Decreased length of stay after addition of healthcare provider in emergency department triage: a comparison between computer-simulated and real-world interventions.
Decreased length of stay after addition of healthcare provider in emergency department triage: a comparison between computer-simulated and real-world interventions.
复制标题
DOI：
10.1136/emermed-2012-201113
复制
发表时间：
2013-02
期刊：
影响因子：
--
通讯作者：
Goldlust EJ
中科院分区：
文献类型：
--
作者：
Day TE;Al-Roubaie AR;Goldlust EJ
(1)确定在分诊中增加提供者对平均住院时间（LOS）和LOS>6 h的患者比例的影响。 (2)评估计算机模拟在预测这些指标的影响程度方面的准确性。一项组水平的准实验性试验，比较了圣路易斯退伍军人事务医疗中心急诊科（1）干预前，（2）提供者分诊后，以及类似（3）“前”和（4）“后”条件的离散事件模拟（DES）模型。结果测量为每日平均LOS和LOS >6 h的患者百分比。 DES模型干预预测6小时LOS %从19.0%下降到13.1%，日平均LOS从249分钟下降到200分钟（p<0.0001）。 在（实际）干预后，LOS >6小时的患者数量从19.9%降至14.3%（p<0.0001），每日平均LOS从247分钟降至210分钟（p<0.0001）。 在这种情况下，医生和中级提供者在分诊时的覆盖率显著降低了急诊科的LOS。DES准确地预测了这种影响的程度。这些结果表明，进一步的工作，在分流供应商的普遍性和DES预测过程变化的定量影响的效用。
(1) To determine the effects of adding a provider in triage on average length of stay (LOS) and proportion of patients with >6 h LOS. (2) To assess the accuracy of computer simulation in predicting the magnitude of such effects on these metrics. A group-level quasi-experimental trial comparing the St. Louis Veterans Affairs Medical Center emergency department (1) before intervention, (2) after institution of provider in triage, and discrete event simulation (DES) models of similar (3) ‘before’ and (4) ‘after’ conditions. The outcome measures were daily mean LOS and percentage of patients with LOS >6 h. The DES-modelled intervention predicted a decrease in the %6-hour LOS from 19.0% to 13.1%, and a drop in the daily mean LOS from 249 to 200 min (p<0.0001). Following (actual) intervention, the number of patients with LOS >6 h decreased from 19.9% to 14.3% (p<0.0001), with the daily mean LOS decreasing from 247 to 210 min (p<0.0001). Physician and mid-level provider coverage at triage significantly reduced emergency department LOS in this setting. DES accurately predicted the magnitude of this effect. These results suggest further work in the generalisability of triage providers and in the utility of DES for predicting quantitative effects of process changes.
登录
查看更多内容
影响因子：
6.2
作者：
Chan, TC;Killeen, JP;Guss, DA
通讯作者：
Guss, DA
影响因子：
5.4
作者：
Ackroyd-Stolarz, S.;Guernsey, J. Read;Kovacs, G.
通讯作者：
Kovacs, G.
影响因子：
6.2
作者：
Khare, Rahul K.;Powell, Emilie S.;Lucenti, Martin
通讯作者：
Lucenti, Martin
影响因子：
6.2
作者：
Kyriacou, DN;Ricketts, V;Talan, DA
通讯作者：
Talan, DA
影响因子：
4.8
作者：
Levin, Scott R.;Dittus, Robert;France, Daniel
通讯作者：
France, Daniel