Federal University of Goias, Goiania, Brazil.
Federal University of Ceara, Fortaleza, Brazil.
J Nurs Scholarsh. 2022 May;54(3):376-387. doi: 10.1111/jnu.12747. Epub 2021 Nov 22.
A standardized language system can support the elaboration of clinical guidelines by matching information from similar patterns of response to people. To identify the factors that are related to a higher likelihood of an ineffective health management nursing diagnosis.
We conduct a systematic review and meta-analysis. An electronic search was conducted in MEDLINE databases via PubMed, Web of Science, SciELO, CINAHL, SCOPUS, and Embase between October and November 2020. Descriptive data were extracted from each article. The odds ratios for each etiological factor related to ineffective health management were directly extracted from the articles or calculated from the data described in the articles. The analysis of the measurements of exposure and the magnitude of the effect was performed using the statistical software R, and a forest plot was constructed for each etiological factor.
Ten studies were included, and 15 related factors were recovered from the primary studies. The factors that significantly increased the likelihood of an ineffective health management nursing diagnosis were insufficient knowledge of the therapeutic regimen, perceived barriers, powerlessness, economic disadvantage, and difficulty managing complex treatment regimens. No effect was verified with the following factors: decision conflict, family pattern of healthcare, and inadequate number of cues to action.
Factors related to a higher likelihood of ineffective health management may be the focus of early and targeted nursing interventions, contributing to an improved quality of care.
Understanding exposure to these factors can improve diagnostic reasoning at different population levels.
标准化语言系统可以通过匹配对人群的类似反应模式的信息，支持临床指南的详细说明。确定与更大概率的无效健康管理护理诊断相关的因素。
我们进行了系统评价和荟萃分析。2020 年 10 月至 11 月，我们通过 PubMed、Web of Science、SciELO、CINAHL、SCOPUS 和 Embase 在 MEDLINE 数据库中进行了电子检索。从每篇文章中提取描述性数据。直接从文章中提取每个与无效健康管理相关的病因因素的优势比，或从文章中描述的数据中计算。使用统计软件 R 对暴露和效应大小的测量进行分析，并为每个病因因素构建森林图。
纳入了 10 项研究，从原始研究中恢复了 15 个相关因素。增加无效健康管理护理诊断可能性的显著因素包括：治疗方案知识不足、感知障碍、无力感、经济劣势和复杂治疗方案管理困难。以下因素未验证出效果：决策冲突、家庭医疗保健模式和行动提示不足。
与无效健康管理可能性增加相关的因素可能是早期和有针对性的护理干预的重点，有助于提高护理质量。
了解这些因素的暴露情况可以提高不同人群水平的诊断推理能力。
