Division of Medical Information Sciences, University Hospitals of Geneva.
Department of Radiology and Medical Informatics, University of Geneva.
Stud Health Technol Inform. 2022 May 25;294:317-321. doi: 10.3233/SHTI220466.
In spring 2020, as the COVID-19 pandemic is in its first wave in Europe, the University hospitals of Geneva (HUG) is tasked to take care of all Covid inpatients of the Geneva canton. It is a crisis with very little tools to support decision-taking authorities, and very little is known about the Covid disease. The need to know more, and fast, highlighted numerous challenges in the whole data pipeline processes. This paper describes the decisions taken and processes developed to build a unified database to support several secondary usages of clinical data, including governance and research. HUG had to answer to 5 major waves of COVID-19 patients since the beginning of 2020. In this context, a database for COVID-19 related data has been created to support the governance of the hospital in their answer to this crisis. The principles about this database were a) a clearly defined cohort; b) a clearly defined dataset and c) a clearly defined semantics. This approach resulted in more than 28 000 variables encoded in SNOMED CT and 1 540 human readable labels. It covers more than 216 000 patients and 590 000 inpatient stays. This database is used daily since the beginning of the pandemic to feed the "Predict" dashboards of HUG and prediction reports as well as several research projects.
2020 年春季，随着 COVID-19 疫情在欧洲处于第一波高峰期，日内瓦大学附属医院（HUG）负责照顾日内瓦州的所有 COVID-19 住院患者。这是一场危机，几乎没有工具可以为决策机构提供支持，而且对 COVID-19 疾病知之甚少。需要尽快了解更多情况，这突显了整个数据管道流程中的许多挑战。本文描述了为构建一个支持临床数据的多个二次使用（包括治理和研究）的统一数据库而做出的决策和开发的流程。自 2020 年初以来，HUG 已经应对了 5 波 COVID-19 患者。在这种情况下，创建了一个 COVID-19 相关数据的数据库，以支持医院在应对这场危机中的治理。该数据库的原则是：a）明确界定的队列；b）明确界定的数据集；c）明确界定的语义。这种方法导致超过 28000 个变量采用 SNOMED CT 编码和 1540 个人可读标签。它涵盖了超过 216000 名患者和 590000 次住院。自疫情开始以来，该数据库每天都被用于为 HUG 的“Predict”仪表板和预测报告以及多个研究项目提供数据。
