Dermoscopy Training to Improve Early Melanoma Detection in Rural Maine
Asghar Shah
Vinny Seiverling
Medical Student Award
Warren Alpert Medical School of Brown University
Asghar Shah’s Abstract
Melanoma is a serious form of skin cancer that is much easier to treat when found early. However, in many parts of rural Maine, people live far from dermatologists, making early detection difficult. Most skin checks in these areas are done by family medicine doctors and nurse practitioners, but they often do not have access to the same tools or training used by skin specialists. One of these tools, called a dermatoscope, is a hand-held 10x magnifier that helps clinicians see important patterns on the skin that can help tell the difference between dangerous and harmless moles. This project will bring hands-on training in dermoscopy, the use of the dermatoscope, to a rural Maine county. The program builds on a successful pilot conducted in Rockport, Maine, where providers joined dermatologists for a one-hour “Lunch and Learn” session that combined short lessons, case examples, and hands-on practice. After the session, the clinicians took part in a free community skin cancer screening, where they worked alongside dermatologists to apply their new skills in real time. That experience identified nine suspected skin cancers and five precancerous spots among 36 patients screened.
The new program will adapt this model for another high-need Maine community, chosen based on melanoma rates and access. The training will include a simple, step-by-step method called the Triage Amalgamated Dermoscopy Algorithm (TADA). Family medicine providers will complete surveys before and after the training to measure their confidence and ability. They will be encouraged to continue using dermoscopy in the months after the event. By providing focused, practical education and access to dermoscopy, this project aims to make early melanoma detection more achievable in parts of Maine with limited specialty care. Participants are expected to report greater confidence and satisfaction with this interactive learning model. The goal is to help rural clinicians identify melanoma earlier.