Doubly-Robust Estimation of Effect of Imaging Resource Utilization on Discharge Decisions in Emergency Departments.
Doubly-Robust Estimation of Effect of Imaging Resource Utilization on Discharge Decisions in Emergency Departments.
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影像资源利用对急诊科出院决策影响的双稳健估计。
DOI：
10.1109/embc.2018.8513076
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Nemati,ShamimNemati
中科院分区：
文献类型：
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作者：
Tabaie,Azade;Chokshi,FalgunH;Holder,AndreL;Nemati,ShamimNemati
聚类分析提供了一种数据驱动的多维方法，用于识别队列中不同的患者亚组。每个聚类代表具有特定临床轨迹和医疗需求的特定健康状况。到急诊室就诊的患者不具有相同的健康状况，因此区分不同的群体可能会对诊断测试和资源利用产生影响。我们对2010年1月至2015年9月在埃默里三家医院急诊室就诊的13825例头部创伤和非卒中样非特异性神经系统症状患者进行了这项回顾性队列研究。我们利用k-means聚类找到五个不同的子组。然后，我们调查了紧急头部CT扫描是否会对出院产生统计学显著影响。对每个聚类应用调整的效应估计方法以估计接受诊断测试（例如，头部CT扫描）的处置状态。在队列中的五个患者亚组中，两个集群的出院机会受到头部CT扫描的显著影响。他们都包括年龄相对较大的非裔美国人或黑人患者，他们带着EMS来到急诊室，后者暗示着严重的健康状况。
Cluster analysis provides a data-driven multidimensional approach for identifying distinct subgroups of patients in a cohort. Each of the clusters represents a particular health condition with specific clinical trajectory and medical needs. Patients visiting emergency rooms do not share the same health condition, therefore discriminating between groups may have implications for diagnostic testing and resource utilization. We carried out this retrospective cohort study on 13825 patients who visited the emergency rooms in three Emory hospitals presenting with head trauma and non-stroke-like non-specific neurologic symptoms from January 2010 to September 2015. We utilized k-means clustering to find five distinct subgroups. Then, we investigated if getting an emergency head CT scan could have a statistically significant effect on getting discharged from the hospital. Adjusted effect estimation method was applied on each cluster to estimate the association between receiving a diagnostic test (e.g., head CT scan) on the disposition status. Out of five patient subgroups in the cohort, the chance of getting discharged for two clusters were significantly affected by getting a head CT scan. They both include comparatively older, African American or black patients who arrived in the ER with EMS, the latter suggesting critical health conditions.