Clinical Schedule Management Using Similarity-Based Mining Methods

This paper proposes a temporal data mining method to maintain a clinical pathway used for schedule management of clinical care. The method consists of the following four steps: first, histories of nursing orders are extracted from hospital information system. Second, orders are classified into several groups by using clustering and multidimensional scaling method. Third, by using the information on groups, feature selection is applied to the data and important features for classification are extracted. Finally, original temporal data are split into several groups and the first step will be repeated. After the grouping results are stable, a new pathway is constructed based on the induced results. The method was applied to datasets of several diseases extracted from a hospital information system. The results show that the reuse of stored data will give a powerful tool for maintenance of clinical pathway, which can be viewed as data-oriented management of nursing schedule. The abstract goes here.