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Purpose <p>Point-of-care ultrasound (POCUS) has gained widespread adoption in medical diagnostics due to its simplicity, accessibility, and cost-effectiveness. However, insufficient training remains a significant challenge and limits its effective use. Particularly neglected is image pattern recognition and interpretation. Conventional educational methods are struggling to meet the growing demand for comprehensive POCUS training. This study aims to address this gap by introducing a novel approach using a computer-based image recognition and interpretation training (CBIRIT).</p> Materials and methods <p>In a prospective randomized controlled study, 46 medical students were divided into three groups: conventional teaching alone, conventional teaching with supplementary CBIRIT, and a control group with no training. A competency assessment test measured diagnostic performance in gallbladder disease detection. Pre- and post-test results were analyzed using non-parametric tests to compare performance within and between groups.</p> Results <p>The CBIRIT group showed a significant improvement in diagnostic performance (<i>p</i> &lt; .001). In contrast, the conventional teaching group showed no significant improvement. Interestingly, this group exhibited increased confidence (<i>p</i> &lt; .05) without improved performance, suggesting overconfidence.</p> Conclusion <p>CBIRIT significantly improves diagnostic performance in POCUS when compared to traditional teaching methods. It offers a resource-efficient solution to POCUS training, addressing conventional methods’ limitations and reducing overconfidence in diagnostic judgments. This approach also supports skill assessment and recertification.</p>

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POCUS - a new computer-based training approach for improving the quality of ultrasound diagnostics in gallbladder diseases

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月1日

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  • Florian Recker,
  • Stefan Michel,
  • Manuela Lehmann,
  • Gebhard Mathis,
  • Joseph Osterwalder

摘要

Purpose

Point-of-care ultrasound (POCUS) has gained widespread adoption in medical diagnostics due to its simplicity, accessibility, and cost-effectiveness. However, insufficient training remains a significant challenge and limits its effective use. Particularly neglected is image pattern recognition and interpretation. Conventional educational methods are struggling to meet the growing demand for comprehensive POCUS training. This study aims to address this gap by introducing a novel approach using a computer-based image recognition and interpretation training (CBIRIT).

Materials and methods

In a prospective randomized controlled study, 46 medical students were divided into three groups: conventional teaching alone, conventional teaching with supplementary CBIRIT, and a control group with no training. A competency assessment test measured diagnostic performance in gallbladder disease detection. Pre- and post-test results were analyzed using non-parametric tests to compare performance within and between groups.

Results

The CBIRIT group showed a significant improvement in diagnostic performance (p < .001). In contrast, the conventional teaching group showed no significant improvement. Interestingly, this group exhibited increased confidence (p < .05) without improved performance, suggesting overconfidence.

Conclusion

CBIRIT significantly improves diagnostic performance in POCUS when compared to traditional teaching methods. It offers a resource-efficient solution to POCUS training, addressing conventional methods’ limitations and reducing overconfidence in diagnostic judgments. This approach also supports skill assessment and recertification.