Teaching cardiac auscultation: effectiveness of a patient-centered teaching conference on improving cardiac auscultatory skills.

OBJECTIVES: To assess the cardiac auscultatory skills of health care professionals before and after an actual (not simulated) patient-centered cardiac auscultation conference and to determine the effectiveness of this clinical teaching method on Improving diagnostic proficiency. SUBJECTS AND METHODS: Seventy-eight participants at a conference on cardiac auscultation completed preconference and postconference examinations on their ability to diagnose a wide variety of heart sounds and murmurs. Among those tested, 46 (59%) were physicians: 17 (22%) were cardiologists, 19 (24%) were medical Interns or residents, 7 (9%) were cardiology fellows, 2 (3%) were general practitioners, and 1 (1%) was a pediatrician. Thirty-two (41%) of this group of respondents were nonphysicians: 14 (18%) were nurse practitioners, 9 (12%) were nurses, 6 (8%) were physician assistants, 2 (3%) were medical students, and 1 (1%) was a nonmedical professional. All participants were tested on 14 clinically Important cardiac auscultatory events directly recorded from actual (not simulated) patients and transmitted via wireless Infrared stethophones. The auscultatory events tested were wide physiologic splitting of S2 in right bundle branch block, fixed S2 splitting and systolic murmur in atrial septal defect, midsystolic click and late systolic murmur of mitral valve prolapse, S4 gallop, S3 gallop, opening snap of mitral stenosis, innocent systolic murmur, systolic murmur of mitral regurgitation, systolic murmur of tricuspid regurgitation, systolic murmur of hypertrophic obstructive cardiomyopathy, continuous murmur of patent ductus arteriosus, pericardial friction rub, prosthetic valve sounds, and alternation of heart sounds, heart murmurs, and the S3 gallop in congestive heart failure. RESULTS: On the basis of the analysis of the 78 participants who completed preconference and postconference evaluations of the 14 selected cardiac auscultatory events, a preconference Identification score of 26.3% and a postconference score of 44.7% were observed. This represents a statistically significant overall Improvement in diagnostic proficiency (P < .001). CONCLUSIONS: Cardiac auscultatory skills among today's health care professionals are extremely poor, regardless of the level and/or type of training of the professional. An actual (not simulated) patient-centered teaching conference is an effective clinical method of improving cardiac auscultatory skills and diagnostic proficiency of health care professionals.

Computer-assisted detection of systolic murmurs associated with hypertrophic cardiomyopathy: a pilot study.

A pilot study was conducted to ascertain the level of agreement between auscultatory findings derived from heart sound recordings by a cardiologist and the results of a computer-based heart sound analysis algorithm. Heart sound recordings were obtained from volunteer subjects previously diagnosed with hypertrophic cardiomyopathy. Twenty-second recordings were obtained at each of 4 standard auscultatory locations on the precordium in 2 postures: standing and reclining. Detailed auscultatory findings were derived by a cardiologist, who listened to the heart sound recordings and was blinded to the study design. The recordings were analyzed by an algorithm that detects heart sounds and murmurs, and derives associated timing and energy parameters. The algorithm results were compared with the auscultatory findings provided by the cardiologist and correlated with the medical histories provided by the volunteer subjects. A high degree of concordance between the medical histories, auscultatory findings, and computer analyses was obtained. The 1st and 2nd heart sounds were detected with high sensitivity (90.7%) and positive predictivity (93.0%). Systolic murmurs were detected with a sensitivity that increased from 50% for grade 1 to 100% for grades 2-3 and 3. The signal energy in the mid-frequency range correlated well with murmur grade judgments, and also agreed well with the cardiologist's judgments of the relative loudness of murmurs in standing versus reclining postures. The computer analysis algorithm thus instantiates the objective detection and identification of apical systolic murmurs that are louder in standing than in reclining postures; such murmurs are a cardinal sign of hypertrophic obstructive cardiomyopathy.