A traditionally administered short course failed to improve medical students' diagnostic performance. A quantitative evaluation of diagnostic thinking.

BACKGROUND: Quite often medical students or novice residents have difficulty in ruling out diseases even though they are quite unlikely and, due to this difficulty, such students and novice residents unnecessarily repeat laboratory or imaging tests. OBJECTIVE: To explore whether or not a carefully designed short training course teaching Bayesian probabilistic thinking improves the diagnostic ability of medical students. PARTICIPANTS AND METHODS: Ninety students at 2 medical schools were presented with clinical scenarios of coronary artery disease corresponding to high, low, and intermediate pretest probabilities. The students' estimates of test characteristics of exercise stress test, and pretest and posttest probability for each scenario were evaluated before and after the short course. RESULTS: The pretest probability estimates by the students, as well as their proficiency in applying Bayes's theorem, were improved in the high pretest probability scenario after the short course. However, estimates of pretest probability in the low pretest probability scenario, and their proficiency in applying Bayes's theorem in the intermediate and low pretest probability scenarios, showed essentially no improvement. CONCLUSION: A carefully designed, but traditionally administered, short course could not improve the students' abilities in estimating pretest probability in a low pretest probability setting, and subsequently students remained incompetent in ruling out disease. We need to develop educational methods that cultivate a well-balanced clinical sense to enable students to choose a suitable diagnostic strategy as needed in a clinical setting without being one-sided to the "rule-in conscious paradigm."

Quantitative evaluation of the diagnostic thinking process in medical students.

OBJECTIVE: To explore the diagnostic thinking process of medical students. SUBJECTS AND METHODS: Two hundred twenty-four medical students were presented with 3 clinical scenarios corresponding to high, low, and intermediate pre-test probability of coronary artery disease. Estimates of test characteristics of the exercise stress test, and pre-test and post-test probability for each scenario were elicited from the students (intuitive estimates) and from the literature (reference estimates). Post-test probabilities were calculated using Bayes' theorem based upon the intuitive estimates (Bayesian estimates of post-test probability) and upon the reference estimates (reference estimates of post-test probability). The differences between the reference estimates and the intuitive estimates, and between Bayesian estimates and the intuitive estimates were used for assessing knowledge of test characteristics, and ability of estimating pre-test and post-test probability of disease. RESULTS: Medical students could not rule out disease in low or intermediate pre-test probability settings, mainly because of poor pre-test estimates of disease probability. They were also easily confused by test results that differed from their anticipated results, probably because of their inaptitude in applying Bayes' theorem to real clinical situations. These diagnostic thinking patterns account for medical students or novice physicians repeating unnecessary examinations. CONCLUSIONS: Medical students' diagnostic ability may be enhanced by the following educational strategies: 1) emphasizing the importance of ruling out disease in clinical practice, 2) training in the estimation of pre-test disease probability based upon history and physical examination, and 3) incorporation of the Bayesian probabilistic thinking and its application to real clinical situations.