An Automated Technique for Identifying Associations Between Traditional Chinese Medicine (TCM) and Disease: An Application of Taiwanese National Health Insurance Research Database.

• Main Authors: Shen-Hsien Lin, 林昇憲
• Other Authors: Yu-Chuan Li
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/befcvu

碩士 === 臺北醫學大學 === 醫學資訊研究所 === 102 === In recent years, the utilization rate of alternative and complementary medicine in the world is rising, and Chinese traditional medicine is one of alternative and complementary medicine. According to statistics of the Ministry of Health and Welfare in Taiwan, about 25 % of the population had to treat diseases through Chinese traditional medicine, so we should need to pay much attention to patient safety and quality of care of Chinese traditional medicine. In Taiwan, Traditional Chinese medicine use the International Classification of Diseases, Ninth Revision (ICD-9-CM) as the code of disease diagnosis. Western medicine is also using the same way,and this is the world''s first case. In other countries, Traditional Chinese medicine diagnosis is to use text description. By comparison, using this way to record is more easy to organize and analyze data. The sample database in this study was using the millions of people file of the National Health Insurance Research Database is recorded from 2000 to 2011,and the Taipei Medical University Hospitals of Chinese medicine outpatient database is recorded from 2007 to 2011. Using thess database established the knowledge base of association of disease - Scientific Chinese Medication and Scientific Chinese Medication - Medication. The research method consists of three steps, the first use of data mining association rules to find out the various combinations of disease-Scientific Chinese Medication, and Scientific Chinese Medication- Medication.And to quantify the strength of association to establish a knowledge base in disease-Scientific Chinese Medication, and Scientific Chinese Medication- Medication, then use in the same way to a hospital outpatient of traditional Chinese medicine database to establish another knowledge base. Then, using Pearson correlation coefficients analysis these two knowledge base. Finally, through a sensitivity analysis to find out cut-off value(Q) for detection of inappropriate prescription. The study sample source for millions people of NHIRD, This sample is a national sample, not only representative is also available for reference and use of medical institutions nationwide. Therefore, the expected results of this study for the establishment of an advantage, and can be applied to any one hospital spread of knowledge, through sensitivity analysis to identify the appropriate cut-off value to improve the sensitivity of detection of inappropriate prescribing. In the future, expecting this knowledge base can be integrated in Chinese medicine outpatient physician order systems, to reduce medication errors, and improve quality of care medicine.