Sandhya Joshi, HanumanthacharJoshi, “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 • 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, medicaldevices 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 [5]
Healthcare Data Mining Applications • There is vast potential for data mining applications in • healthcare. • Treatment effectiveness • Healthcare management • Customer relationship management • 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].