Nursing College, Federal University of Goiás, Goiás, Brazil.
Nursing College, Federal University of Ceará, Ceará, Brazil.
Worldviews Evid Based Nurs. 2022 Dec;19(6):489-499. doi: 10.1111/wvn.12602. Epub 2022 Aug 25.
Nursing diagnoses should reasonably represent global nursing practice phenomena, organizing indicators in their clinical structure that represent different scenarios and populations. However, few studies have summarized the evidence of these indicators, mainly for behavioral diagnoses.
This systematic review aimed to identify the best clinical indicators (CI) to determine the presence or absence of the nursing diagnosis "Ineffective Health Management" (IHM).
A systematic review with meta-analysis was utilized. Six electronic databases were consulted to retrieve studies that identified the nursing diagnosis IHM, with at least one CI. The period of data collection was between September and October 2020. The research group independently conducted the selection, quality assessment, data extraction, and analysis of all included studies. Fixed-effect measures and meta-analyses summarized sensitivity, specificity measures, and diagnostic odds ratios using the statistical software R. The preferred reporting items for systematic reviews and meta-analyses and standards for reporting studies of diagnostic accuracy guidelines were used to guide this review, and quality assessment of diagnostic accuracy studies was used for the critical appraisal of the methodological quality of the included studies.
The systematic review included 11 studies on people with chronic conditions, the elderly, and pregnant women. The analyzed four CI showed diagnostic odds ratios statistically higher than the unit value, highlighting the "Failure to include the treatment regimen in daily living" (DOR = 45.53; CI = 10.1, 205.6).
Overall, findings showed that all CI of the IHM nursing diagnosis had good sensitivity, specificity, and diagnostic odds ratio measures to identify their presence correctly. These findings can contribute to better accuracy in nurses' decision-making process, providing indicators to infer the IHM nursing diagnosis early in different population spectra based on the best measures of diagnostic accuracy.
护理诊断应合理地代表全球护理实践现象，在其临床结构中组织代表不同情况和人群的指标。然而，很少有研究总结这些指标的证据，主要是针对行为诊断。
本系统评价旨在确定最佳临床指标（CI）以确定护理诊断“无效健康管理”（IHM）的存在与否。
采用系统评价与荟萃分析。检索了六个电子数据库，以检索确定护理诊断 IHM 且至少有一个 CI 的研究。数据收集时间为 2020 年 9 月至 10 月。研究小组独立对所有纳入研究进行了选择、质量评估、数据提取和分析。使用统计软件 R 采用固定效应措施和荟萃分析汇总了灵敏度、特异性措施和诊断比值比。采用系统评价和荟萃分析的首选报告项目以及诊断准确性研究报告标准指南指导本评价，并使用诊断准确性研究的质量评估对纳入研究的方法学质量进行批判性评价。
系统评价纳入了 11 项针对慢性病患者、老年人和孕妇的研究。分析的四个 CI 显示诊断比值比统计上高于单位值，突出了“未能将治疗方案纳入日常生活”（DOR=45.53；CI=10.1, 205.6）。
总体而言，研究结果表明，IHM 护理诊断的所有 CI 均具有良好的灵敏度、特异性和诊断比值比测量值，可正确识别其存在。这些发现有助于提高护士决策过程的准确性，为不同人群谱中早期识别 IHM 护理诊断提供指标，基于最佳诊断准确性测量值。
