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首页> 外文期刊>Reliability Engineering & System Safety >Application of a non-linear model to understand healthcare processes: using the functional resonance analysis method on a case study of the early detection of sepsis
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Application of a non-linear model to understand healthcare processes: using the functional resonance analysis method on a case study of the early detection of sepsis

机译：非线性模型在理解医疗保健过程中的应用：使用功能共振分析方法进行败血症早期检测的案例研究

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The use of non-linear models to understand complex processes in healthcare is not a fully adopted concept. Current patient safety research focuses on events by studying adverse events, typically trying to understand the root causes of failures. This article describes an attempt in a Danish hospital to create an understanding of how complex processes produce positive outcomes despite variability and unforeseen factors, using the functional resonance analysis method (FRAM) to describe a frequent activity in healthcare: early detection of sepsis. The model presents 40 activities performed by nurses, doctors, secretaries, health workers and laboratory technicians; and illustrates possible and actual variability in the process. The results reveal that the application of FRAM helped to gain a heightened understanding of a complex healthcare process. The FRAM provided new insights to staff by focusing on aspects that previously had not been central when working with the patient safety during sepsis detection. This included aspects such as becoming aware of the importance of asking the right questions during the referral process from a general practitioner, using experience and clinical judgement during early assessment of patients and the importance of having a good collegial relationship between doctors and nurses. The method helped reveal how the process is often able to succeed despite variability, and how aspects like experience and clinical judgement play a vital role in adapting to everyday conditions. This knowledge can enhance the understanding of how complex processes develop and be useful in supporting their management and improving patient safety.
机译：使用非线性模型来理解医疗保健中的复杂过程并不是一个完全采用的概念。当前的患者安全研究主要通过研究不良事件来关注事件，通常是试图了解失败的根本原因。本文介绍了在丹麦一家医院中尝试建立的理解，以了解尽管存在可变性和不可预见的因素，复杂的过程如何产生积极的结果，使用功能共振分析方法（FRAM）描述医疗保健中的频繁活动：败血症的早期检测。该模型展示了护士，医生，秘书，卫生工作者和化验员执行的40项活动；并说明了过程中可能的和实际的可变性。结果表明，FRAM的应用有助于加深对复杂医疗流程的了解。 FRAM通过专注于败血症检测过程中与患者安全一起工作时以前并不重要的方面，为工作人员提供了新的见解。这包括以下方面：意识到在全科医生转诊过程中提出正确问题的重要性，在对患者进行早期评估期间运用经验和临床判断以及在医生和护士之间保持良好的大学关系的重要性。该方法有助于揭示尽管存在可变性，但该过程通常如何能够成功完成，以及经验和临床判断等方面如何在适应日常条件方面发挥至关重要的作用。这些知识可以增进对复杂过程如何发展的理解，并有助于支持其管理和改善患者安全。

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