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Title: Predicting success on the certification examinations of the American Board of Anesthesiology. Author: McClintock JC, Gravlee GP. Journal: Anesthesiology; 2010 Jan; 112(1):212-9. PubMed ID: 20010419. Abstract: BACKGROUND: Currently, residency programs lack objective predictors for passing the sequenced American Board of Anesthesiology (ABA) certification examinations on the first attempt. Our hypothesis was that performance on the ABA/American Society of Anesthesiologists In-Training Examination (ITE) and other variables can predict combined success on the ABA Part 1 and Part 2 examinations. METHOD: The authors studied 2,458 subjects who took the ITE immediately after completing the first year of clinical anesthesia training and took the ABA Part 1 examination for primary certification immediately after completing residency training 2 yr later. ITE scores and other variables were used to predict which residents would complete the certification process (passing the ABA Part 1 and Part 2 examinations) in the shortest possible time after graduation. RESULTS: ITE scores alone accounted for most of the explained variation in the desired outcome of certification in the shortest possible time. In addition, almost half of the observed variation and most of the explained variance in ABA Part 1 scores was accounted for by ITE scores. A combined model using ITE scores, residency program accreditation cycle length, country of medical school, and gender best predicted which residents would complete the certification examinations in the shortest possible time. CONCLUSIONS: The principal implication of this study is that higher ABA/ American Society of Anesthesiologists ITE scores taken at the end of the first clinical anesthesia year serve as a significant and moderately strong predictor of high performance on the ABA Part 1 (written) examination, and a significant predictor of success in completing both the Part 1 and Part 2 examinations within the calendar year after the year of graduation from residency. Future studies may identify other predictors, and it would be helpful to identify factors that predict clinical performance as well.[Abstract] [Full Text] [Related] [New Search]