Data Mining Nursing Care Plans of End-of-Life Patients: A Study to Improve Healthcare Decision Making
Data Mining Nursing Care Plans of End-of-Life Patients: A Study to Improve Healthcare Decision Making
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DOI：
10.1111/j.2047-3095.2012.01217.x
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发表时间：
2013-02-01
影响因子：
1.4
通讯作者：
Wilkie, Diana J.
中科院分区：
文献类型：
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作者：
Almasalha, Fadi;Xu, Dianhui;Wilkie, Diana J.
目的：揭示隐藏的模式和知识，目前的护理信息记录与标准化护理术语临终（EOL）住院患者。方法：使用统计和数据挖掘工具对596例包括疼痛在内的患者护理计划中的问题进行检查。数据提取自Hands-On自动化护理数据系统护理计划事件数据库（n= 40747），采用NANDA-I、护理结局分类和护理干预分类（NNN）术语编码。系统事件数据（事件=住院期间每次移交患者时更新的护理计划）之前已在4个不同医疗机构的8个单位收集了2年以上的系统事件数据（总事件=40,747次；EOL事件=1,425次），并在此分析之前进行了匿名化处理。结果：结果显示了多项发现，包括EOL患者的住院时间(
PURPOSE: To reveal hidden patterns and knowledge present in nursing care information documented with standardized nursing terminologies on end-of-life (EOL) hospitalized patients. METHOD: 596 episodes of care that included pain as a problem on a patient's care plan were examined using statistical and data mining tools. The data were extracted from the Hands-On Automated Nursing Data System database of nursing care plan episodes (n=40,747) coded with NANDA-I, Nursing Outcomes Classification, and Nursing Intervention Classification (NNN) terminologies. System episode data (episode=care plans updated at every hand-off on a patient while staying on a hospital unit) had been previously gathered in eight units located in four different healthcare facilities (total episodes=40,747; EOL episodes=1,425) over 2 years and anonymized prior to this analyses. RESULTS: Results show multiple discoveries, including EOL patients with hospital stays (