Data Mining in Military Health Systems - Clinical and Administrative Applications1 1 This material is based upon work partially supported by the United States Army Military Health Data Mining Library (MHDML) project (contract number DAMD17-02-C-0071). The MHDML project has developed a research data cube and the advanced data mining methods serving as knowledge analysis templates for medical knowledge discovery demonstrated in this study. This material is also partially supported by the United States Army Blood Reserve Availability Assessment, Tracking, and Management System (BRAMS) project (contract number W81XWH-05-C-0074). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Army.
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This paper describes two applications that illustrate the role of data mining technology in excavating actionable knowledge from healthcare systems data repositories. Across the health care industry, a wide variety of medical data is being generated at a staggering rate. The widespread adoption of information technology in the civilian (and military) healthcare industries has resulted in notable increase in quality of care and process efficiencies, however, a higher level of return on these data investments can be realized. Current information technologies do not address the larger knowledge extraction potential. Data mining can leverage the vast quantities of data that is captured for treatment, payment or operations purposes and extract from it key clinical and administrative directed insights. Accessing this currently unrealized knowledge potential would enable the delivery of actionable knowledge to medical practitioners, healthcare system managers, policy planners and even patients to make a significant difference in overall healthcare. 2007 IEEE.
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2007 IEEE International Conference on Automation Science and Engineering
