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Using Flow Disruptions to Examine System Safety in Robotic-Assisted Surgery: Protocol for a Stepped Wedge Crossover Design

机译:利用流动中断来检查机器人辅助手术中的系统安全:阶梯式楔形交叉设计的协议

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Background The integration of high technology into health care systems is intended to provide new treatment options and improve the quality, safety, and efficiency of care. Robotic-assisted surgery is an example of high technology integration in health care, which has become ubiquitous in many surgical disciplines. Objective This study aims to understand and measure current robotic-assisted surgery processes in a systematic, quantitative, and replicable manner to identify latent systemic threats and opportunities for improvement based on our observations and to implement and evaluate interventions. This 5-year study will follow a human factors engineering approach to improve the safety and efficiency of robotic-assisted surgery across 4 US hospitals. Methods The study uses a stepped wedge crossover design with 3 interventions, introduced in different sequences at each of the hospitals over four 8-month phases. Robotic-assisted surgery procedures will be observed in the following specialties: urogynecology, gynecology, urology, bariatrics, general, and colorectal. We will use the data collected from observations, surveys, and interviews to inform interventions focused on teamwork, task design, and workplace design. We intend to evaluate attitudes toward each intervention, safety culture, subjective workload for each case, effectiveness of each intervention (including through direct observation of a sample of surgeries in each observational phase), operating room duration, length of stay, and patient safety incident reports. Analytic methods will include statistical data analysis, point process analysis, and thematic content analysis. Results The study was funded in September 2018 and approved by the institutional review board of each institution in May and June of 2019 (CSMC and MDRH: Pro00056245; VCMC: STUDY 270; MUSC: Pro00088741). After refining the 3 interventions in phase 1, data collection for phase 2 (baseline data) began in November 2019 and was scheduled to continue through June 2020. However, data collection was suspended in March 2020 due to the COVID-19 pandemic. We collected a total of 65 observations across the 4 sites before the pandemic. Data collection for phase 2 was resumed in October 2020 at 2 of the 4 sites. Conclusions This will be the largest direct observational study of surgery ever conducted with data collected on 680 robotic surgery procedures at 4 different institutions. The proposed interventions will be evaluated using individual-level (workload and attitude), process-level (perioperative duration and flow disruption), and organizational-level (safety culture and complications) measures. An implementation science framework is also used to investigate the causes of success or failure of each intervention at each site and understand the potential spread of the interventions.
机译:背景技术高科技将高科技进入医疗保健系统,旨在提供新的治疗选择,提高护理的质量,安全性和效率。机器人辅助手术是医疗保健高科技一体化的一个例子,这在许多手术学科中都变得无处不在。目的本研究旨在了解和测量当前的机器人辅助手术过程,以系统,定量和可复制的方式,以确定基于我们的观察和实施和评估干预措施的潜在系统威胁和改善机会。今年5年的研究将遵循人类的工程方法,提高4美国医院的机器人辅助手术的安全性和效率。方法该研究使用具有3个干预的阶梯式楔形交叉设计,在每个医院的不同序列中引入超过四个月的阶段。在以下专业中将观察到机器人辅助的手术程序:尿同步,妇科,泌尿外科,肥胖症,一般和结直肠癌。我们将使用从观察,调查和访谈收集的数据来提供专注于团队合作,任务设计和工作场所设计的干预措施。我们打算评估每个干预,安全文化,主观工作量的每种情况的态度,每种干预的有效性(包括直接观察每个观察阶段的手术​​样本),手术室持续时间,住宿时间和患者安全事件报告。分析方法将包括统计数据分析,点过程分析和主题内容分析。结果该研究于二零一八年九月供资,并于2019年5月和6月(CSMC和MDRH:Pro00056245; VCMC:研究270; Musc:ProS00088741)的每个机构的机构审查委员会批准。在精炼第1阶段的3个干预后,2019年11月开始的第2阶段(基准数据)的数据收集,并于2020年6月举行。然而,由于Covid-19大流行,将于3月20日暂停数据收集。我们在大流行前的4个地点收集了65个观察结果。阶段2的数据收集于10月20日在4个站点的2个中恢复。结论这将是在4个不同机构的680个机器人手术程序中进行的数据进行的最大直接观察研究。拟议的干预措施将使用个性级别(工作量和态度),过程级(围手术期持续时间和流动中断)和组织级(安全文化和并发症)措施进行评估。实施科学框架还用于调查每个站点的每个干预的成功或失败的原因,并理解干预措施的潜在传播。

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