Division of Hospital Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
Department of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, California, USA.
J Am Med Inform Assoc. 2022 Jun 14;29(7):1279-1285. doi: 10.1093/jamia/ocac041.
There is a need for a systematic method to implement the World Health Organization's Clinical Progression Scale (WHO-CPS), an ordinal clinical severity score for coronavirus disease 2019 patients, to electronic health record (EHR) data. We discuss our process of developing guiding principles mapping EHR data to WHO-CPS scores across multiple institutions.
Using WHO-CPS as a guideline, we developed the technical blueprint to map EHR data to ordinal clinical severity scores. We applied our approach to data from 2 medical centers.
Our method was able to classify clinical severity for 100% of patient days for 2756 patient encounters across 2 institutions.
Implementing new clinical scales can be challenging; strong understanding of health system data architecture was integral to meet the clinical intentions of the WHO-CPS.
We describe a detailed blueprint for how to apply the WHO-CPS scale to patient data from the EHR.
需要一种系统的方法来实现世界卫生组织临床进展量表(WHO-CPS),这是一种针对 2019 年冠状病毒病患者的有序临床严重程度评分,以便将其应用于电子健康记录(EHR)数据。我们讨论了我们在多个机构开发指导原则,将 EHR 数据映射到 WHO-CPS 评分的过程。
使用 WHO-CPS 作为指导,我们开发了将 EHR 数据映射到有序临床严重程度评分的技术蓝图。我们将我们的方法应用于来自 2 家医疗中心的数据。
我们的方法能够对来自 2 家医疗机构的 2756 例患者就诊的 100%患者日进行临床严重程度分类。
实施新的临床量表可能具有挑战性;对卫生系统数据架构的深入了解对于满足 WHO-CPS 的临床意图至关重要。
我们描述了一个详细的蓝图,说明如何将 WHO-CPS 量表应用于来自 EHR 的患者数据。