Identifying Association Rules among Drugs in Prescription of a Single Drugstore Using Apriori Method

• 作者: Ahmad Yoosofan Farshad Mahini Fatemeh Ghovanlooy Ghajar Sima Ayat Somayeh Hamidi
• 来源期刊: 智能信息管理(英文)
• 学科: 医学
• 关键词: Data Mining Association Rules PURCHASE PORTFOLIO Analysis APRIORI
• 年，卷（期）: 2015,（5）
• 页码范围: 253-259
• 页数: 7页
• 分类号: R73

摘要

These days, health care systems such as pharmacies and drugstores normally produce high volumes of data. Consequently, utilizing data mining methods in health care systems has become a conventional process. In this research, Apriori algorithm has been applied to perform data mining using the data obtained from the prescriptions ordered within a pharmacy. Ten association rules were achieved from the assigned pharmaceutical drugs in those prescriptions using the aforementioned Apriori algorithm. The accuracy of these rules is also manually studied and reviewed by a physician. Among these association rules, Vitamin D and Calcium pills are the most interrelated medications, and Omeprazole and Metronidazole rankd second in terms of association. The results of this study provide useful feedback information about associations among drugs.