Becker Christian D, Yang Muer, Fusaro Mario, Fry Michael, Scurlock Corey S
eHealth Center, Westchester Medical Center Health Network, Valhalla, NY.
Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Westchester Medical Center and New York Medical College, Valhalla, NY.
Crit Care Explor. 2019 Dec 10;1(12):e0064. doi: 10.1097/CCE.0000000000000064. eCollection 2019 Dec.
Little is known on how to best prioritize various tele-ICU specific tasks and workflows to maximize operational efficiency. We set out to: 1) develop an operational model that accurately reflects tele-ICU workflows at baseline, 2) identify workflow changes that optimize operational efficiency through discrete-event simulation and multi-class priority queuing modeling, and 3) implement the predicted favorable workflow changes and validate the simulation model through prospective correlation of actual-to-predicted change in performance measures linked to patient outcomes.
Tele-ICU of a large healthcare system in New York State covering nine ICUs across the spectrum of adult critical care.
Seven-thousand three-hundred eighty-seven adult critically ill patients admitted to a system ICU (1,155 patients pre-intervention in 2016Q1 and 6,232 patients post-intervention 2016Q3 to 2017Q2).
Change in tele-ICU workflow process structure and hierarchical process priority based on discrete-event simulation.
Our discrete-event simulation model accurately reflected the actual baseline average time to first video assessment by both the tele-ICU intensivist (simulated 132.8 ± 6.7 min vs 132 ± 12.2 min actual) and the tele-ICU nurse (simulated 128.4 ± 7.6 min vs 123 ± 9.8 min actual). For a simultaneous priority and process change, the model simulated a reduction in average TVFA to 51.3 ± 1.6 min (tele-ICU intensivist) and 50.7 ± 2.1 min (tele-ICU nurse), less than the added simulated reductions for each change alone, suggesting correlation of the changes to some degree. Subsequently implementing both changes simultaneously resulted in actual reductions in average time to first video assessment to values within the 95% CIs of the simulations (50 ± 5.5 min for tele-intensivists and 49 ± 3.9 min for tele-nurses).
Discrete-event simulation can accurately predict the effects of contemplated multidisciplinary tele-ICU workflow changes. The value of workflow process and task priority modeling is likely to increase with increasing operational complexities and interdependencies.
对于如何以最佳方式对各种远程重症监护病房（tele-ICU）特定任务和工作流程进行优先级排序以实现运营效率最大化，我们知之甚少。我们着手开展以下工作：1）开发一个能准确反映基线时远程重症监护病房工作流程的运营模型；2）通过离散事件模拟和多类优先级排队建模，识别能优化运营效率的工作流程变化；3）实施预测的有利工作流程变化，并通过将与患者预后相关的绩效指标的实际变化与预测变化进行前瞻性关联，来验证模拟模型。
纽约州一个大型医疗系统的远程重症监护病房，涵盖九个不同类型的成人重症监护病房。
7387名入住该系统重症监护病房的成年重症患者（2016年第一季度干预前有1155名患者，2016年第三季度至2017年第二季度干预后有6232名患者）。
基于离散事件模拟对远程重症监护病房工作流程结构和分层流程优先级进行改变。
我们的离散事件模拟模型准确反映了远程重症监护病房重症监护医生首次视频评估的实际基线平均时间（模拟值为132.8±6.7分钟，实际值为132±12.2分钟）以及远程重症监护病房护士的首次视频评估实际基线平均时间（模拟值为128.4±7.6分钟，实际值为123±9.8分钟）。对于同时进行的优先级和流程改变，该模型模拟首次视频评估平均时间降至51.3±1.6分钟（远程重症监护病房重症监护医生）和50.7±2.1分钟（远程重症监护病房护士），低于单独对每个改变进行模拟时减少的时间之和，这表明这些改变在一定程度上具有相关性。随后同时实施这两个改变，使得首次视频评估的实际平均时间降至模拟的95%置信区间内的值（远程重症监护医生为50±5.5分钟，远程护士为49±3.9分钟）。
离散事件模拟能够准确预测预期的多学科远程重症监护病房工作流程改变所产生的效果。随着运营复杂性和相互依赖性的增加，工作流程和任务优先级建模的价值可能会提高。
