Improving Clinical Path Management Strategies by Constructive Induction

Digitalization of data has provided self understandable aspect of collect, store and retrieve large amounts of documents in databases, data repositories and data warehouses. Discovery of knowledge hidden in these databases can provide organizations with insight into there own internal intellectual assets. However, how to interpret meaningful information from this data remains one of the important challenges. This paper emphasizes importance of the preprocess part of KDD in such large data repositories. A health care organization study is used as an illustrative example where the KDD methods of C5.0 and CART are used. With careful analysis on large data, such as the use of proper feature sets, appropriate sampling sets, important meaningful information as insight into clinical pathways are discovered.