Clustering-based analysis in hospital information systems

Rapid progress in electronization of hospital information gives an opportunity to realize evidence-based hospital management and services. This paper proposes a clustering-based data mining approach to temporal data in hospital information. The process consists of repetitions of clustering for grouping records and decision tree inducion for feature selection. It will terminate if the clustering results are converged. We evaluated this method to data on order history stored in hospital information system. The results show that the reuse of stored data will give a powerful tool for hospital management and lead to improvement of hospital services.