An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography
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Kara Gaetke-Udager1,2, Zachary N London3,4, Sean Woolen5
1Assistant Professor, Department of Radiology, University of Michigan Medical School.
Introduction:
New radiology and other residents must quickly assimilate a vast amount of anatomic and pathologic information when learning to interpret noncontrast head computed tomography (CT). No interactive, computer-based module using a search-pattern approach to provide new residents with the groundwork for interpretation of noncontrast head CT previously existed.
Methods:
We developed such a learning module using PowerPoint. First-year radiology residents completed the module prior to their neuroradiology rotation, and neurology residents completed it during orientation. Residents took 20-question pre- and posttests to assess knowledge and a postmodule survey. Each resident was randomized to one of two pretests and took the opposite as the posttest. Scores were collected over 5 years for radiology residents and 4 years for neurology residents. Statistical analysis of scores was performed using t tests.
Results:
Forty-seven first-year radiology residents and 31 neurology residents completed the module and the pre- and posttests. Scores for all residents either stayed the same or increased, regardless of the order of the versions of the pre- or posttests; the mean score increase was 4 (p < .0001) out of 20. Radiology residents had higher mean scores than neurology residents on the pre- and posttests, which were statistically significant (p < .04 and .0004, respectively). Feedback on the survey was overwhelmingly positive.
Discussion:
This computerized learning module is effective for teaching basic interpretation skills to new radiology and neurology residents. The module allows for asynchronous, programmed learning and the use of a step-by-step search-pattern approach.
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