护理常规数据作为护理知识领域关联分析的基础。

Björn Sellemann, Jürgen Stausberg, Ursula Hübner
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摘要

本文描述了在数据库知识发现(KDD)框架下的关联分析数据挖掘方法,旨在识别护理的标准模式。该方法以应用为导向,应用于LEP护理2方法的护理常规数据。医院越来越多地使用信息技术,特别是护理信息系统,需要存储大量数据集,迄今为止,这些数据集并不总是得到充分的分析。对入院、手术和出院的天数进行了三次关联分析。生成的近150万条关联规则的结果表明,将关联分析应用于护理常规数据是有效的。所有规则在语义上都是微不足道的,因为它们反映了护理领域的现有知识。这可能是由于LEP护理2的方法,或护理活动本身。尽管如此,关联分析可能在未来成为一种有用的基于结构化护理常规数据的分析工具。
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Nursing routine data as a basis for association analysis in the domain of nursing knowledge.

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.

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