Teaching Benign Skin Lesions as a Strategy to Improve the Triage Amalgamated Dermoscopic Algorithm (TADA).

Document Type

Article

Publication Date

1-1-2019

Institution/Department

Dermatology

Journal Title

J Am Board Fam Med

MeSH Headings

Algorithms, Clinical Competence, Cross-Sectional Studies, Dermoscopy, Diagnosis, Differential, Female, Heuristics, Humans, Keratosis, Seborrheic, Lentigo, Male, Physicians, Family, Program Evaluation, Quality Improvement, Simulation Training, Skin, Skin Neoplasms, Teaching, Triage

Abstract

INTRODUCTION: Dermoscopy aids family physicians (FPs) in skin cancer detection. The triage amalgamated dermoscopic algorithm (TADA) was created to simplify the dermoscopic evaluation of a skin growth. The purpose of this image-based study was to evaluate the effect of teaching the clinical and dermoscopic features of benign skin lesions on the diagnostic accuracy of skin cancer identification using TADA. We also sought to determine the best method to teach benign neoplasms.

METHODS: In this cross-sectional study of an educational intervention, FPs participated in dermoscopy training. Participants were divided into 3 groups for teaching of common benign neoplasms (dermatofibroma, angioma, and seborrheic keratosis/lentigo): didactic + interactive, didactic + heuristic, and didactic. For each group, the benign teaching was followed by skin cancer identification training with TADA. All participants took a 30 image pre-test and 30 image post-test.

RESULTS: Fifty-nine participants completed the study. The mean preintervention score (out of 30 correct responses) was 17.9 (SD, 4.5) and increased to 23.5 (SD, 3.0) on the postintervention evaluation (

CONCLUSION: Short dermoscopy training sessions with dedicated time for benign growths followed by TADA training for malignant growths are an effective means of teaching FPs dermoscopy and result in a high sensitivity and specificity for the identification of benign and malignant skin neoplasms.

ISSN

1558-7118

First Page

96

Last Page

102

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