Healthcare professionals are benefitting from the launch of a new app, developed by the University of Edinburgh, United Kingdom, to help them learn to assess and detect skin cancer at an early stage and reduce unnecessary specialist referrals.
The new app, called Dermofit, has been designed to help train non-specialist doctors, nurses, and medical students to more accurately identify different skin lesions and growths along with their related diagnoses, using interactive, cognitive training techniques and an extensive image reference library.
Launched earlier this month, Dermofit is already in use in a range of medical training settings around the world, helping healthcare professionals develop a greater knowledge of the variety of visual characteristics that different skin lesions have, and the way that these can be used to determine benign cases from more serious examples of skin cancer.
Dermofit was first devised by Prof. Jonathan Rees, grant chair of dermatology at the University of Edinburgh, who came up with the idea to develop a digital tool to help medical professionals accurately identify malignant and benign skin lesion and skin growths at an early stage.
The result of 4 years of research and development by the University of Edinburgh, Dermofit provides trainee doctors, nurses, and other non-specialist healthcare professionals with digital resources that allow them to hone their ability to correctly identify specific skin lesion types and, as a result, improve the accuracy with which they can determine skin cancer diagnoses.
In the case of suspected skin cancers – including malignant melanoma, squamous cell carcinoma, or basal cell carcinoma – the need for prompt referral to a specialist for assessment and treatment is essential. However, in many cases, these referrals are often unnecessary.
“Thirty percent of doctors will automatically send a patient to a hospital if they have signs of a skin growth,” says Prof. Rees. “But the evidence is that the vast majority of people who are seen and referred do not have skin cancer or anything serious at all.”
Resources that can equip non-specialist care practitioners with the skills necessary to more accurately identify these different types of skin growth and lesion can therefore be extremely valuable, in terms of improving the quality of care provided to patients and also reducing costs for care providers.
Dermofit uses algorithms that automatically groups library photos of skin lesions based on their color and texture properties.
Selecting from a library of more than 1,300 images, the Dermofit app will take the user to further sets of similar lesion types to illustrate the difference in lesions that may look similar but are from different skin lesion classes. Other modules allow users to further build and test their skills of identification and diagnosis.
Bob Fisher, who specializes in computer vision and helped design the computer algorithms for the app, adds: “Dermofit contains a photo library of skin lesions to help inform practitioners to diagnosis more effectively.”
Practitioners can click on the image of a lesion of interest which then leads to further similar lesions. As lesions are selected, further sets of similar lesions are displayed. This gives familiarity with the different skin lesion types and allows users to differentiate between lesions that look similar, but that are from different skin lesion classes,” he says.
The use of cognitive teaching tools is a rapidly growing area of medical training, as it allows healthcare professionals to develop the necessary skills that are required to more accurately diagnose and treat patients within risk-free digital environments.
Providing healthcare practitioners with training tools like Dermofit helps them acquire skills that would otherwise require years of practical experience.
Simedics, a U.K.-based company specializing in digital products and publishing for the healthcare industry, is the commercial partner responsible for bringing Dermofit to market. They hope that the product will become instrumental in providing an effective way to train medical students and primary care practitioners in this area and, as a result, help improve skin cancer detection rates and patient care.
The company is already working with teaching hospitals, universities, and organizations around the world to incorporate Dermofit into teaching regimens.
More information on the Dermofit project is available at dermofit.org.
Dermofit is available on iOS and can be downloaded from the App Store.