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Who waits longest in the emergency department and who leaves without being seen?

机译:谁在急诊室等待时间最长谁不见面就离开?

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摘要

>Objectives: To determine which patient characteristics are associated with prolonged waiting times in the emergency department and which characteristics are associated with an increased risk of leaving without being seen. >Methods: Multivariate analysis of routine data collected at the Northern General Hospital, Sheffield between 1 January and 31 December 2001. Patient age, sex, triage priority, postcode, initiator of attendance, mode of arrival, time, day, and month of presentation were examined as potential predictors of waiting time and risk of leaving without being seen. >Results: Waiting time data for 71 331 patients were analysed, along with a further 5512 patients who left without being seen. Older patients and those with lower triage priority had longer waiting times, while ambulance borne patients had slightly shorter waiting times. Sex, source of referral, and postcode did not predict waiting times. The most powerful predictors of waiting time related to time of presentation, with longer waits being associated with presentation at night, on Mondays or Sundays, and during autumn months. Patients who left without being seen were more likely to be younger, male, lower triage priority, non-ambulance borne, self referred, and presenting at the times when waiting times were longest. >Conclusion: Time of presentation, rather than individual patient characteristics, seem to be the most powerful predictors of waiting time. This suggests that concerns about inequity of waiting times should be addressed by reorganisation of staff duty rosters.
机译:>目标:确定哪些患者特征与急诊科等待时间长有关,哪些特征与离开医院而被发现的风险增加有关。 >方法:对2001年1月1日至12月31日在谢菲尔德北部总医院收集的常规数据进行多变量分析。患者年龄,性别,分流优先级,邮政编码,出勤人,到达方式,时间,演讲的日期和月份被视为等待时间和离开的风险的潜在预测因素。 >结果:分析了71 331例患者的等待时间数据,以及另外5512例未见踪影的患者的等待时间数据。年龄较大的患者和优先级较低的患者等待时间更长,而由救护车运送的患者的等待时间略短。性别,推荐来源和邮政编码无法预测等待时间。等待时间最有力的预测因素与演示时间有关,在晚上,周一或周日以及秋季的几个月中,较长的等待时间与演示相关。那些没有被看见的离开的患者更有可能是年轻,男性,分诊优先级较低,非救护车携带,自我介绍以及在等待时间最长的时候出诊。 >结论:呈现时间而不是个别患者的特征似乎是等待时间的最有力预测指标。这表明,应通过改组工作人员名册来解决对等待时间不均的担忧。

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