Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT; Department of Emergency Medicine, Yale New Haven Health System, New Haven, CT.
Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT.
Ann Emerg Med. 2021 May;77(5):501-510. doi: 10.1016/j.annemergmed.2020.10.021. Epub 2021 Jan 15.
The measurement of emergency department (ED) throughput as a patient-centered quality measure is ubiquitous; however, marked heterogeneity exists between EDs, complicating comparisons for payment purposes. We evaluate 4 scoring methodologies for accommodating differences in ED visit volume and heterogeneity among ED groups that staff multiple EDs to improve the validity and "fairness" of ED throughput quality measurement in a national registry, with the goal of developing a volume-adjusted throughput measure that balances variation at the ED group level.
We conducted an ED group-level analysis using the 2017 American College of Emergency Physicians Clinical Emergency Data Registry data set, which included 548 ED groups inclusive of 889 unique EDs. We calculated ED throughput performance scores for each ED group by using 4 scoring approaches: plurality, simple average, weighted average, and a weighted standardized score. For comparison, ED groups (ie, taxpayer identification numbers) were grouped into 3 types: taxpayer identification numbers with only 1 ED; those with multiple EDs, but no ED with greater than 60,000 visits; and those with multiple EDs and at least 1 ED with greater than 60,000 visits.
We found marked differences in the classification of ED throughput performance between scoring approaches. The weighted standardized score (z score) approach resulted in the least skewed and most uniform distribution across the majority of ED types, with a kurtosis of 12.91 for taxpayer identification numbers composed of 1 ED, 2.58 for those with multiple EDs without any supercenter, and 3.56 for those with multiple EDs with at least 1 supercenter, all lower than comparable scoring methods. The plurality and simple average scoring approaches appeared to disproportionally penalize ED groups that staff a single ED or multiple large-volume EDs.
Application of a weighted standardized (z score) approach to ED throughput measurement resulted in a more balanced variation between different ED group types and reduced distortions in the length-of-stay measurement among ED groups staffing high-volume EDs. This approach may be a more accurate and acceptable method of profiling ED group throughput pay-for-performance programs.
将急诊科（ED）吞吐量作为以患者为中心的质量指标进行测量已经非常普遍；然而，ED 之间存在明显的异质性，这使得为支付目的进行比较变得复杂。我们评估了 4 种评分方法，以适应多科室 ED 工作人员的 ED 就诊量差异和 ED 组之间的异质性，从而提高全国注册中心 ED 吞吐量质量测量的有效性和“公平性”，目标是开发一种调整后的量纲吞吐量测量方法，以平衡 ED 组水平的变化。
我们使用 2017 年美国急诊医师学院临床急诊数据登记处数据集进行了 ED 组水平分析，该数据集包括 548 个 ED 组，共 889 个独特的 ED。我们使用 4 种评分方法计算每个 ED 组的 ED 吞吐量绩效评分：多数法、简单平均值、加权平均值和加权标准化评分。为了比较，ED 组（即纳税人识别号）分为 3 种类型：只有 1 个 ED 的纳税人识别号；有多个 ED，但没有任何一个 ED 的就诊量超过 60000 人的纳税人识别号；以及有多个 ED，至少有 1 个 ED 的就诊量超过 60000 人的纳税人识别号。
我们发现评分方法之间 ED 吞吐量性能的分类存在明显差异。加权标准化评分（z 评分）方法在大多数 ED 类型中产生的偏斜度最小且分布最均匀，偏度为 12.91，对于只有 1 个 ED 的纳税人识别号，偏度为 2.58，对于没有超级中心的多个 ED 的纳税人识别号，偏度为 3.56，对于至少有 1 个超级中心的多个 ED 的纳税人识别号，所有这些都低于可比评分方法。多数法和简单平均值评分方法似乎不成比例地惩罚只服务于单个 ED 或多个大容量 ED 的 ED 组。
应用加权标准化（z 评分）方法进行 ED 吞吐量测量，可在不同 ED 组类型之间产生更平衡的变化，并减少高容量 ED 工作人员的 ED 组之间的入住时间测量的扭曲。这种方法可能是一种更准确和可接受的 ED 组吞吐量绩效付费计划分析方法。
