Harris M J, Gabriel R A, Dutton R P, Urman R D
Department of Anesthesiology, Perioperative, and Pain Medicine, Brigham and Women's Hospital, Boston, MA, United States.
Department of Anesthesiology, University of California, San Diego, San Diego, CA, United States; Department of Biomedical Informatics, University of California, San Diego, San Diego, CA, United States.
Int J Obstet Anesth. 2018 May;34:42-49. doi: 10.1016/j.ijoa.2018.01.002. Epub 2018 Jan 13.
Accurately predicting cesarean delivery case duration is an integral component of designing appropriate workflow protocols and ensuring adequate provider availability. Our primary objective was to describe the variability of case duration, based on factors that we hypothesized would be influential, such as hospital facility type, United States region, time of day, case volume, and patient and provider characteristics.
We analyzed hospital-, patient-, and provider-level variables from the National Anesthesia Clinical Outcomes Registry, a voluntary registry created to share anesthesia-related data and outcomes. Multivariable linear regression was performed to assess the association of these variables to case duration.
A total of 205332 cases were included in the final analysis. The majority of these cases came from medium-sized community hospitals (50.8%). Mean and median case duration were 115 and 79 minutes, respectively. Mean duration was longest for cases performed at university hospitals (143 min, standard deviation 136 min). Case duration varied in clinically meaningful ways based on hospital facility type, United States region, presence of a Certified Registered Nurse Anesthetist, and anesthesia type. Differences were not clinically significant with respect to other variables studied.
This study analyzed national cesarean delivery data and determined factors associated with cesarean delivery duration. We showed that case durations varied in meaningful ways according to facility type, United States region, presence of a Certified Registered Nurse Anesthetist, and anesthesia type. Our work contributes to a small but growing body of research on optimal staffing models for anesthesia practices.
准确预测剖宫产手术时长是设计合理工作流程方案以及确保有足够医护人员可用的一个重要组成部分。我们的主要目标是根据我们假设具有影响力的因素来描述手术时长的变异性，这些因素包括医院设施类型、美国地区、一天中的时间、手术量以及患者和医护人员特征。
我们分析了来自国家麻醉临床结果登记处的医院、患者和医护人员层面的变量，该登记处是一个为共享麻醉相关数据和结果而设立的自愿登记处。进行多变量线性回归以评估这些变量与手术时长之间的关联。
最终分析共纳入205332例病例。这些病例大多数来自中型社区医院（50.8%）。平均和中位数手术时长分别为115分钟和79分钟。在大学医院进行的手术平均时长最长（143分钟，标准差136分钟）。根据医院设施类型、美国地区、是否有注册护士麻醉师以及麻醉类型，手术时长在临床上有显著差异。对于所研究的其他变量，差异无临床意义。
本研究分析了全国剖宫产数据并确定了与剖宫产时长相关的因素。我们表明，手术时长根据设施类型、美国地区、是否有注册护士麻醉师以及麻醉类型而有显著差异。我们的工作为关于麻醉实践最佳人员配置模式的少量但不断增长的研究做出了贡献。
