Clustering of Timed Sequences for Analyzing Care Pathways

The core message of this article is to propose a method for clustering timed sequences, which can be applied to analyze care pathways from electronic health records. The method adapts the drop-DTW metric and the DBA algorithm for averaging timed sequences, enabling the discovery of typical care pathways.