Predicting pass rates on the American Board of Internal Medicine certifying examination

J Gen Intern Med. 1998 Jun;13(6):414-6. doi: 10.1046/j.1525-1497.1998.00122.x.

Abstract

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.

MeSH terms

  • Internal Medicine*
  • Logistic Models
  • Models, Statistical
  • Specialty Boards*
  • United States