Integration of NNN into EHRS: how are we doing?: IJNK virtual issue.
Integration of NNN into EHRS: how are we doing?: IJNK virtual issue.
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将 NNN 集成到 EHRS：我们做得怎么样？：IJNK 虚拟问题。
DOI：
10.1111/2047-3095.12039
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发表时间：
2014
影响因子：
1.4
通讯作者：
Wilkie,DianaJ
中科院分区：
文献类型：
--
作者：
Keenan,GailM;Wilkie,DianaJ
IJNK的这个特别版包括过去20年中发表的六篇文章，这些文章提供了将一个或多个标准化术语NANDA-I，NOC，NIC（NNN）整合到电子健康记录（EHR）中的努力。选择是故意的，并展示了护理的长期EHR目标的实现所取得的进展：通过分析EHR中收集的可互操作护理数据来展示护理对患者结局的影响。前四篇文章写于1993年至2000年，提供了初步步骤和战略的一瞥。最后两篇分别于2009年和2012年发表，表明了与早期战略的重大转变，并提供了在EHR中完全集成和使用NNN的例子。Harvey（1993）报道了一项成功的试点研究，其中神经网络（艺术-2神经网络）被应用到识别模式的定义特征，帮助正确选择五个相关的护理诊断。包含一致标记的定义特征的书面问卷被用来收集数据，而不是实际的文档或EHR数据。在第二个研究中，Coenen等人（1995）使用来自一家公立医院的护理信息系统（NIS）的数据，确定了六种护理诊断的护理干预流行率。所提取的数据包括NANDA诊断标签和当地开发的相关因素和护理干预的标签。Moorhead和Delaney（1997）的第三项研究重点描述和应用了他们开发的一套规则，用于使用一家医院的临床数据将非标准化护理干预手动映射到护理干预分类术语中的标准化术语。在第四项研究中，Delaney et al（2000）检查了30例患者的电子文档，以评估指定NANDA诊断（身体活动受损）的患者的定义特征和相关因素的特定子集的频率。总的来说，这四项研究提供了初步的证据，潜在的可行性和实用性，将NANDA和NIC纳入EHR。然而，还需要进一步的研究来验证这些小型便利样本中发现的结果的普遍性。此外，还需要考虑的是如何将NNN整合到EHR中，以产生标准化数据，用于检查护理对患者结局的影响。
This special edition of IJNK, includes six articles published in the last 20 years that provide a snap shot of efforts to integrate one or more of the standardized terminologies, NANDA-I, NOC, NIC (NNN), into electronic health records (EHRs). The selection was intentional and demonstrates the progress made toward the achievement of nursing’s long term EHR goal: To demonstrate the impact of nursing care on patient outcomes through the analysis of interoperable nursing data gathered in EHRs. The first four articles, written between 1993 and 2000, provide a glimpse of initial steps and strategies. The final two, published respectively in 2009 and 2012, indicate a major shift from the earlier strategies and provide examples of the full integration and use of NNN in EHRs.In the first article, Harvey (1993) reported a successful pilot study in which a neural network (Art-2 NN) was applied to identify patterns of defining characteristics that aided the correct selection of five related nursing diagnoses. Written questionnaires, containing consistently labeled defining characteristics, were used to gather the data rather than actual documentation or EHR data. In the second, Coenen et al (1995) determined the prevalence of nursing interventions for six nursing diagnoses using data from the nursing information system (NIS) from one public hospital. The extracted data included NANDA diagnoses labels and the locally developed labels for related factors and nursing interventions. The third study by Moorhead and Delaney (1997) focused on describing and applying a set of rules they developed for manually mapping non-standardized nursing interventions to the standardized terms in the Nursing Intervention Classification terms using clinical data from one hospital. In the fourth study, Delaney et al (2000) examined the electronic documentation of 30 patients to assess the frequency with which a specified subset of defining characteristics and related factors were noted for patients assigned the NANDA diagnosis, Impaired Physical Mobility. Collectively these four studies provided preliminary evidence of the potential feasibility and utility of integrating NANDA and NIC into EHRs. Additional studies, however, would be needed to validate the generalizability of the results found in these small convenience samples. Moreover, yet to be considered was how NNN could be integrated into EHRs in ways that would produce standardized data for examining the impact of nursing care on patient outcomes.