Construction of Clinical Pathway based on Similarity-based Mining in Hospital Information System

This paper proposes construction of clinical care plan conducted by nurses by using data mining methods. The key idea is to summarize the history of nursing orders into numerical temporal sequences with admission dates, which is the best temporal granularity for thsis analysis. After extracting numerical temporal sequences on frequencies of nursing care, similarity-based methods, such as clustering and multidimensional scaling (MDS) are applied to the data and the labels for grouping are obtained. By using the labels, rule induction is applied, and classification power of each date is estimated. The admission dates are sorted by an index of classification power, the original dataset is decomposed into subtables. Clustering, rule induction and table decomposition methods are applied to the subtables in a recursive way. The method was applied to datasets stored in hospital information system stored in 10 years. The results show that the reuse of stored data will give a powerful tool for construction of clinical process, which can be viewed as data-oriented management of nursing schedule