Lin Peter, Argon Nilay T, Cheng Qian, Evans Christopher S, Linthicum Benjamin, Liu Yufeng, Mehrotra Abhishek, Patel Mehul D, Ziya Serhan
Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, North Carolina, USA.
Information Services, ECU Health, Greenville, North Carolina, USA.
Acad Emerg Med. 2022 Nov;29(11):1320-1328. doi: 10.1111/acem.14598. Epub 2022 Oct 5.
We identify patient demographic and emergency department (ED) characteristics associated with rooming prioritization decisions among ED patients who are assigned the same triage acuity score.
We performed a retrospective analysis of adult ED patients with similar triage acuity, as defined as an Emergency Severity Index (ESI) of 3, at a large academic medical center, during 2019. Violations of a first-come-first-served (FCFS) policy for rooming are identified and used to create weighted multiple logistic regression models and 1:M matched case-control conditional logistic regression models to determine how rooming prioritization is affected by individual patient age, sex, race, and ethnicity after adjusting for patient clinical and time-varying ED operational characteristics.
A total of 15,781 ED encounters were analyzed, with 1612 (10.2%) ED encounters having a rooming prioritization in violation of a FCFS policy. Patient age and race were found to be significantly associated with being prioritized in violation of FCFS in both logistic regression models. The 1:M matched model showed a statistically significant relationship between violation of rooming prioritization with increasing age in years (adjusted odds ratio [aOR] 1.009, 95% confidence interval [CI] 1.005-1.013) and among African American patients compared to Caucasians (aOR 0.636, 95% CI 0.545-0.743).
Among ED patients with a similar triage acuity (ESI 3), we identified patient age and patient race as characteristics that were associated with deviation from a FCFS prioritization in ED rooming decisions. These findings suggest that there may be patient demographic disparities in ED rooming decisions after adjusting for clinical and ED operational characteristics.
我们确定了在被分配相同分诊 acuity 评分的急诊科(ED)患者中,与病房分配优先级决策相关的患者人口统计学和急诊科特征。
我们对 2019 年在一家大型学术医疗中心就诊的成年 ED 患者进行了回顾性分析,这些患者具有相似的分诊 acuity,定义为急诊严重程度指数(ESI)为 3。识别违反病房分配先到先得(FCFS)政策的情况,并用于创建加权多元逻辑回归模型和 1:M 匹配病例对照条件逻辑回归模型,以确定在调整患者临床和随时间变化的 ED 运营特征后,病房分配优先级如何受到患者个体年龄、性别、种族和民族的影响。
共分析了 15781 次 ED 就诊,其中 1612 次(10.2%)ED 就诊的病房分配优先级违反了 FCFS 政策。在两个逻辑回归模型中,患者年龄和种族均与违反 FCFS 而被优先考虑显著相关。1:M 匹配模型显示,违反病房分配优先级与年龄逐年增加(调整后的优势比[aOR]为 1.009,95%置信区间[CI]为 1.005 - 1.013)以及非裔美国患者与白种人相比(aOR 为 0.636,95%CI 为 0.545 - 0.743)之间存在统计学上的显著关系。
在分诊 acuity 相似(ESI 3)的 ED 患者中,我们确定患者年龄和患者种族是与 ED 病房分配决策中偏离 FCFS 优先级相关的特征。这些发现表明,在调整临床和 ED 运营特征后,ED 病房分配决策中可能存在患者人口统计学差异。