Medical College of Wisconsin
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Predictors of performance on the Maintenance of Certification in Anesthesiology Program® (MOCA®) examination. J Clin Anesth 2015 Feb;27(1):1-6

Date

12/04/2014

Pubmed ID

25468588

DOI

10.1016/j.jclinane.2014.08.007

Scopus ID

2-s2.0-84923254238 (requires institutional sign-in at Scopus site)   14 Citations

Abstract

STUDY OBJECTIVE: The aim of this study was to determine the independent factors associated with performance on the Maintenance of Certification in Anesthesiology Program (MOCA) examination.

DESIGN: Cross-sectional study.

SETTING: The American Board of Anesthesiology, Raleigh, NC.

SUBJECTS: The American Board of Anesthesiology (ABA) diplomates who were certified between 2000 and 2006 and had taken the MOCA examination at least once by July 2013.

MEASUREMENTS: MOCA examination score for the first attempt.

MAIN RESULTS: Independent positive predictors for MOCA examination score in multiple regression analysis included passing the ABA Part 1 and Part 2 certification examinations on the first attempt and male sex, whereas negative predictors included history of action(s) taken against any medical license, taking the examination later in the MOCA cycle and older age at primary certification.

CONCLUSIONS: Several factors in addition to performance on the written examination for primary certification (Part 1 Examination) are independently associated with performance on the MOCA examination. Because many of these factors are not modifiable, those diplomates who possess unfavorable risk factors should pay special attention to engaging in continuing learning to prepare for the MOCA examination.

Author List

Sun H, Culley DJ, Lien CA, Kitchener DL, Harman AE, Warner DO

Author

Cynthia A. Lien MD Chair, Professor in the Anesthesiology department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Adult
Anesthesiology
Certification
Clinical Competence
Cross-Sectional Studies
Educational Measurement
Female
Humans
Male
Middle Aged
Regression Analysis