Simulation-based Mastery Learning Improves Cardiac Auscultation Skills in Medical Students
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Cardiac auscultation is a core clinical skill. However, prior studies show that trainee skills are often deficient and that clinical experience is not a proxy for competence.
To describe a mastery model of cardiac auscultation education and evaluate its effectiveness in improving bedside cardiac auscultation skills.
Untreated control group design with pretest and posttest.
Third-year students who received a cardiac auscultation curriculum and fourth year students who did not.
A cardiac auscultation curriculum consisting of a computer tutorial and a cardiac patient simulator. All third-year students were required to meet or exceed a minimum passing score (MPS) set by an expert panel at posttest.
Diagnostic accuracy with simulated heart sounds and actual patients.
Trained third-year students (n = 77) demonstrated significantly higher cardiac auscultation accuracy compared to untrained fourth year students (n = 31) in assessment of simulated heart sounds (93.8% vs. 73.9%, p < 0.001) and with real patients (81.8% vs. 75.1%, p = 0.003). USMLE scores correlated modestly with a computer-based multiple choice assessment using simulated heart sounds but not with bedside skills on real patients.
A cardiac auscultation curriculum consisting of deliberate practice with a computer-based tutorial and a cardiac patient simulator resulted in improved assessment of simulated heart sounds and more accurate examination of actual patients.
Key wordsCardiac Auscultation simulation medical students learning
- 1.Butterworth JS, Reppert EH. Ausculatatory acumen in the general medical population. JAMA. 1960;174:32–4.Google Scholar
- 5.Accreditation Council for Graduate Medical Education Outcome Project. Available at: (http://www.acgme.org/Outcome). Accessed February 1, 2010.
- 12.Barsuk JH, McGaghie WC, Cohen ER, O’Leary KJ, Wayne DB. Simulation-based mastery learning reduces complications during central venous catheter insertion in a medical intensive care unit. Crit Care Med. 2009;37: in press.Google Scholar
- 17.Block, JH ed. Mastery Learning: Theory and Practice. New York: Holt, Rinehart and Winston 1971.Google Scholar
- 18.McGaghie WC, Miller GE, Sajid A, Telder TV. Competency-Based Curriculum Development in Medical Education. Public Health Paper No. 68, Geneva, Switzerland: World Health Organization 1978.Google Scholar
- 20.Shadish WR, Cook TD, Campbell DT. Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Boston: Houghton Mifflin; 2002.Google Scholar
- 22.Miami Group. UMedic User Manual. Gordon Center for Research in Medical Education, University of Miami Miller School of Medicine, 2007.Google Scholar
- 24.Issenberg SB, McGaghie WC, Brown DD, et al. Development of multimedia computer-based measures of clinical skills in bedside cardiology. In: Melnick DE, ed. The Eighth International Ottawa Conference on Medical Education and Assessment Proceedings. Evolving Assessment: Protecting the Human Dimension. Philadelphia: National Board of Medical Examiners; 2000:821–9.Google Scholar
- 26.Fleiss JL, Levin B, Paik MC. Statistical Methods for Rates and Proportions. 3rd ed. New York: John Wiley & Sons; 2003.Google Scholar
- 27.Brennan RL, Prediger DJ. Coefficient kappa: some uses, misuses and alternatives. Educ Psychol Meas. 1981;41:587–699.Google Scholar
- 30.Fletcher RH, Fletcher SW, Wagner EH. Clinical Epidemiology—The Essentials. 3rd ed. Baltimore: Williams & Wilkins; 1996.Google Scholar