Department of Adult Intensive Care, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Department of Adult Intensive Care, Erasmus MC University Medical Center, Rotterdam, The Netherlands
BMJ Health Care Inform. 2021 Sep;28(1). doi: 10.1136/bmjhci-2021-100447.
In the current situation, clinical patient data are often siloed in multiple hospital information systems. Especially in the intensive care unit (ICU), large volumes of clinical data are routinely collected through continuous patient monitoring. Although these data often contain useful information for clinical decision making, they are not frequently used to improve quality of care. During, but also after, pressing times, data-driven methods can be used to mine treatment patterns from clinical data to determine the best treatment options from a hospitals own clinical data. In this implementer report, we describe how we implemented a data infrastructure that enabled us to learn in real time from consecutive COVID-19 ICU admissions. In addition, we explain our step-by-step multidisciplinary approach to establish such a data infrastructure. By sharing our steps and approach, we aim to inspire others, in and outside ICU walls, to make more efficient use of data at hand, now and in the future.
在当前情况下，临床患者数据通常在多个医院信息系统中被隔离。特别是在重症监护病房（ICU），通过对患者的连续监测，通常会定期收集大量的临床数据。尽管这些数据通常包含对临床决策有用的信息，但它们并不经常用于提高护理质量。在紧急时期，也可以在之后，使用数据驱动的方法从临床数据中挖掘治疗模式，以确定从医院自身临床数据中获得最佳治疗方案。在本实施者报告中，我们描述了如何实施数据基础架构，从而能够实时从连续的 COVID-19 ICU 入院患者中学习。此外，我们还解释了我们建立这种数据基础架构的多学科逐步方法。通过分享我们的步骤和方法，我们希望激励 ICU 内外的其他人，现在和将来更有效地利用手头的数据。
