This paper proposes a method for construction of a clinical pathway based on attribute and
sample clustering, called dual clustering. The method consists of the following four steps: first, histories
of nursing orders are extracted from a hospital information system. Second, orders are classified
into several groups by using clustering on the pricipal components (sample clustering). Third, attribute
clustering is applied to the data. Finally, original temporal data are split into several sub-tables and the
first step will be repeated in a recursive way. After the grouping results become stable, a new pathway will be constructed
from all the induced results. The method was applied to datasets of a disease extracted from a hospital information system.
The results show that the proposed method constructed a clinical pathway, which was not only similar to the pathway
manually acquired from medical experts but also discovered nursing orders which they forget to include.
Keywords: Clinical pathway, decision support, dual clustering, temporal data mining, hospital information system.
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