Ibrahim Halah, Sorrell Sara, Nair Satish Chandrasekhar, Al Romaithi Ahmed, Al Mazrouei Shamma, Kamour Ashraf
Department of Medicine, Sheikh Khalifa Medical City, Abu Dhabi, United Arab Emirates.
Department of Medicine, Khalifa University College of Medicine and Health Sciences, Abu Dhabi, United Arab Emirates.
Acta Inform Med. 2020 Sep;28(3):209-213. doi: 10.5455/aim.2020.28.209-213.
The COVID-19 pandemic has created an unprecedented situation where sudden and prolonged surges of critically ill patients have disrupted healthcare systems worldwide A major concern for hospitals worldwide is how to best manage large numbers of COVID-19 infected and non-infected patients, while still maintaining high-quality clinical care.
This manuscript describes the system development, collaborative efforts and the challenges encountered in developing an in-house clinical intelligence dashboard.
Through a longitudinal, interdepartmental collaboration, a COVID-19 clinical intelligence dashboard was created using Microsoft Power BI and Cerner Computer Language (CCL) to demonstrate clinical severity of patients and patient location in a single screen. A color-coding schema was applied to produce a red highlight for patients whose condition is deteriorating, whether due to increasing oxygen demand or worsening laboratory values. An additional function enabled users to drill down into the patient's clinical and laboratory parameters for the past 5 days, and ultimately to the respective patient chart for further assessment.
The development of an in-house clinical intelligence dashboard is a feasible, effective tool to allow frontline clinicians to monitor patient status in multiple wards and proactively intervene as clinically necessary and transfer patients to the appropriate level of care. Comparing the 30 days before and 30 days after the implementation of the dashboard, the percentage of patients who required urgent intubation or cardiac resuscitation on the general medical ward, rather than a critical care setting, declined by over 50% (8 out of 34, 33% vs. 7 out of 55, 13%; two-tailed p < 0.05 by Fisher's exact test; OR 3.43; CI 1.07 to 10.95).
The dashboard has enabled physicians to efficiently assess patient volumes and case severity to prioritize clinical care and appropriately allocate scarce resources. The dashboard can be replicated by developing healthcare systems that are continuing to grapple with the pandemic.
新冠疫情造成了前所未有的局面，危重症患者的突然激增且持续时间之长，扰乱了全球医疗系统。全球医院面临的一个主要问题是如何在维持高质量临床护理的同时，妥善管理大量新冠病毒感染和未感染患者。
本文描述了内部临床智能仪表板的系统开发、协作努力以及开发过程中遇到的挑战。
通过纵向跨部门协作，利用微软Power BI和erner计算机语言（CCL）创建了一个新冠临床智能仪表板，以便在单个屏幕上展示患者的临床严重程度和所在位置。应用了一种颜色编码模式，为病情恶化的患者（无论是因氧气需求增加还是实验室检查结果恶化）突出显示为红色。另外一项功能使用户能够深入查看患者过去5天的临床和实验室参数，并最终查看相应患者病历以进行进一步评估。
开发内部临床智能仪表板是一种可行、有效的工具，可让一线临床医生监测多个病房的患者状况，并在临床需要时积极干预，将患者转至适当的护理级别。比较仪表板实施前30天和实施后30天的数据，普通内科病房中需要紧急插管或心脏复苏（而非在重症监护环境下）的患者比例下降了50%以上（34例中的8例，占33%；55例中的7例，占13%；Fisher精确检验的双侧p<0.05；OR 3.43；CI 1.07至10.95）。
该仪表板使医生能够有效评估患者数量和病例严重程度，以便确定临床护理的优先顺序并合理分配稀缺资源。正在应对疫情的医疗系统可以复制该仪表板。
