School of Nursing, University of São Paulo, São Paulo, Brazil.
Florida Atlantic University Christine E Lynn College of Nursing, Boca Raton, Florida, USA.
J Am Med Inform Assoc. 2023 Oct 19;30(11):1784-1793. doi: 10.1093/jamia/ocad144.
To analyze the nursing diagnostic concordance among users of a clinical decision support system (CDSS), The Electronic Documentation System of the Nursing Process of the University of São Paulo (PROCEnf-USP®), structured according to the Nanda International, Nursing Intervention Classification and Nursing Outcome Classification (NNN) Taxonomy.
This pilot, exploratory-descriptive study was conducted from September 2017 to January 2018. Participants were nurses, nurse residents, and nursing undergraduates. Two previously validated written clinical case studies provided participants with comprehensive initial assessment clinical data to be registered in PROCEnf-USP®. After having registered the clinical data in PROCEnf-USP®, participants could either select diagnostic hypotheses offered by the system or add diagnoses not suggested by the system. A list of nursing diagnoses documented by the participants was extracted from the system. The concordance was analyzed by Light's Kappa (K).
The research study included 37 participants, which were 14 nurses, 10 nurse residents, and 13 nursing undergraduates. Of the 43 documented nursing diagnoses, there was poor concordance (K = 0.224) for the diagnosis "Ineffective airway clearance" (00031), moderate (K = 0.591) for "Chronic pain" (00133), and elevated (K = 0.655) for "Risk for unstable blood glucose level" (00179). The other nursing diagnoses had poor or no concordance.
Clinical reasoning skills are essential for the meaningful use of the CDSS.
There was concordance for only 3 nursing diagnoses related to biological needs. The low level of concordance might be related to the clinical judgment skills of the participants, the written cases, and the sample size.
分析使用临床决策支持系统(CDSS)的用户之间的护理诊断一致性,该 CDSS 的结构依据的是 Nanda 国际、护理干预分类和护理结局分类(NNN)分类法。
这是一项试点、探索性描述研究,于 2017 年 9 月至 2018 年 1 月进行。参与者为护士、护士住院医师和护理本科生。两个先前经过验证的书面临床病例研究为参与者提供了全面的初始评估临床数据,以便在 PROCEnf-USP®中进行登记。在 PROCEnf-USP®中登记了临床数据后,参与者可以选择系统提供的诊断假设,也可以添加系统未提示的诊断。从系统中提取参与者记录的护理诊断列表。通过 Light's Kappa(K)分析一致性。
研究包括 37 名参与者,其中包括 14 名护士、10 名护士住院医师和 13 名护理本科生。在记录的 43 个护理诊断中,“无效气道清除”(00031)的诊断一致性较差(K=0.224),“慢性疼痛”(00133)的一致性为中度(K=0.591),“不稳定血糖水平风险”(00179)的一致性为高度(K=0.655)。其他护理诊断的一致性较差或没有一致性。
临床推理技能对于有意义地使用 CDSS 至关重要。
仅有 3 个与生物需求相关的护理诊断具有一致性。一致性水平低可能与参与者的临床判断技能、书面病例和样本量有关。