Ambulance Research Institute, Ambulance Service of New South Wales, Locked Bag 105, Rozelle, NSW 2039, Australia.
Emerg Med J. 2013 Jul;30(7):583-8. doi: 10.1136/emermed-2011-200971. Epub 2012 Jul 16.
The last decade has seen a vast amount of work directed at the investigation of patient harm events. Unfortunately, little of it has pertained to prehospital care and as such, risk remains unquantified and poorly understood in this setting. We hypothesised that adverse patient events occurring during the prehospital phase may fall into discernible patterns, and that an understanding of these patterns would be valuable in the development of mitigation strategies.
A survey tool was developed with reference to the human factors literature. Paramedics in a large Australian ambulance service were asked to recall an adverse event and to nominate factors that may have contributed to its occurrence. Responses were analysed using principal components analysis in order to identify contributory factors that could be statistically grouped together in meaningful patterns.
The survey yielded 370 responses. Eight key single contributors and 14 groups of contributory factors were identified. Of the groups, only two were strongly associated with serious patient outcomes, such as reported significant deterioration or death.
The deteriorating patient was identified as the leading single contributor to prehospital adverse events, and two perfect storm patient harm scenarios were found to contribute materially to adverse outcomes. This approach to identifying both single factors contributing to an incident and factors which could be grouped together in a pattern, appears useful in delineating risk in the acute prehospital setting, and warrants further exploration in this and other areas of patient safety.
在过去的十年中，大量的工作致力于调查患者伤害事件。不幸的是，其中很少涉及院前护理，因此，风险在这一领域仍然没有被量化和很好地理解。我们假设在院前阶段发生的不良患者事件可能会呈现出可识别的模式，而了解这些模式对于制定缓解策略将是有价值的。
该研究参考了人为因素文献开发了一种调查工具。要求澳大利亚一家大型救护车服务机构的护理人员回忆一起不良事件，并提名可能导致事件发生的因素。使用主成分分析对响应进行了分析，以确定可以以有意义的模式进行统计分组的促成因素。
调查共产生了 370 份回复。确定了 8 个关键的单一促成因素和 14 个促成因素组。在这些组中，只有两组与严重的患者结果密切相关，例如报告的显著恶化或死亡。
情况恶化的患者被确定为院前不良事件的主要单一促成因素，发现两个完美风暴患者伤害场景对不良结果有实质性贡献。这种识别导致事件发生的单一因素和可以组合在一起形成模式的因素的方法，似乎有助于在急性院前环境中划定风险，并值得在这一领域和患者安全的其他领域进一步探索。
