Consensus-based recommendations for research priorities related to interventions to safeguard patient safety in the crowded emergency department.
Consensus-based recommendations for research priorities related to interventions to safeguard patient safety in the crowded emergency department.
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DOI：
10.1111/j.1553-2712.2011.01234.x
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发表时间：
2011-12
期刊：
影响因子：
--
通讯作者：
Wears R
中科院分区：
文献类型：
--
作者：
Fee C;Hall K;Morrison JB;Stephens R;Cosby K;Fairbanks RT;Youngberg B;Lenehan G;Abualenain J;O'Connor K;Wears R
本文描述了2011年学术急诊医学（AEM）共识会议题为“在拥挤的急诊科中确保质量的干预措施”的安全保障干预分组会议的结果。急诊拥挤、患者安全和系统工程方面的专家使用多步骤命名小组技术，定义了与维持拥挤的急诊科安全相关的知识差距和优先研究问题。就与维持拥挤的急诊科安全的干预措施相关的七个研究重点达成了共识。其中包括：1)在拥挤期间，常规纠正过程和补偿机制如何变化？2)应该使用哪些指标来确定ED的安全性？3)检查清单如何确保更安全的护理，哪些因素导致了检查清单的成功或失败？什么构成安全的人员配备水平/比例？5)我们如何将急诊医学（EM）特定的患者安全问题与国家患者安全问题结合起来？6)我们如何开发指标和技能来识别ED何时接近灾难性过载条件？7)新兴市场可以从医学以外领域的专家和模型中学到什么，以开发创新的解决方案？这些优先事项有可能为与这一重要主题相关的未来临床和人为因素研究以及校外资助决策提供信息。
This article describes the results of the Interventions to Safeguard Safety breakout session of the 2011 Academic Emergency Medicine (AEM) consensus conference entitled “Interventions to Assure Quality in the Crowded Emergency Department.” Using a multistep nominal group technique, experts in emergency department (ED) crowding, patient safety, and systems engineering defined knowledge gaps and priority research questions related to the maintenance of safety in the crowded ED. Consensus was reached for seven research priorities related to interventions to maintain safety in the setting of a crowded ED. Included among these are: 1) How do routine corrective processes and compensating mechanism change during crowding? 2) What metrics should be used to determine ED safety? 3) How can checklists ensure safer care and what factors contribute to their success or failure? 4) What constitutes safe staffing levels / ratios? 5) How can we align emergency medicine (EM)-specific patient safety issues with national patient safety issues? 6) How can we develop metrics and skills to recognize when an ED is getting close to catastrophic overload conditions? and 7) What can EM learn from experts and modeling from fields outside of medicine to develop innovative solutions? These priorities have the potential to inform future clinical and human factors research and extramural funding decisions related to this important topic.
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