This paper describes the data mining method of association analysis within the framework of Knowledge Discovery in Databases (KDD) with the aim to identify standard patterns of nursing care. The approach is application-oriented and used on nursing routine data of the method LEP nursing 2. The increasing use of information technology in hospitals, especially of nursing information systems, requires the storage of large data sets, which hitherto have not always been analyzed adequately. Three association analyses for the days of admission, surgery and discharge, have been performed. The results of almost 1.5 million generated association rules indicate that it is valid to apply association analysis to nursing routine data. All rules are semantically trivial, since they reflect existing knowledge from the domain of nursing. This may be due either to the method LEP Nursing 2, or to the nursing activities themselves. Nonetheless, association analysis may in future become a useful analytical tool on the basis of structured nursing routine data.
['Björn Sellemann', 'Jürgen Stausberg', 'Ursula Hübner']
Nursing routine data as a basis for association analysis in the domain of nursing knowledge.