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首页> 外文期刊>BMJ Open >‘Errors’ and omissions in paper-based early warning scores: the association with changes in vital signs—a database analysis
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‘Errors’ and omissions in paper-based early warning scores: the association with changes in vital signs—a database analysis

机译:基于纸张的预警评分中的“错误”和遗漏:与生命体征变化的关联-数据库分析

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摘要

Objectives To understand factors associated with errors using an established paper-based early warning score (EWS) system. We investigated the types of error, where they are most likely to occur, and whether ‘errors’ can predict subsequent changes in patient vital signs. Methods Retrospective analysis of prospectively collected early warning system database from a single large UK teaching hospital. Results 16?795 observation sets, from 200 postsurgical patients, were collected. Incomplete observation sets were more likely to contain observations which should have led to an alert than complete observation sets (15.1% vs 7.6%, p0.001), but less likely to have an alerting score correctly calculated (38.8% vs 30.0%, p0.001). Mis-scoring was much more common when leaving a sequence of three or more consecutive observation sets with aggregate scores of 0 (55.3%) than within the sequence (3.0%, p0.001). Observation sets that ‘incorrectly’ alerted were more frequently followed by a correctly alerting observation set than error-free non-alerting observation sets (14.7% vs 4.2%, p0.001). Observation sets that ‘incorrectly’ did not alert were more frequently followed by an observation set that did not alert than error-free alerting observation sets (73.2% vs 45.8%, p0.001). Conclusions Missed alerts are particularly common in incomplete observation sets and when a patient first becomes unstable. Observation sets that ‘incorrectly’ alert or ‘incorrectly’ do not alert are highly predictive of the next observation set, suggesting that clinical staff detect both deterioration and improvement in advance of the EWS system by using information not currently encoded within it. Work is urgently needed to understand how best to capture this information.
机译:目的使用已建立的基于纸张的预警评分(EWS)系统来了解与错误相关的因素。我们调查了错误的类型,最可能发生的位置以及“错误”是否可以预测患者生命体征的后续变化。方法对英国一家大型教学医院的前瞻性预警系统数据库进行回顾性分析。结果收集了200例术后患者的16?795观察集。与完整的观察集相比,不完整的观察集更有可能包含应该引起警报的观察结果(15.1%对7.6%,p <0.001),但是正确计算警告分数的可能性较小(38.8%对30.0%,p <0.001)。当留下三个或三个以上连续观察集的序列且总分为0(55.3%)时,比序列内的错误得分高得多(3.0%,p <0.001)。 “无误”警报的观察集比无错误无警报观察集的出现频率更高,其次是正确警报的观察集(14.7%vs 4.2%,p <0.001)。与没有错误的警报观察集相比,“不正确”警报的观察集出现频率更高,其次是没有警报的观察集(73.2%对45.8%,p <0.001)。结论遗漏的警报在不完整的观察集中以及患者第一次变得不稳定时尤其常见。 “不正确”警报或“不正确”警报的观察结果高度预测下一个观察结果,表明临床人员通过使用当前未在其中编码的信息来提前发现EWS系统的恶化和改善。迫切需要进行工作以了解如何最好地捕获此信息。

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