A ”Ubiquitous Environment” through Wireless Voice/Data Communication and a Fully Computerized Hospital Information System in a University Hospital

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing

et al. 2012

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This paper proposes an exploratory temporal data mining process which aims at capturing behavior of medical staff. The process consists of the following four process. First, datasets will be extracted from hospital information systems through double-step datawarehousing. Second, similarities between temporal sequences are calculated from datasets. Third, data mining methods such as clustering, multidimensional scaling are applied for obtaining the class labels. Finally, other data mining methods, such as decision tree and correspondence analysis are applied to original data sets with the class labels.

Section: A Hospital Information System: Cyberspace In Hospitalmentioning

confidence: 99%

Exploratory temporal data mining process in hospital information systems

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing

et al. 2012

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“…Dealing with cyberspace in a hospital will give a new challenging problem in hospital management in which spatiotemporal data mining, social network analysis and other new data mining methods may play central roles. 1 …”

Section: Introductionmentioning

confidence: 97%

Temporal data mining of order entry histories for characterization of medical practice

2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)

2012

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Since hospital data include temporal trends of clinical symptoms and medical services, we can discover not only knowledge about temporal evolution of disease, but also one about medical practice from hospital information system. This paper proposes temporal data mining process and applied the method to capture temporal knowledge about nursing practice. The results show that the reuse of stored data will give a powerful tool for management of nursing schedule and lead to improvement of hospital services.

“…HIS stores all the histories of clinical activities in a hospital, such as electronic patient records, laboratory data, x-ray photos, and so on. The advantage of HIS is that all the data are input through the network service and they can retrieve from the terminals inside the hospital [4,3].…”

Section: Introductionmentioning

confidence: 99%

Mining Schedule of Nursing Care Based on Dual-Clustering

Procedia Computer Science

2015

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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 hospital information system. Second, orders are classified into several groups by using clustering on the pricipal components (sample clustering). Third, attributes 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 are 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.