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Training pattern recognition of skin lesion morphology, configuration, and distribution - 15/02/15

Doi : 10.1016/j.jaad.2014.11.016 
Lauren Rimoin, MD a, Lisa Altieri, BA b, Noah Craft, MD, PhD c, d, e, f, Sally Krasne, PhD g, ⁎ , Philip J. Kellman, PhD h, i
a Department of Dermatology, Emory University School of Medicine, Atlanta, Georgia 
b David Geffen School of Medicine, University of California, Los Angeles, California 
c Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 
d Olive View-UCLA Medical Center, Sylmar, California 
e Science 37, Inc, Los Angeles, California 
f Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California 
g Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, California 
h Department of Psychology, University of California, Los Angeles, California 
i Insight Learning Technology Inc, Santa Monica 

∗Correspondence to: Sally Krasne, PhD, Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095-1751.

Abstract

Background

The ability to reliably recognize and classify a range of skin signs and symptoms remains a necessary skill across most clinical disciplines but one that is traditionally mastered via nonsystematic experience over long periods.

Objective

We investigated whether online Perceptual and Adaptive Learning Modules (PALMs) could efficiently train preclerkship medical students to identify and discriminate primary skin lesion morphologies, configurations, and anatomic distributions.

Methods

Medical students completed an online skin lesion morphology PALM voluntarily in year 1 and by requirement, along with configuration and anatomic distribution PALMs, in year 2. In controlled before-and-after studies, multiple-choice pretests and posttests using previously unused images, assessed PALM-induced learning. In prospective cohort studies, differences in year-2 performance between students who had and had not completed the morphology PALM in year 1 were also assessed.

Results

Multiple-choice tests, used to evaluate PALM effectiveness, demonstrated large (effect sizes of 1.1 [±0.1 SE] to 2.2 [±0.1 SE]) and statistically significant (P < .0001) improvements after PALM training, with learning retention when tested after 1 year.

Limitations

Results are from self-selected groups and a single class at 1 institution.

Conclusion

PALMs are a useful tool for efficient development of the core clinical skills of pattern recognition and classification of skin lesion characteristics.

Il testo completo di questo articolo è disponibile in PDF.

Key words : adaptive learning, dermatology, diagnosis, experiential learning, lesion configuration, lesion distribution, lesion morphology, pattern recognition, perceptual learning, skin lesions


Mappa


 Dr Rimoin and Ms Altieri contributed equally to this article.
 A research grant (principal investigators: Sally Krasne, PhD, and Sarah Kim, PhD) from the Institute for Innovative Technology in Medical Education provided support for this project.
 Disclosure: Dr Craft is a consultant to Logical Images Inc, Rochester, NY, the makers of VisualDx.com and learnderm.org, with approved and pending patents on the use of images and visual knowledge to assist in the diagnostic process. Dr Kellman is the president of Insight Learning Technology Inc, with approved and pending patents on adaptive and perceptual learning technologies. Dr Rimoin, Ms Altieri, and Dr Krasne have no conflicts of interest to declare.
 Reprints not available from the authors.


© 2014  American Academy of Dermatology, Inc.. Pubblicato da Elsevier Masson SAS. Tutti i diritti riservati.
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