Effect of monitoring system design on response time to cardiac arrhythmias

 描述(由申请人提供)：美国医院每年尝试的心肺复苏术数量在37万到75万之间。这些患者中约有80%无法存活到出院。然而，对于许多人来说，无脉性室性心动过速或室颤(VT/VF)是第一个监测到的心律失常，可以通过迅速除颤来治疗。美国心脏协会建议在心脏骤停发作后2分钟内进行除颤治疗。然而，对于30%的患者来说，除颤延迟超过2分钟，使他们存活到出院的机会减少了一半。在护理有风险的住院患者方面，几乎没有什么比对潜在的致命心律失常做出迅速反应更重要的目标了；然而，几乎没有可靠的证据来指导实现这一目标的最佳实践。有一个NED可以更好地理解可修改因素对监测有效性的影响，这些因素包括监测人员的工作量、通信路径和辅助技术。在真实的医院单元中模拟心律失常使我们能够测量这些因素对反应时间的影响，而不会将患者置于危险之中。我们的目标是识别和测试有效的心脏监测系统的决定因素。为了实现这一目标，我们将首先比较10个监测系统，包括远程遥测、护士本地监测和具有自动通知的本地监测系统。在每个设置中，我们将使用来自访谈、观察和4个VT/VF模拟的数据来进行任务分析。任务分析将使我们能够根据从心律失常开始到临床医生到达患者病房的事件的顺序和时间来描述每个系统的特征，并建立相关的系统约束。利用任务分析的结果，我们将选择3个代表持续快速响应时间的最大潜力的系统，并在每个系统中进行详细的观察和20个VT/VF模拟。收集的数据将包括响应危急和非危急警报的比例以及在不同护理任务上花费的时间分布。这些数据将为开发每个系统的计算机模拟模型提供信息，使我们能够确定最有效的系统。模拟模型还将使我们能够进行敏感性(“假设”)分析。最后，在一个没有包括在研究中的新的患者护理单元中，我们将实施通过模拟模型确定的最有效的监测系统。我们将在实施前进行40次VT/VF模拟，并在实施后进行40次额外的模拟。我们假设，使用新系统对严重心律失常的反应时间将会更短。这项研究的预期结果是一系列监测因素，这些因素可以对严重心律失常的反应时间产生有利和不利的影响。所获得的知识将有助于开发和研究干预措施以改善心律失常的反应时间，并最终将有助于制定循证监测标准。这些标准的应用有望提高住院心脏骤停后的存活率。

 DESCRIPTION (provided by applicant): Between 370,000 and 750,000 cardiopulmonary resuscitations are attempted each year in US hospitals. Approximately 80% of these patients do not survive to discharge. However, for many, pulseless ventricular tachycardia or ventricular fibrillation (VT/VF) is the first monitored arrhythmia, and is treatable with prompt defibrillation The American Heart Association recommends defibrillation therapy within 2 minutes of cardiac arrest onset. Yet, for 30% of patients, defibrillation is delayed more than 2 minutes, reducing their chance of survival to hospital discharge by half. There are few more important objectives in caring for a hospitalized patient at risk than prompt response to potentially fatal arrhythmias; however, there is little reliable evidence to guide best practice for this objective. There is a ned for a better understanding of the impact of modifiable factors, including monitor watchers' workload, communication pathways, and supportive technologies, on monitoring effectiveness. Simulation of cardiac arrhythmias in real hospital units allows us to measure the effect of these factors on response times without putting patients at risk. Our objective is to identify and test determinants of effective cardiac monitoring systems. To achieve this objective, we will first compare 10 monitoring systems including remote telemetry, local monitoring by nurses, and local monitoring with automated notifications. In each setting, we will use data from interviews, observations, and 4 VT/VF simulations to conduct task analyses. The task analyses will allow us to characterize each system according to the sequence and timing of events from the beginning of an arrhythmia until a clinician arrives in the patient's room, and to establish the relevant system constraints. Using the findings from the task analyses, we will choose 3 systems that represent the greatest potential for consistently rapid response times and conduct detailed observations and 20 VT/VF simulations in each one. Data collected will include the proportion of critical and non-critical alarms responded to and the distribution of time spent on different nursing tasks. These data will inform the development of a computer simulation model of each system that will allow us to identify the most efficient system. The simulation models will also allow us to conduct sensitivity (`what-if') analyses. Finally, in a new patient care unit that was ot included in the study, we will implement the monitoring system determined to be the most efficient by the simulation models. We will conduct 40 VT/VF simulations before implementation and 40 additional simulations after implementation. We hypothesize that response times to the critical arrhythmias will be shorter using the new system. The expected outcome of this study is a catalog of monitoring factors that can favorably and unfavorably impact response times to critical arrhythmias. The knowledge gained will inform efforts to develop and study interventions to improve arrhythmia response time, and will ultimately help to develop evidence-based monitoring standards. The application of such standards is expected to improve survival after in-hospital cardiac arrest.