A drug association based inventory control system for ambulatory care. Issue 6 (18th August 2019)

• Record Type: Journal Article
• Authors: Shiau, Jiun-Yan
• Is Part Of: Journal of information & optimization sciences. Volume 40:Issue 6(2019)
• Page Start: 1351
• Page End: 1365
• Publication Date: 2019-08-18
• Subjects: 90B05 -- 68T99; Drug inventory control -- Basket analysis -- Association rules -- Data mining; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2019.1649032
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: The purpose of the research is to explore an innovated drug inventory control system for medical organization to improve the system performance in terms of daily patients' prescriptions and drugs flows. It is not easy to well control drugs inventory due to large numbers of stock keeping units and huge quantities of them in a medical organization. In order to maintain both the daily jobs of ambulatory care and the rights of the patients, the availability of all drugs keeping at a reasonable stock level for medical staffs and patients is required. Also, to avoid increase of cost due to over stocking to overcome the prediction of possible shortage of drugs is a must. In traditional control system, cost is always be considered as the decision variable. Based on the total cost of each item in an inventory management within a planning cycle, and to calculate out the quantity for that particular item within the total inventory, the total amount of inventory ratio for that item will also be derived and be classified to make different inventory management strategies for different catalogues. There are hundreds of variable pharmaceutical goods in medical organization, hence, large number of prescription data and critical information will be ignored if the inventory classification is determined by the traditional cost approach. This study used association rules analysis to mining the patient treatments database, in order to derive prescription-oriented association rules for improving cost-oriented categories inventory management. In this research, data mining technology is utilized to detect hiddenly issues, which might cause drug shortages. Around 480, 000 data, ranges from January to March, 2010, were extracted from Taiwan's National Health Insurance files, and applied with multi-level association rule analysis, 19 association rules were obtained. In conclusion, the potential relationship in a huge database, found by data mining technique, can be used to support managing staff to adjust inventory policies accordingly.