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Coordination and Continuity of Intensive Care Unit Patient Care

机译:重症监护病房患者护理的协调与连续性

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Objective: Using Klein's model of team coordination, we explored the null hypothesis that intensive care unit (ICU) care coordination unfolds as a linear sequence. Our intent was to generate hypotheses for further research and to provide interim recommendations for improving care coordination. We also explored factors contributing to care coordination (e.g., role responsibilities, support tools). Background: Although the body of clinical communications research is considerable, few studies address broader team processes in real-world environments; hence, these processes are not well understood. Methods: All bedside communications for 5 ICU patients were recorded for 5 days per patient and were coded using Klein's model. Markov analysis was used to describe the care coordination process. Multivariate contingency table analysis and standardized parameter estimates described important contributing factors, and support tools were described using descriptive statistics. Results: First-, second-, and third-order Markov analyses show that care coordination does not unfold as a linear sequence; however, Markov diagrams suggest some process structure. Standardized parameter estimates of factors contributing to care coordination were calculated from a statistically significant three-way model (χ~2[df= 18] = 36.95, p< .005). Role-based differences depend on context, with important differences in contributions to care coordination occurring within rounds. Tools supported only 48% of conversations. Conclusion: Three alternative research hypotheses were defined with at least a minimal level of support. Testing these hypotheses present substantial theoretical, methodological, and data analysis challenges. Application: Within a research framework, recommendations for change could achieve significant gains for understanding and for reducing breakdowns in care coordination.
机译:目的:使用克莱因的团队协作模型,我们探索了重症监护病房(ICU)监护协调以线性序列展开的原假设。我们的目的是为进一步的研究提出假设,并为改善护理协调提供临时建议。我们还探讨了有助于护理协调的因素(例如,角色责任,支持工具)。背景:尽管临床交流研究的主体相当多,但很少有研究针对现实环境中的更广泛的团队流程进行研究;因此,这些过程不是很了解。方法:每位患者记录5位ICU患者的所有床旁通讯,每位患者连续5天,并使用Klein模型进行编码。马尔可夫分析用于描述护理协调过程。多变量列联表分析和标准化参数估计描述了重要的影响因素,并使用描述性统计数据描述了支持工具。结果:一阶,二阶和三阶马尔可夫分析表明,护理协调并没有以线性顺序展开。但是,马尔可夫图提出了一些过程结构。从具有统计学意义的三通模型计算出有助于护理协调的因素的标准参数估计值(χ〜2 [df = 18] = 36.95,p <.005)。基于角色的差异取决于具体情况,各轮之间对护理协调的贡献存在重要差异。工具仅支持48%的对话。结论:定义了三个替代研究假设,并至少提供了最低限度的支持。检验这些假设提出了巨大的理论,方法和数据分析挑战。应用:在研究框架内,对变更的建议可以在理解和减少护理协调失灵方面取得重大进展。

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  • 来源
    《Human Factors》 |2009年第3期|354-367|共14页
  • 作者单位

    Vanderbilt University Medical Center, Center for Perioperative Research in Quality,1211 21st Avenue South, Nashville, TN 37212;

    Alfred Hospital, Melbourne, Australia;

    Alfred Hospital, Melbourne, Australia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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  • 入库时间 2022-08-18 02:19:07

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