Identification of COVID-19 using conventional radiography (chest X-rays) in the Emergency Department (ED) is a crucial skill for frontline clinicians. Report and Image Quality Control (RAIQC) is an original web-based tool designed to improve the image reporting ability of clinicians. (Click on image to find out more)
We set out to evaluate the use of this platform in order to measure and improve the accuracy of COVID-19 identification on chest X-rays via a multi-centre service improvement study. 112 clinicians working in EDs across five regional hospitals were recruited over a six-month period.
All recruits completed the initial assessment. 56 recruits completed all three training components. The initial mean accuracy of clinicians in identifying COVID-19 on chest X-rays was 43%. The mean accuracy was 57% amongst recruits who completed all three online training components. Participants who completed all training components had an improved reporting speed.
Online training can improve the accuracy of frontline clinicians in identifying COVID-19 on chest X-rays.
Below:
Poster presented at the Oxford School of Emergency Medicine Conference 2021
Abstract presentation at the Royal College of Emergency Medicine Annual Scientific conference 2021
Check out this great video
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