Extracting drug utilization knowledge using self-organizing map and rough set theory

Authors:
Hsin-Chuan Chou;Ching-Hsue Cheng;Jing-Rong Chang
Affiliations:
Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Touliu, Yunlin 640, Taiwan;Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Touliu, Yunlin 640, Taiwan;Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Touliu, Yunlin 640, Taiwan and Graduate School of Management, National ...
Venue:
Expert Systems with Applications: An International Journal
Year:
2007

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Abstract

Cardiovascular disease is becoming the major cause of death in many industrialized countries. People who receive long-term treatments usually ignore the progress of the disease states. Therefore, it is critical and necessary to evaluate drug utilization and laboratory test in order to discover the knowledge that is beneath and can be extracted from those raw data. This paper utilizes techniques of self-organizing map (SOM) and rough set theory (RST) to discover the trend of individual patient's condition. With 10-fold cross-verification, the proposed SOM-SOM-RST process successfully and effectively detects patients whose diagnosis codes have been changed during the period of investigation and attains an accuracy of approximate 98%. This method can remind physicians to reevaluate the disease conditions of their patients.