Rashes and reflection: a novel curriculum using clinical reasoning to teach ambulatory dermatology to internal medicine residents
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Anne Richardson
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Katherine Gavinski
Abstract
Objectives
Internists do not feel competent in diagnosing and treating common dermatologic conditions. Teaching clinical reasoning principles in graduate medical education can improve trainees’ diagnostic accuracy, but previously published dermatology curricula did not emphasize these skills. We developed a novel curriculum applying clinical reasoning concepts to teach internal medicine (IM) residents how to describe dermatologic lesions, develop differential diagnoses, and use deliberate reflection to improve diagnostic accuracy for four common dermatologic complaints.
Methods
Five asynchronous, interactive 10-min online modules were developed and administered to all 152 IM residents at a large academic residency program in 2023. Residents were evaluated for their ability to describe dermatologic lesions, their diagnostic accuracy, and their deliberate reflection skills. Residents completed this novel assessment before, immediately after, and four months after the curriculum. Linear mixed effects regression models were used to assess changes in assessment scores over time.
Results
One hundred eleven of 152 residents (73 %) participated in the study. Total assessment scores improved between pre-test and post-test (mean difference 0.98, 95 % CI [0.32, 1.64], p=0.004), but not between pre-test and delayed post-test. Residents who completed 4 or 5 modules improved from pre-test to post-test in the description component (mean difference 0.46, 95 % CI [0.01, 0.91], p=0.043) and the final diagnosis/treatment component (mean difference 0.69, 95 % CI [0.22, 1.17] p=0.004), but not the deliberate reflection component.
Conclusions
An interactive, asynchronous clinical reasoning-based dermatology curriculum can improve IM resident knowledge of common dermatologic complaints, particularly immediately after participation and if most modules are completed.
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Research ethics: The local Institutional Review Board reviewed and determined the above referenced study meets the regulatory requirements for exempt research under 45 CFR 46.104(d)(1).
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Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/dx-2025-0076).
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