2020
DOI: 10.7861/fhj.2020-0037
|View full text |Cite
|
Sign up to set email alerts
|

COVID-19 recognition and digital risk stratification

Abstract: In the acute hospital setting the COVID-19 pandemic presents some unique challenges to acute patient care. These include accurate recognition of cases, confirmation of both testing requests and results, establishing patient acuity and alerting to deterioration. We report our experience introducing a digital COVID-19 assessment tool with an associated live dashboard at two acute NHS hospitals, enabling accurate hospital-level reporting alongside risk stratification.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
3
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(3 citation statements)
references
References 14 publications
(12 reference statements)
0
3
0
Order By: Relevance
“…Findings have shown that choosing various data sources, data granularity levels, and types of data to develop dashboards mainly depends on the dashboard’s objective and users’ needs (Florez and Singh 2020 ; Ibrahim et al 2020 ; Peddireddy et al 2020 ; Ulahannan et al 2020 ). For example, in most of the reviewed dashboards that used only primary data sources, the targeted users were generally healthcare professionals, and the data granularity was institutional level (Bae et al 2020 ; Hodgson et al 2020 ; Ibrahim et al 2020 ). Since the data sources used by the dashboards were primarily collected by authorized organizations, such as Centers for Disease Control and Prevention (CDC), WHO, and European Centre for Disease Prevention and Control (ECDC), the users could use these data more confidently to make fact-based decisions and take more appropriate actions at organizational, national, or global levels.…”
Section: Discussionmentioning
confidence: 99%
“…Findings have shown that choosing various data sources, data granularity levels, and types of data to develop dashboards mainly depends on the dashboard’s objective and users’ needs (Florez and Singh 2020 ; Ibrahim et al 2020 ; Peddireddy et al 2020 ; Ulahannan et al 2020 ). For example, in most of the reviewed dashboards that used only primary data sources, the targeted users were generally healthcare professionals, and the data granularity was institutional level (Bae et al 2020 ; Hodgson et al 2020 ; Ibrahim et al 2020 ). Since the data sources used by the dashboards were primarily collected by authorized organizations, such as Centers for Disease Control and Prevention (CDC), WHO, and European Centre for Disease Prevention and Control (ECDC), the users could use these data more confidently to make fact-based decisions and take more appropriate actions at organizational, national, or global levels.…”
Section: Discussionmentioning
confidence: 99%
“…Assessing whether certain symptoms are more specific for a positive COVID-19 test has utility to the clinical provider, providing a gauge that helps to discern whether any particular symptom is likely to place a patient in one of two groups: COVID-19 illness or not COVID-19 illness. This is crucial as it can help aid in risk stratification and efficient utilization of testing resources in children, which is critical to pandemic control [12][13] especially when resources are scarce, as was evident during the early months of the pandemic.…”
Section: Introductionmentioning
confidence: 99%
“…Assessing whether certain symptoms are more specific for a positive COVID-19 test has utility to the clinical provider, providing a gauge that helps to discern whether any particular symptom is likely to place a patient in one of two groups: COVID-19 illness or not COVID-19 illness. This is crucial as it can help aid in risk stratification and efficient utilization of testing resources in children, which is critical to pandemic control [12][13] especially when resources are scarce, as was evident during the early months of the pandemic.Given the varying presentations of pediatric COVID-19 illness, we conducted an analysis of symptom prevalence among pediatric patients presenting to emergency departments with concern for COVID-19 who subsequently received COVID-19 testing. We collected data from three pediatric emergency department (ED) facilities in a single health system during the initial stages of the pandemic.…”
mentioning
confidence: 99%