隨著近年來人口老化以及文明病的氾濫造成需仰賴長期照護的個案增加，病
人的用藥安全問題議題越來越重要。在中西醫對立的醫療模式制約下造成病人中
西藥未經專業醫師的調配下濫用，如何結合中醫與西醫雙方的優點達到溫和且具
療效又不造成病人的身體上負擔的治療成為重要課題。然而，近代醫學的趨勢強
調實證醫學，且受到傳統觀念以及疾病治癒的風險影響，過去少有研究針對中西
醫併用的資料進行分析與探討，因此缺乏案例與實證造成後續臨床處方上的使用
性不足。本研究以紫式決策分析架構為基礎，發展中西藥併用決策模型，利用資
料探勘(Data Mining)方法針對病患的疾病、治療時間、用藥方式去探討之間和腎
絲球過濾率(Glomerular Filtration Rate，GFR)變化的關聯規則，再從個案中分析
出最適合人體的中西藥併用組合，以利醫師開立處方時能有參考依據，提供病患
有利且副作用低的治療方法，增加臨床處方上中西藥併用的使用性，改變未來的
醫療模式。
With the ageing population and the spread of civilized diseases in recent years, the
number of cases requiring long-term care has increased, and the issue of patient safety
is becoming more and more important. Under the restriction of the medical model of
Chinese and Western medicine, the patient's Chinese and Western medicines are abused
without the deployment of professional doctors. How to combine the advantages of
both Chinese medicine and Western medicine to achieve mild and curative treatment
without causing the patient's physical burden becomes an important issue. However,
the trend of modern medicine emphasizes empirical medicine, and it is influenced by
the traditional concept and the risk of cure of the disease. In the past, few studies have
analyzed and discussed the data used in combination with Chinese and Western
medicine. Therefore, the lack of case and evidence has led to insufficient use of followup
clinical prescriptions. . Based on the purple decision-making analysis framework,
this study develops a decision-making model for the use of Chinese and Western
medicines, using data mining methods to explore the disease, treatment time, and
medication patterns of patients and the spheroid filtration rate (Glomerular Filtration).
Rate, GFR) change the association rules, and then analyze the most suitable
combination of Chinese and Western medicines in the case, so that the doctor can have
a reference when opening a prescription, provide treatments with low and low side
effects, and increase clinical prescriptions. The usability of the combination of Chinese
and Western medicines will change the future medical model.
