An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography - Kara Gaetke-Udager; Zachary N London; Sean Woolen; Hemant Parmar; Janet E. Bailey; Daniel C. Barr (Association of American Medical Colleges, 2018)
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.