Failure To Rescue, What Can Be Done To Prevent It?

Duarte de Brito Tiago Marçal Pedro, P. Maria, Machado Humberto
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引用次数: 1

Abstract

Introduction: Failure to Rescue (FTR) is the failure to prevent a patient’s death after a complication. It measures the ability of a hospital to prevent the death of patients who develop one or more complication that was not present at the time of admission. Therefore, the aim of this study is to review the factors that contribute to FTR, and the measures and strategies that can be applied to prevent the FTR events, in order to discuss the best way to improve patient outcomes in the hospital setting. Methods: A search was conducted on PUBMED retrieving a total of 464 articles. A review of the selected articles’ bibliography was conducted to find other relevant articles. Sixty studies were reviewed in this paper. Results: Patient factors as increasing age, comorbidities and frailty increase the risk of FTR, as well as an increasing number of complications. Several hospital factors, nursing care, and microsystem also influence FTR. Some track and Trigger Systems (TTS) and Early Warning Scores (EWS) have been shown to predict clinical deterioration. On the other hand, machine learning systems have outperformed EWS. Rapid response teams have become the standard approach to delivery and escalation of care, and cognitive aids and crisis checklists also have potential to help reduce FTR. Conclusion: Patient and hospital factors are often non-modifiable; thus, microsystem factors could be a target for improvement. Creating clinical pathways can improve surveillance, and communication tools like SBAR can help relay information. EWS, machine learning models and continuous monitoring are strategies that can help detect clinical deterioration. In the efferent limb rapid response teams have shown to reduce FTR.
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救援失败,如何预防?
简介:抢救失败(FTR)是指在并发症发生后未能阻止患者死亡。它衡量的是医院防止出现入院时不存在的一种或多种并发症的患者死亡的能力。因此,本研究的目的是回顾导致FTR的因素,以及可用于预防FTR事件的措施和策略,以便讨论改善医院环境中患者预后的最佳方法。方法:在PUBMED检索共464篇文献。对所选文章的参考书目进行了审查,以找到其他相关文章。本文对60项研究进行了综述。结果:年龄增加、合并症和虚弱等患者因素增加了FTR的风险,并发症数量也增加了。一些医院因素、护理和微系统也会影响FTR。一些跟踪和触发系统(TTS)和早期预警评分(EWS)已被证明可以预测临床恶化。另一方面,机器学习系统的表现优于EWS。快速反应小组已成为提供和升级护理的标准方法,认知辅助工具和危机检查清单也有可能有助于减少FTR。结论:患者和医院因素往往不可改变;因此,微系统因素可能是一个改进的目标。建立临床途径可以改善监测,像SBAR这样的通信工具可以帮助传递信息。EWS、机器学习模型和持续监测是有助于检测临床恶化的策略。在传出肢体快速反应小组已经显示出减少FTR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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