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Emergency residents' skill level in chest X-ray interpretation
1Emergency Medicine, King Fahad Medical City, Second Health Cluster, 11525 Riyadh, Saudi Arabia
2Emergency Medicine, Prince Mohammed Bin Abdulaziz Hospital, Second Health Cluster, 11676 Riyadh, Saudi Arabia
3Department of Internal Medicine, College of Medicine, Princess Nourah bint Abdulrahman University, 11671 Riyadh, Saudi Arabia
DOI: 10.22514/sv.2025.131 Vol.21,Issue 9,September 2025 pp.73-83
Submitted: 30 December 2024 Accepted: 05 March 2025
Published: 08 September 2025
*Corresponding Author(s): Muna Aljahany E-mail: msaljahany@pnu.edu.sa
Background: Emergency residents frequently perform chest X-rays (CXRs) in emergency departments (ED), yet their competency in interpreting these images is often questioned. This study evaluates the competency of ED residents in interpreting and diagnosing CXRs, and primarily determines their confidence and accuracy in CXR reading. Additionally, the current study assesses the factors influencing residents’ skills and the possibility of making medical decisions based on CXR images. Methods: An electronic survey was distributed to all Saudi emergency medicine residents (612 at the time of the study), collecting demographic data and participant characteristics, including sex, years of practice, elective rotation, interest in diagnostic radiology, and frequency of CXR readings per week. The survey had a response rate of 69.6% (426/612) and included the most commonly encountered CXR cases, each accompanied by a brief clinical description. Respondents selected the correct answers from multiple choices and rated their diagnostic confidence on a Likert scale from 1 to 5. Results: The accuracy of interpreting the ten CXR images was 70.6%, while the overall diagnostic confidence was notably low at 29.0%. Normal chest radiographs exhibited the highest interpretation accuracy (99.7%) but with only 23.8% confidence. The highest confidence was reported for diagnosing Pneumoperitoneum at 64.6%. The residents who completed an elective in diagnostic radiology had a higher diagnostic accuracy than those who did not receive adequate training (p = 0.0088). Despite their training, all ED residents indicated a significant lack of adequate training (p < 0.0001). Conclusions: Emergency residents displayed moderate accuracy in interpreting CXRs; however, they could not make medical decisions based solely on their interpretations. Further research is needed to determine the most cost-effective technique for reducing misinterpretations, and introducing artificial intelligence may be a future solution to increase CXR interpretation accuracy.
Residency program; Chest X-ray; Emergency medicine; Radiographs; Diagnostic error; Radiology education; Pneumothorax
Nouf Badr Alabdulwahed,Rawan Ishaq Tukruni,Muna Aljahany. Emergency residents' skill level in chest X-ray interpretation. Signa Vitae. 2025. 21(9);73-83.
[1] Morra M, Braund H, Hall AK, Szulewski A. Cognitive load and processes during chest radiograph interpretation in the emergency department across the spectrum of expertise. AEM Education and Training. 2021; 5: e10693.
[2] Rucker G, Kalayanamitra R, Gopaul R. Assessment of chest X-ray utilization for the evaluation of nontraumatic chest pain in an academic emergency department. International Journal of Radiology and Imaging Technology. 2021; 7: 76.
[3] Dreyer RG, van der Merwe CM, Nicolaou MA, Richards GA. Assessing and comparing chest radiograph interpretation in the Department of Internal Medicine at the University of the Witwatersrand medical school, according to seniority. African Journal of Thoracic and Critical Care Medicine. 2023; 29: 12–17.
[4] Fabre C, Proisy M, Chapuis C, Jouneau S, Lentz PA, Meunier C, et al. Radiology residents’ skill level in chest X-ray reading. Diagnostic and Interventional Imaging. 2018; 99: 361–370.
[5] Petts A, Neep M, Thakkalpalli M. Reducing diagnostic errors in the emergency department at the time of patient treatment. Emergency Medicine Australasia. 2023; 35: 466–473.
[6] Alherz F, Alharthi F, Almutari F, Alahmari A, Alsolami A, nojoom M, et al. X-ray interpretation in emergency department, do we need the radiologist? Journal of Radiology and Clinical Imaging. 2023; 6: 24–31.
[7] Hardy M, Snaith B, Scally A. The impact of immediate reporting on interpretive discrepancies and patient referral pathways within the emergency department: a randomised controlled trial. The British Journal of Radiology. 2013; 86: 20120112.
[8] Gatt ME, Spectre G, Paltiel O, Hiller N, Stalnikowicz R. Chest radiographs in the emergency department: is the radiologist really necessary? Postgraduate Medical Journal. 2003; 79: 214–217.
[9] Espinosa JA. Reducing errors made by emergency physicians in interpreting radiographs: longitudinal study. The BMJ. 2000; 320: 737–740.
