From the Departments of Emergency Medicine and Critical Care, Kaiser Permanente Oakland Medical Center, Oakland, CA, USA.
the Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
Acad Emerg Med. 2020 Oct;27(10):1028-1038. doi: 10.1111/acem.14068. Epub 2020 Jul 24.
Coronary risk scores are commonly applied to emergency department patients with undifferentiated chest pain. Two prominent risk score-based protocols are the Emergency Department Assessment of Chest pain Score Accelerated Diagnostic Protocol (EDACS-ADP) and the History, ECG, Age, Risk factors, and Troponin (HEART) pathway. Since prospective documentation of these risk determinations can be challenging to obtain, quality improvement projects could benefit from automated retrospective risk score classification methodologies.
EDACS-ADP and HEART pathway data elements were prospectively collected using a Web-based electronic clinical decision support (eCDS) tool over a 24-month period (2018-2019) among patients presenting with chest pain to 13 EDs within an integrated health system. Data elements were also extracted and processed electronically (retrospectively) from the electronic health record (EHR) for the same patients. The primary outcome was agreement between the prospective/eCDS and retrospective/EHR data sets on dichotomous risk protocol classification, as assessed by kappa statistics (ĸ).
There were 12,110 eligible eCDS uses during the study period, of which 66 and 47% were low-risk encounters by EDACS-ADP and HEART pathway, respectively. Agreement on low-risk status was acceptable for EDACS-ADP (ĸ = 0.73, 95% confidence interval [CI] = 0.72 to 0.75) and HEART pathway (ĸ = 0.69, 95% CI = 0.68 to 0.70) and for the continuous scores (interclass correlation coefficients = 0.87 and 0.84 for EDACS and HEART, respectively).
Automated retrospective determination of low risk status by either the EDACS-ADP or the HEART pathway provides acceptable agreement compared to prospective score calculations, providing a feasible risk adjustment option for use in large data set analyses.
冠状动脉风险评分常用于鉴别胸痛的急诊科患者。两种突出的基于风险评分的方案是急诊胸痛评分加速诊断方案（EDACS-ADP）和病史、心电图、年龄、风险因素和肌钙蛋白（HEART）路径。由于难以获得这些风险确定的前瞻性记录，质量改进项目可能受益于自动化的回顾性风险评分分类方法。
在 24 个月的时间里（2018 年至 2019 年），在一个集成的医疗系统中，使用基于网络的电子临床决策支持（eCDS）工具前瞻性地收集了 EDACS-ADP 和 HEART 路径的数据元素，这些数据元素来自 13 个急诊部胸痛患者。也从相同患者的电子健康记录（EHR）中提取并以电子方式（回顾性地）处理这些数据元素。主要结果是通过 Kappa 统计量（ĸ）评估前瞻性/eCDS 和回顾性/EHR 数据集在二分类风险方案分类上的一致性。
研究期间有 12110 个符合条件的 eCDS 使用，其中 EDACS-ADP 和 HEART 路径分别为低风险的占 66%和 47%。EDACS-ADP（ĸ=0.73，95%置信区间[CI]为 0.72 至 0.75）和 HEART 路径（ĸ=0.69，95%CI 为 0.68 至 0.70）的低风险状态和连续评分的一致性是可以接受的（EDACS 和 HEART 的组内相关系数分别为 0.87 和 0.84）。
与前瞻性评分计算相比，EDACS-ADP 或 HEART 路径自动回顾性确定低风险状态具有可接受的一致性，为在大数据集分析中使用提供了可行的风险调整选项。
