Improving the Accuracy of Emergency Department Clinicians in Detecting SARS-COV-2 on Chest X-Rays Using a Bespoke Virtual Training Platform

Abstract Background During and after the COVID pandemic, online learning became a key component in most undergraduate and post-graduate training. The non-specific symptoms of COVID-19 and limitations of available diagnostic tests can make it difficult to detect and diagnose in acute care settings. Accurate identification of SARS-CoV-2 related changes on chest x-ray (CXR) by frontline clinicians involved in direct patient care in the Emergency Department (ED) is an important skill. We set out to measure the accuracy of ED clinicians in detecting SARS-CoV-2 changes on CXRs and assess whether this could be improved using an online learning platform. Methods Baseline reporting performance of a multi-centre cohort of ED clinicians with varying experience was assessed via the Report and Image Quality Control (RAIQC) online platform. Emergency Medicine clinicians working in EDs across five hospitals in the Thames Valley Emergency medicine Research Network (TaVERN) region were recruited over a six-month period. An image bank was created containing both SARS-CoV-2 and non- SARS-CoV-2 pathological findings. Radiological ground truth diagnosis was established by thoracic radiologists. Participants then undertook an online training module with performance re-assessed. Diagnostic accuracy and speed of X-ray reporting was assessed before and after training in 3 subgroups: Consultants, Junior Doctors and Nurses. Results 90 clinicians undertook pre-training assessment with an overall reporting accuracy of 43.8 (±9.89)% across all cases. 56 participants completed the post-training assessment and reporting accuracy improved to 57.4 (±9.39)% (p<0.001). The sensitivity for recognition of SARS-CoV-2 improved from 64.7% to 76.8%. Conclusion ED clinicians show moderate baseline accuracy in the identification of SARS-CoV-2 related changes on CXR. Accuracy and speed can be improved by online training.