Medical Material Management Support Using Data Mining and Analytics

We present the application of data mining and analytics to support medical material management. Medical materials considered include medical equipment, drugs and pharmaceuticals, and blood. This paper presents the work performed in two different Office of Secretary of Defense (OSD) funded projects – (i) Medical Material Knowledge Discoverer (MMKD), covering medical equipment, pharmaceuticals and item management; and (ii) Blood Reserve Availability Assessment, Tracking, and Management System (BRAMS), covering blood supply chain management. Data mining and analytics are used to analyze inventory and consumption patterns, evaluate supply chain status, identify and determine key performance metrics at different levels of hierarchy, detect potential problems and issues and identify opportunities for improvement. The paper presents the application of clustering, association rules, regression analyses, online analytical processing (OLAP), performance metrics, data validation, alerts and notifications, a Geographic Information System (GIS), and analyses at multiple levels of abstraction to facilitate the efficient management of supply chains. Due to the sensitive nature of the data, the paper does not present data mining results per se, and data and analyses results are obscured when necessary. Instead, the focus of the paper is on how data mining and analytics are used to support supply chain management.