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[ICU Management & Practice]: 新冠病毒感染仪表盘:数据分析帮助ICU资源分配
2020年08月06日 时讯速递, 进展交流 暂无评论

ICU Management & Practice, Volume 20 - Issue 1, 2020

A COVID-19 Dashboard: Data Analytics to Aid Resource Allocation in Intensive Care Units

In this article, we focus on clinical and practical application of current available cloud-based data analysis to track and benchmark in real-time suspect and confirmed COVID-19 cases, resource use and availability.

Introduction

The COVID-19 pandemic represents an unprecedented challenge to intensive care units (ICU) due to the surge of severe cases of pneumonia posing great stress to hospitals and healthcare systems (Phua et al. 2020). The fast occupation of ICU beds by these severe cases has exceeded any possibilities of organisation and planning making ICU beds and ventilators a scarce and valuable resource (Phua et al. 2020). The possibility of monitoring case-load, local and regional trends as well as the current use and availability of resources in ICUs has become even more important in the present scenario (Phua et al. 2020; Salluh et al. 2018).

In the present article we describe the characteristics of a COVID-19 dashboard for ICUs and its deployment in 1100 ICUs.

Methods and Results

We used as a base the Epimed Monitor ICU system (epimedsolutions.com), a cloud-based quality improvement (QI) software that allows near-real time monitoring of case-mix, performance metrics and benchmarking for adult, paediatric and neonatal ICUs (Zampieri et al. 2017). The solution is currently implemented in 1100 ICUs in Belgium, Brazil, Chile, Colombia, France, Portugal and Uruguay. Data from this platform is also publicly available (beyond the scope of QI) in National projects (Belgium- micaproject.be, Brazil- utisbrasileiras.com, Uruguay- ucisuruguayas.com and the international project LOGIC – icubenchmarking.com). As of February 2020, we incorporated the diagnosis of COVID-19 pneumonia in the diagnostic/coding of Epimed. We subsequently developed an online platform that was seamlessly integrated with the Epimed Monitor database and allowed the near real-time surveillance of suspected and confirmed COVID-19 cases in the ICUs, its occupancy rates, use of mechanical ventilation (MV), outcomes (mortality) as well as the availability of ICU beds and ventilator support resources remaining (ventilators, NIV, ECMO) in the hospital (Figure 1). Through the benchmarking all users of Epimed can track the cumulative cases in their hospitals and region, including the outcomes and resource use. Thus, ICU managers can use near real-time data on the availability of the combined local and regional data to better inform the planning on resource allocation and use. In large hospitals with multiple ICUs or in a hospital network, such information would be a part of the routine evaluation of ICU status and therefore would improve the transparency of decision-making process of ICU admission of COVID-19 cases as well as serve as a platform to evaluate where to admit or transfer a patient within an ICU or hospital network.

In addition, the present pandemic represents a unique condition leading to ICU strain. Strain is defined as discordance between available resources and demand to admit more critically ill patients while continuing to provide the highest quality of care (Hussain et al. 2019). During a pandemic or a disaster management, it is fundamental to check the ICU strain. As an ICU manager it is possible to evaluate the ICU strain integrating all this information cited above and evaluate the contingency risk and eminent crisis in almost real time. Moreover, it is fundamental to develop a framework to triage and adequate resource allocation (Christian et al. 2014) and the availability of reliable and timely data is an important part of it.

Conclusions

The implementation of a specialised COVID-19 dashboard with near real-time information of suspected and confirmed cases as well as resource use and availability is feasible and was delivered in two weeks for 1100 ICUs in 7 countries. Information technology and clinical data may be used to help improve resource allocation in ICUs for the COVID-19 pandemic.

Data-driven management applied to COVID-19 patients in the ICU allows not only evaluation of ICU performance but may help the planning and resource allocation for these patients.

References:

Christian MD, Devereaux AV, Dichter JR et al. (2014) Introduction and Executive Summary Care of the Critically Ill and Injured During Pandemics and Disasters: CHEST Consensus Statement. Chest, 146(4S):8s-34s.

Hossain T, Ghazipura M, Dichter JR (2019) Intensive Care Role in Disaster Management Critical Care Clinics. Crit Care Clin, 35:535-550.

Phua J, Weng L, Ling L et al. (2020) Asian Critical Care Clinical Trials Group.Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations. Lancet Respir Med, S2213-2600(20)30161-2.

Salluh JIF, Chiche JD, Reis CE et al. (2018) New perspectives to improve critical care benchmarking. Ann Intensive Care, 8(1):17. doi: 10.1186/s13613018-0363-0.

Zampieri FG, Soares M, Borges LP et al. (2017) The Epimed Monitor ICU Database®: a cloud-based national registry for adult intensive care unit patients in Brazil. Rev Bras Ter Intensiva, Oct-Dec;29(4):418426.doi: 10.5935/0103-507X.20170062.

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