Received June 6, 2021 from Los Angeles County Emergency Medical Service Agency, Santa Fe Springs, CA, USA (NB, MGH); Department of Emergency Medicine, Harbor UCLA Medical Center, Torrance, CA, USA (NB, JT, JTN, MGH); David Geffen School of Medicine at UCLA, Los Angeles, CA, USA (NB, JT, JTN, JLT, WJF, MGH); Department of Cardiology, Long Beach Medical Center, Long Beach, CA, USA (DS); Division of Cardiology, UCLA Medical Center, Torrance, CA, USA (JLT; WJF). Revision received July 27, 2021; accepted for publication August 3, 2021.
Prehosp Emerg Care. 2022 Nov-Dec;26(6):772-781. doi: 10.1080/10903127.2021.1965681. Epub 2021 Aug 24.
Within Emergency Medical Systems (EMS) regional systems, there may be significant differences in the approach to patient care despite efforts to promote standardization. Identifying hospital-level factors that contribute to variations in care can provide opportunities to improve patient outcomes. The purpose of this analysis was to evaluate variation in post-cardiac arrest care within a large EMS system and explore the contribution of hospital-level factors. This was a retrospective analysis from a regional cardiac system serving over 10 million persons. Patients with out-of-hospital cardiac arrest (OHCA) with return of spontaneous circulation (ROSC) are transported to 36 cardiac arrest centers with 24/7 emergent coronary angiography (CAG) capabilities and targeted temperature management (TTM) policies based on regional guidelines. We included adult patients ≥18 years with non-traumatic OHCA from 2016-2018. Patients with a Do-Not-Resuscitate order and those who died in the emergency department (ED) were excluded. For the TTM analysis, we also excluded patients who were alert in the ED. The primary outcome was receiving CAG or TTM after cardiac arrest. The secondary outcome was neurologic recovery (dichotomized to define a "good" outcome as cerebral performance category (CPC) 1 or 2). We used generalized estimating equations including patient-level factors (age, sex, witnessed arrest, initial rhythm) and hospital-level factors (academic status, hospital size based on licensed beds, annual OHCA patient volume) to estimate the odds ratios associated with these variables. There were 7831 patients with OHCA during the study period; 4694 were analyzed for CAG and 3903 for TTM. The median and range for treatment with CAG and TTM after OHCA was 23% (12-49%) and 58% (17-92%) respectively. Hospital size was associated with increased likelihood of CAG, adjusted odds ratio 1.71, 95% CI 1.05-2.86, p = 0.03. Academic status approached significance in its association with TTM, adjusted odds ratio 1.69, 95% CI 0.98-2.91, p = 0.06. Overall, 28% of patients survived with good neurologic outcome, ranging from 17 to 43% across hospitals. Within this regional cardiac system, there was significant variation in use of CAG and TTM after OHCA, which was not fully explained by patient-level factors. Hospital size was associated with increased CAG.
在紧急医疗服务（EMS）区域系统中，尽管努力促进标准化，但在患者护理方法上可能存在显著差异。确定导致护理差异的医院级别因素可为改善患者结局提供机会。本分析的目的是评估大型 EMS 系统内心脏骤停后护理的变化，并探讨医院级别因素的贡献。这是一项针对服务超过 1000 万人的区域心脏系统的回顾性分析。患有院外心脏骤停（OHCA）并恢复自主循环（ROSC）的患者被转运至 36 个心脏骤停中心，这些中心 24/7 均可进行紧急冠状动脉造影（CAG），并根据区域指南实施靶向体温管理（TTM）政策。我们纳入了 2016 年至 2018 年期间患有非创伤性 OHCA 的成年患者，年龄≥18 岁。排除有不复苏医嘱和在急诊科（ED）死亡的患者。对于 TTM 分析，我们还排除了在 ED 时意识清醒的患者。主要结局是心脏骤停后接受 CAG 或 TTM。次要结局是神经恢复（定义为良好结局的二分变量为脑功能预后分类（CPC）1 或 2）。我们使用包括患者级别因素（年龄、性别、目击性骤停、初始节律）和医院级别因素（学术地位、基于许可床位的医院规模、每年 OHCA 患者量）在内的广义估计方程，估计与这些变量相关的优势比。研究期间共有 7831 例 OHCA 患者；4694 例患者接受 CAG 治疗，3903 例患者接受 TTM 治疗。OHCA 后接受 CAG 和 TTM 治疗的中位数和范围分别为 23%（12%-49%）和 58%（17%-92%）。医院规模与 CAG 的可能性增加相关，调整后的优势比为 1.71，95%CI 为 1.05-2.86，p=0.03。学术地位与 TTM 的关联接近显著，调整后的优势比为 1.69，95%CI 为 0.98-2.91，p=0.06。总体而言，28%的患者存活且神经功能结局良好，不同医院的比例为 17%-43%。在这个区域性心脏系统中，OHCA 后 CAG 和 TTM 的使用存在显著差异，这不能完全用患者级别因素来解释。医院规模与 CAG 的增加有关。
