Predicting pass rates on the American Board of Internal Medicine certifying examination.
Our objective was to determine the ability of the internal medicine In-Training Examination (ITE) to predict pass or fail outcomes on the American Board of Internal Medicine (ABIM) certifying examination and to develop an externally validated predictive model and a simple equation that can be used by residency directors to provide probability feedback for their residency programs. We collected a study sample of 155 internal medicine residents from the three Virginia internal medicine programs and a validation sample of 64 internal medicine residents from a residency program outside Virginia. Scores from both samples were collected across three class cohorts. The Kolmogorov-Smirnov z test indicated no statistically significant difference between the distribution of scores for the two samples (z = 1.284, p = .074). Results of the logistic model yielded a statistically significant prediction of ABIM pass or fail performance from ITE scores (Wald = 35.49, SE = 0.036, df = 1, p < .005) and overall correct classifications for the study sample and validation sample at 79% and 75%, respectively. The ITE is a useful tool in assessing the likelihood of a resident's passing or failing the ABIM certifying examination but is less predictive for residents who received ITE scores between 49 and 66.
University of Virginia School of Medicine, Charlottesville 22908, USA.
L K
LK
Rollins
J R
JR
Martindale
M
M
Edmond
T
T
Manser
W M
WM
Scheld
D007388:Internal Medicine; D016015:Logistic Models; D015233:Models, Statistical; D013044:Specialty Boards; D014481:United States