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Patient complaints as predictors of patient safety incidents

机译:患者投诉可预测患者安全事件

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Patients remain an underused resource in efforts to improve quality and safety in healthcare, despite evidence that they can provide valuable insights into the care they receive. This study aimed to establish whether high-level patient safety incidents (HLIs) were predictable from preceding complaints, enabling complaints to be used to prevent HLIs. For this study complaints received from November 2011 through June 2012 and HLI incident reports from April through September 2012 were examined. Complaints and HLIs were categorised according to location or specialty and the themes they included. Data were analysed to look for correlations between number of complaints and HLIs in a given area. A qualitative analysis was carried out to determine whether any complaints contained information that, if acted upon earlier, could have prevented later HLIs. In the data a total of 52 complaints and 16 HLIs were included. No correlation was established between location of HLIs and complaints. Complaints commonly focused on staff attitude, diagnostic problems and delayed treatment. HLIs most often arose from failure to recognise a patient’s deterioration and escalate appropriately or incorrect patient identification. Most HLIs were not preceded by similar complaints. However, in two instances complaints did signpost future HLIs. Patient complaints can highlight specific risks to patient safety and act as an early warning system. There is a need to devise reliable means of identifying the minority of complaints that do precede serious incidents.
机译:尽管有证据表明患者可以提供有关所接受护理的宝贵见解,但患者在努力提高医疗质量和安全性方面仍未得到充分利用。这项研究旨在确定从先前的投诉中是否可以预测出高级别的患者安全事件(HLI),从而使投诉可用于预防HLI。在本研究中,审查了从2011年11月至2012年6月收到的投诉以及从2012年4月至2012年9月收到的HLI事件报告。投诉和HLI根据位置或专业及其所包含的主题进行分类。分析数据以查找给定区域中投诉数量和HLI之间的相关性。进行了定性分析,以确定是否有任何投诉所包含的信息,如果尽早采取行动,可能会阻止以后的HLI。在数据中,总共包括52个投诉和16个HLI。在HLI的位置和投诉之间没有建立相关性。投诉通常集中在员工的态度,诊断问题和延误治疗上。 HLI最常起因于无法识别患者的病情恶化,无法适当升级,识别错误的患者。大多数HLI之前都没有类似的投诉。但是,有两次投诉确实签署了未来的HLI。患者投诉可以突出显示患者安全的特定风险,并可以作为预警系统。有必要设计一种可靠的方法来识别严重事件之前的少数投诉。

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