TITLE:
Identifying Association Rules among Drugs in Prescription of a Single Drugstore Using Apriori Method
AUTHORS:
Ahmad Yoosofan, Fatemeh Ghovanlooy Ghajar, Sima Ayat, Somayeh Hamidi, Farshad Mahini
KEYWORDS:
Data Mining, Association Rules, Purchase Portfolio Analysis, Apriori
JOURNAL NAME:
Intelligent Information Management,
Vol.7 No.5,
September
16,
2015
ABSTRACT: 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.