A randomized crossover trial of Quick Medical Reference (QMR) as a teaching tool for medical interns.
OBJECTIVE
To determine whether the addition of Quick Medical Reference (QMR) to usual educational tools improves an intern's performance in managing clinical cases that test diagnostic and investigative skills.


METHODS
Randomized, controlled, single-blinded crossover study.


METHODS
Tertiary care teaching hospital.


METHODS
Comprehensive medical interns who are proficient in the use of QMR.


METHODS
A total of 16 interns trained in the use of QMR were randomized to work up a total of six diagnostically challenging cases, three using medical textbooks plus access to QMR and three using textbooks and no access to QMR.


METHODS
The interns provided their solutions to the cases, which consisted of the differential diagnosis and investigations. They were scored by comparing their answers with the consensus answers provided by subspecialty consultants. For each intern, the difference in mean total scores with and without QMR was calculated.


RESULTS
The mean difference in total scores was 7.2% benefit (p < 0.05, 95% CI = 0.05 to 14.4) using QMR. The beneficial difference was driven mainly by improvement in diagnostic scores, with the mean difference being 11.6% (p = 0.01, 95% CI = 2.4 to 20.8). Regression analysis showed that the more difficult the case, the greater the benefit of QMR.


CONCLUSIONS
Quick Medical Reference may be a useful adjunct to interns in formulating diagnostic strategies for difficult clinical cases. However, since optimal conditions were chosen for QMR benefit in this study design, the small benefit in test scores must be weighed against the time required to teach QMR to interns.
Department of Medicine, University of Toronto, Ontario, Canada.
C M
CM
Bacchus
C
C
Quinton
K
K
O'Rourke
A S
AS
Detsky
D000328:Adult; D018592:Cross-Over Studies; D003661:Decision Support Techniques; D004503:Education, Medical, Graduate; D005260:Female; D006801:Humans; D007396:Internship and Residency; D008297:Male; D008490:Medical Informatics; D012044:Regression Analysis; D016037:Single-Blind Method