标准化护理计划数据挖掘与分析框架
Framework for Mining and Analysis of Standardized Nursing Care Plan Data.
作者信息
Khokhar Ashfaq, Lodhi Muhammad Kamran, Yao Yingwei, Ansari Rashid, Keenan Gail, Wilkie Diana J
机构信息
1 Illinois Institute of Technology, Chicago, IL, USA.
2 University of Illinois, Chicago, IL, USA.
出版信息
West J Nurs Res. 2017 Jan;39(1):20-41. doi: 10.1177/0193945916672828. Epub 2016 Oct 22.
Despite an unprecedented amount of health-related data being amassed from various technological innovations, our ability to process this data and extract hidden knowledge has yet to catch up with this explosive growth. Although nursing care plans can be an effective tool to support the achievement of desired patient outcomes, their online collection, storage, and processing is lagging far behind. As a result, the impact of nursing care is not well understood from qualitative as well as quantitative perspectives. In this article, we first outline a complete life cycle of nursing care data, and present a knowledge discovery and analysis framework for such data sets. We also highlight Big Data issues pertaining to the analysis of nursing care data. Using an exemplar data set, we demonstrate the broad applicability of the proposed framework by showing knowledge discovery results for different outcomes related to patients, nursing staff, and administrators.
尽管通过各种技术创新积累了前所未有的大量健康相关数据，但我们处理这些数据并提取隐藏知识的能力尚未跟上这种爆炸式增长。虽然护理计划可以成为支持实现预期患者治疗效果的有效工具，但其在线收集、存储和处理却远远滞后。因此，从定性和定量角度来看，护理的影响都没有得到很好的理解。在本文中，我们首先概述护理数据的完整生命周期，并提出针对此类数据集的知识发现与分析框架。我们还强调了与护理数据分析相关的大数据问题。通过一个示例数据集，我们展示了与患者、护理人员和管理人员相关的不同结果的知识发现结果，从而证明了所提出框架的广泛适用性。
Zotero 插件