Updating Eindhoven: Clarifying the features of a patient safety near miss

IF 0.6 Q4 HEALTH CARE SCIENCES & SERVICES
Nick Woodier, Charlotte Burnett, Paul Sampson, Iain Moppett
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Abstract

There are benefits to healthcare from reporting and learning from near misses in patient care. However, there have been longstanding issues with identifying near misses, with variation in definitions. Learning is being lost, unlike in other industries that have harnessed their learning potential. The features of a healthcare near miss have never been described nor modelled. This study aimed to identify those features to support near-miss identification, reporting and learning. This study took a mixed-methods approach with participants from healthcare and four high-reliability industries – aviation, maritime, nuclear and rail. Qualitative exploration helped identify the features of a near miss, while quantitative supported assessment of agreement on features between participants through the use of a scenario. Participants from 17 healthcare and 35 industry organisations took part. Quantitative findings demonstrated variation in agreement of the features of a near miss using Fleiss Kappa. Qualitative findings identified the following themes in relation to the features of a near miss – context dependent, involve control, are complex and represent vulnerabilities. In particular, several industries have lists of specific situations that constitute near misses that support reporting and focus. Without clear agreement of the features of a healthcare near miss, definitions will continue to vary. This study has, for the first time, provided exploration and clarification of the features of a near miss with the offer of a healthcare model for future validation. Without addressing the fundamentals, such as agreeing what a near miss is, healthcare cannot hope to learn from them.
更新埃因霍温:明确患者安全险情的特征
报告病人护理中的险情并从中吸取教训,对医疗保健工作大有裨益。然而,长期以来,在识别险情方面一直存在问题,对险情的定义也不尽相同。与其他利用学习潜力的行业不同,医疗保健行业正在失去学习的机会。医疗保健险情的特征从未被描述或模拟过。本研究旨在确定这些特征,以支持近乎失误的识别、报告和学习。这项研究采用了混合方法,参与者来自医疗保健和四个高可靠性行业--航空、海事、核能和铁路。定性探索有助于识别近乎失误的特征,而定量探索则通过使用情景模拟,支持对参与者之间就特征达成的一致意见进行评估。来自 17 家医疗保健机构和 35 家行业组织的参与者参加了此次活动。定量研究结果表明,使用弗莱斯卡帕法(Fleiss Kappa)对险情特征的一致意见存在差异。定性研究结果确定了以下与险情特征相关的主题--取决于情境、涉及控制、复杂且代表脆弱性。特别是,一些行业列出了构成险情的具体情况,以支持报告和关注。如果不能就医疗保健险情的特征达成明确的一致意见,定义将继续存在差异。本研究首次对险情的特征进行了探讨和澄清,并提供了一个医疗模型供未来验证。如果不解决基本问题,例如不就什么是医疗差错达成一致意见,医疗保健行业就不可能从中吸取教训。
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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2.00
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