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E-Triage Systems for COVID-19 Outbreak: Review and Recommendations.

Fahd AlhaidariAbdullah M AlmuhaidebShikah J AlsunaidiNehad M IbrahimNida AslamIrfan Ullah KhanFatema S ShaikhMohammed AlshahraniHajar M AlharthiYasmine M AlsenbelDima M Alalharith
Published in: Sensors (Basel, Switzerland) (2021)
With population growth and aging, the emergence of new diseases and immunodeficiency, the demand for emergency departments (EDs) increases, making overcrowding in these departments a global problem. Due to the disease severity and transmission rate of COVID-19, it is necessary to provide an accurate and automated triage system to classify and isolate the suspected cases. Different triage methods for COVID-19 patients have been proposed as disease symptoms vary by country. Still, several problems with triage systems remain unresolved, most notably overcrowding in EDs, lengthy waiting times and difficulty adjusting static triage systems when the nature and symptoms of a disease changes. In this paper, we conduct a comprehensive review of general ED triage systems as well as COVID-19 triage systems. We identified important parameters that we recommend considering when designing an e-Triage (electronic triage) system for EDs, namely waiting time, simplicity, reliability, validity, scalability, and adaptability. Moreover, the study proposes a scoring-based e-Triage system for COVID-19 along with several recommended solutions to enhance the overall outcome of e-Triage systems during the outbreak. The recommended solutions aim to reduce overcrowding and overheads in EDs by remotely assessing patients' conditions and identifying their severity levels.
Keyphrases
  • emergency department
  • sars cov
  • coronavirus disease
  • machine learning
  • end stage renal disease
  • chronic kidney disease
  • deep learning
  • pulmonary embolism
  • high resolution
  • physical activity
  • prognostic factors