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Learning curves in emergency ultrasound education

Blehar, David J.
Barton, Bruce A
Gaspari, Romolo Joseph
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Abstract

OBJECTIVES: Proficiency in the use of bedside ultrasound (US) has become standard in emergency medicine residency training. While milestones have been established for this training, supporting data for minimum standard experience are lacking. The objective of this study was to characterize US learning curves to identify performance plateaus for both image acquisition and interpretation, as well as compare performance characteristics of learners to those of expert sonographers.

METHODS: A retrospective review of an US database was conducted at a single academic institution. Each examination was scored for agreement between the learner and expert reviewer interpretation and given a score for image quality. A locally weighted scatterplot smoothing method was used to generate a model of predicted performance for each individual examination type. Performance characteristics for expert sonographers at the site were also tracked and used in addition to performance plateaus as benchmarks for learning curve analysis.

RESULTS: There were 52,408 US examinations performed between May 2007 and January 2013 and included for analysis. Performance plateaus occurred at different points for different US protocols, from 18 examinations for soft tissue image quality to 90 examinations for right upper quadrant image interpretation. For the majority of examination types, a range of 50 to 75 examinations resulted in both excellent interpretation (sensitivity > 84% and specificity > 90%) and good image quality (90% the image quality benchmark of expert sonographers).

CONCLUSIONS: Educational performance benchmarks occur at variable points for image interpretation and image quality for different examination types. These data should be considered when developing training standards for US education as well as experience requirements for US credentialing.

Source

Acad Emerg Med. 2015 May;22(5):574-82. doi: 10.1111/acem.12653. Epub 2015 Apr 22. Link to article on publisher's site

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10.1111/acem.12653
PubMed ID
25903780
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