Development of a Competency-Based Radiology Clerkship Using Categorical and Statistical Analysis of Assessment.
J Am Coll Radiol
; 19(4): 567-575, 2022 04.
Article
in English
| MEDLINE | ID: covidwho-1676786
ABSTRACT
PURPOSE:
The purpose was to create and analyze a competency-based model of educating medical students in a radiology clerkship that can be used to guide curricular reform.METHODS:
During the 2019 to 2020 academic year, 326 fourth-year medical students were enrolled in a 2-week required clerkship. An online testing platform, ExamSoft (Dallas, Texas), was used to test pre- and postinstruction knowledge on "must see" diagnoses, as outlined in the National Medical Student Curriculum in Radiology. Assessment analysis was used to compare the frequency with which the correct diagnosis was identified on the pretest to that on the posttest. At the end of the academic year, in addition to statistical analysis, categorical analysis was used to classify the degree of this change to uncover topics that students found most challenging.RESULTS:
For 23 of the 27 topics (85%), there was a significant improvement in diagnostic accuracy after instruction in the test curriculum. Categorical analysis further demonstrated that the clerkship had a high impact in teaching 13 of the 27 topics (48%), had a lower impact for 6 topics (22%), and identified the remaining 8 topics (30%) as gaps in teaching and learning.CONCLUSIONS:
For medical students, our instructional program significantly increased competency for most critical radiologic diagnoses. Categorical analysis adds value beyond statistical analysis and allows dynamic tailoring of teaching to address gaps in student learning.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Radiology
/
Students, Medical
/
Clinical Clerkship
Type of study:
Diagnostic study
/
Experimental Studies
/
Prognostic study
Limits:
Humans
Country/Region as subject:
North America
Language:
English
Journal:
J Am Coll Radiol
Journal subject:
Radiology
Year:
2022
Document Type:
Article
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