Background: While ultrasound (US) has continued to expedite diagnosis and therapy for critical care physicians inside the hospital system, the technology has been slow to diffuse into the pre-hospital system. Given the diagnostic benefits of thoracic ultrasound (TUS), we sought to evaluate image recognition skills for two important TUS applications; the identification of B-lines (used in the US diagnosis of pulmonary edema) and the identification of lung sliding and comet tails (used in the US diagnosis of pneumothorax). In particular we evaluated the impact of a focused training module in a pre-hospital system that utilizes physicians as pre-hospital providers.
Methods: 27 Paris Service D'Aide Médicale Urgente (SAMU) physicians at the Hôpital Necker with varying levels of US experience were given two twenty-five image recognition pre-tests; the first test had examples of both normal and pneumothorax lung US and the second had examples of both normal and pulmonary edema lung US. All 27 physicians then underwent the same didactic training modules. A post-test was administered upon completing the training module and results were recorded.
Results: Pre and post-test scores were compared for both the pneumothorax and the pulmonary edema modules. For the pneumothorax module, mean test scores increased from 10.3 +/- 4.1 before the training to 20.1 +/- 3.5 after (p < 0.0001), out of 25 possible points. The standard deviation decreased as well, indicating a collective improvement. For the pulmonary edema module, mean test scores increased from 14.1 +/- 5.2 before the training to 20.9 +/- 2.4 after (p < 0.0001), out of 25 possible points. The standard deviation decreased again by more than half, indicating a collective improvement.
Conclusion: This brief training module resulted in significant improvement of image recognition skills for physicians both with and without previous ultrasound experience. Given that rapid diagnosis of these conditions in the pre-hospital system can change therapy, especially in systems where physicians can integrate this information into treatment decisions, the further diffusion of this technology would seem to be beneficial and deserves further study.