Split flow models, in which a physician rather than a nurse performs triage, are increasingly being used in hospital emergency departments (EDs) to improve patient flow. Before deciding whether such interventions should be adopted, it is important to understand how split flows causally impact patient flow and outcomes. We employ causal inference methodology to estimate average causal effects of a split flow model on time to be roomed, time to disposition after being roomed, admission decisions, and ED revisits at a large tertiary teaching hospital that uses a split flow model during certain hours each day. We propose a regression discontinuity (RD) design to identify average causal effects, which we formalize with causal diagrams. Using electronic health records data (n = 21,570), we estimate that split flow increases average time to be roomed by about 4.6 minutes (95% CI: [2.9,6.2] minutes) but decreases average time to disposition by 14.4 minutes (95% CI: [4.1,24.7] minutes), leading to an overall reduction in length of stay. Split flow is also found to decrease admission rates by 5.9% (95% CI: [2.3%, 9.4%]) but not at the expense of a significant change in revisit rates. Lastly, we find that the split flow model is especially effective at reducing length of stay during low congestion levels, which mediation analysis partly attributes to early task initiation by the physician assigned to triage.
翻译:在医院急诊部门(急诊部门)越来越多地使用医生而不是护士进行分流模型,以便改善病人的流动情况。在决定是否应该采取此类干预措施之前,必须了解分流对病人流动和结果的因果关系。我们采用因果推论方法来估计分流模型的平均因果影响,以便及时间隔,在入院、入院决定和ED后处置时间,在使用分流模型的大型三级师范医院,每天某些小时使用分流模型。我们提议回归中断(RD)设计,以确定平均因果影响,我们用因果图表正式确定这一点。我们使用电子健康记录数据(n=21 570),我们估计,分流平均增加时间间隔大约4.6分钟(95% CI:[2.9,6.2分钟]分钟),但平均时间减少14.4分钟(95% CI:[4.1,24.7分钟]分钟),导致总体停留时间缩短。我们发现,分流减少5.9%(CI:[2.3%,9.4 % 模式)的入院率,但并非以电子病理学数据为基础的早期分析为代价,最后是大幅调整。