A novel approach to teaching cardiac auscultation
Author(s) -
Graham Peigh,
Joseph F. Majdan
Publication year - 2017
Publication title -
mededpublish
Language(s) - English
Resource type - Journals
ISSN - 2312-7996
DOI - 10.15694/mep.2017.000095
Subject(s) - auscultation , heart sounds , medicine , confidence interval , selection (genetic algorithm) , audiology , computer science , artificial intelligence
Purpose: Despite standard instruction, medical students cannot reliably identify common heart sounds and murmurs. The authors developed a novel approach to teach cardiac auscultation that uses process-based techniques to increase the diagnostic ability and confidence of physicians in training. Methods: 64 medical students were initially presented with a random selection of 10 heart sounds from Harvey, The Cardiopulmonary Patient Simulator, and graded on how many they could successfully recognize on a scale from 1-10. All students were then taught the novel approach to cardiac auscultation (the lesson). One day following the lesson, students were presented with another random selection of 10 heart sounds from Harvey, and graded on how many sounds they could correctly identify. Students then completed a survey regarding their confidence levels. Results: Students correctly identified more heart sounds after undergoing the lesson (prior to lesson: 4.1 (1.05); after lesson: 6.7 (1.00); p<0.001). Following the lesson, students also reported increased confidence in their ability to listen to heart sounds (prior: 1.70 (0.46); after: 3.13 (0.33); p<0.001). Conclusion: The novel approach to teaching cardiac auscultation is an effective means of instruction that increases diagnostic ability and confidence among medical students.
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