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Prioritization of Medical Errors in Patient Safety Management: Framework Using Interval-Valued Intuitionistic Fuzzy Sets

机译:患者安全管理中医疗错误的优先级:使用间隔值直觉模糊集的框架

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摘要

Medical errors negatively affect patients, healthcare professionals, and healthcare establishments. Therefore, all healthcare service members should be attentive to medical errors. Research has revealed that most medical errors are caused by the system, rather than individuals. In this context, guaranteeing patient safety and preventing medical faults appear to be basic elements of quality in healthcare services. Healthcare institutions can create internal regulations and follow-up plans for patient safety. While this is beneficial for the dissemination of patient safety culture, it poses difficulties in terms of auditing. On the other hand, the lack of a standard patient safety management system, has led to great variation in the quality of the provided service among hospitals. Therefore, this study aims to create an index system to create a standard system for patient safety by classifying medical errors. Due to the complex nature of healthcare and its processes, interval-valued intuitionistic fuzzy logic is used in the proposed index system. Medical errors are prioritized, based on the index scores that are generated by the proposed model. Because of this systematic study, not only can the awareness of patient safety perception be increased in health institutions, but their present situation can also be displayed, on the basis of each indicator. It is expected that the outcomes of this study will motivate institutions to identify and prioritize their future improvements in the patient safety context.
机译:医疗错误对患者,医疗保健专业人员和医疗保健机构负面影响。因此,所有医疗保健服务成员都应关注医疗错误。研究表明,大多数医疗错误是由系统而不是个人造成的。在这种情况下,保证患者安全性和预防医疗错误似乎是医疗保健服务质量的基本要素。医疗机构可​​以制定内部法规和患者安全的后续计划。虽然这对患者安全文化的传播有益,但它在审计方面存在困难。另一方面,缺乏标准的患者安全管理系统,导致医院提供的服务质量的巨大变化。因此,本研究旨在通过分类医疗错误来创建一个索引系统以创建用于患者安全的标准系统。由于医疗保健的复杂性及其过程,在所提出的指数系统中使用间隔的直觉模糊逻辑。基于所提出的模型生成的索引分数,优先考虑医疗错误。由于这种系统研究,患者安全感知的意识不仅可以在卫生机构增加,但他们的目前也可以在每个指标的基础上展示。预计本研究的结果将激励机构识别和优先考虑患者安全环境的未来改善。

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