[10] Petinaux B, Bhat R, Boniface K, Aristizabal J. Accuracy of radiographic readings in the emergency department. The American Journal of Emergency Medicine. 2011; 29: 18–25.
[11] Agrawal A. Emergency teleradiology-past, present, and, is there a future? Frontiers in Radiology. 2022; 2: 866643.
[12] Ali M, Waseem M. Emergency medicine protocols: enhancing patient outcomes with radiology insights. Frontier in Medical & Health Research. 2023; 1: 36–49.
[13] Kok EM, Abed A, Robben SGF. Does the use of a checklist help medical students in the detection of abnormalities on a chest radiograph? Journal of Digital Imaging. 2017; 30: 726–731.
[14] Villa SE, Wheaton N, Lai S, Jordan J. Radiology education among emergency medicine residencies: a national needs assessment. Western Journal of Emergency Medicine. 2021; 22: 1110–1116.
[15] Alsulimani L, AlRasheed B, Saeed A, Alabsi H. The competency of emergency medicine residents in interpreting hand X-rays across the three major regions of Saudi Arabia. Cureus. 2024; 16: e59270.
[16] Wardrope J, Chennells PM. Should all casualty radiographs be reviewed? British Medical Journal. 1985; 290: 1638–1640.
[17] Al Shammari M, Hassan A, AlShamlan N, Alotaibi S, Bamashmoos M, Hakami A, et al. Family medicine residents’ skill levels in emergency chest X-ray interpretation. BMC Family Practice. 2021; 22: 39.
[18] Ashworth M. When response rates do matter. The BMJ. 2001; 322: 675.
[19] Meyer VM, Benjamens S, Moumni ME, Lange JFM, Pol RA. Global overview of response rates in patient and health care professional surveys in surgery. Annals of Surgery. 2022; 275: e75–e81.
[20] Likert R. A technique for the measurement of attitudes. Archives of Psychology. 1932; 22: 140–155.
[21] Tekin E, Roediger HL. The range of confidence scales does not affect the relationship between confidence and accuracy in recognition memory. Cognitive Research: Principles and Implications. 2017; 2: 49.
[22] Kennedy S, Simon B, Alter HJ, Cheung P. Ability of physicians to diagnose congestive heart failure based on chest X-ray. The Journal of Emergency Medicine. 2011; 40: 47–52.
[23] Alburayh A, AlSubaie R, Almuhanna M, Hazem M. Medical interns’ skill levels in emergency chest X-ray interpretation. Saudi Journal of Radiology. 2023; 2: 1–15.
[24] Anderson PG, Tarder-Stoll H, Alpaslan M, Keathley N, Levin DL, Venkatesh S, et al. Deep learning improves physician accuracy in the comprehensive detection of abnormalities on chest X-rays. Scientific Reports. 2024; 14: 25151.
[25] Huang J, Neill L, Wittbrodt M, Melnick D, Klug M, Thompson M, et al. Generative artificial intelligence for chest radiograph interpretation in the emergency department. JAMA Network Open. 2023; 6: e2336100.
[26] Irmici G, Cè M, Caloro E, Khenkina N, Della Pepa G, Ascenti V, et al. Chest X-ray in emergency radiology: what artificial intelligence applications are available? Diagnostics. 2023; 13: 216.
[27] Ghauri SK, Mustafa KJ, Javaeed A, Khan AS. Accuracy of lung ultrasound and chest X-rays in diagnosing acute pulmonary oedema in patients presenting with acute dyspnoea in emergency department. JPMA. The Journal of the Pakistan Medical Association. 2021; 71: 2423–2425.
[28] McBee M, McBee L. The importance of providing clinical history for radiology studies in the urgent care setting. The Journal of Urgent Care Medicine. 2024; 18: 17–19.
[29] Mehdipoor G, Salmani F, Arjmand Shabestari A. Survey of practitioners’ competency for diagnosis of acute diseases manifest on chest X-ray. BMC Medical Imaging. 2017; 17: 49.
[30] Benger JR. What is the effect of reporting all emergency department radiographs? Emergency Medicine Journal. 2003; 20: 40–43.
[31] Afzal SS, Ali SK, Masood S. Emergency radiology training module: effect on radiology residents’ preparedness for on-call coverage. Pakistan Journal of Radiology. 2022; 32: 187–192.
[32] Mayhue FE, Rust DD, Aldag JC, Jenkins AM, Ruthman JC. Accuracy of interpretations of emergency department radiographs: effect of confidence levels. Annals of Emergency Medicine. 1989; 18: 826–830.
[33] Hwang EJ, Nam JG, Lim WH, Park SJ, Jeong YS, Kang JH, et al. Deep learning for chest radiograph diagnosis in the emergency department. Radiology. 2019; 293: 573–580.
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