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BACKGROUND: Skin cancer diagnostics is challenging, and mastery requires extended periods of dedicated practice. OBJECTIVE: The aim of the study was to determine if self-paced pattern recognition training in skin cancer diagnostics with clinical and dermoscopic images of skin lesions using a large-scale interactive image repository (LIIR) with patient cases improves primary care physicians' (PCPs') diagnostic skills and confidence. METHODS: A total of 115 PCPs were randomized (allocation ratio 3:1) to receive or not receive self-paced pattern recognition training in skin cancer diagnostics using an LIIR with patient cases through a quiz-based smartphone app during an 8-day period. The participants' ability to diagnose skin cancer was evaluated using a 12-item multiple-choice questionnaire prior to and 8 days after the educational intervention period. Their thoughts on the use of dermoscopy were assessed using a study-specific questionnaire. A learning curve was calculated through the analysis of data from the mobile app. RESULTS: On average, participants in the intervention group spent 2 hours 26 minutes quizzing digital patient cases and 41 minutes reading the educational material. They had an average preintervention multiple choice questionnaire score of 52.0% of correct answers, which increased to 66.4% on the postintervention test; a statistically significant improvement of 14.3 percentage points (P<.001; 95% CI 9.8-18.9) with intention-to-treat analysis. Analysis of participants who received the intervention as per protocol (500 patient cases in 8 days) showed an average increase of 16.7 percentage points (P<.001; 95% CI 11.3-22.0) from 53.9% to 70.5%. Their overall ability to correctly recognize malignant lesions in the LIIR patient cases improved over the intervention period by 6.6 percentage points from 67.1% (95% CI 65.2-69.3) to 73.7% (95% CI 72.5-75.0) and their ability to set the correct diagnosis improved by 10.5 percentage points from 42.5% (95% CI 40.2%-44.8%) to 53.0% (95% CI 51.3-54.9). The diagnostic confidence of participants in the intervention group increased on a scale from 1 to 4 by 32.9% from 1.6 to 2.1 (P<.001). Participants in the control group did not increase their postintervention score or their diagnostic confidence during the same period. CONCLUSIONS: Self-paced pattern recognition training in skin cancer diagnostics through the use of a digital LIIR with patient cases delivered by a quiz-based mobile app improves the diagnostic accuracy of PCPs. TRIAL REGISTRATION: ClinicalTrials.gov NCT05661370; https://classic.clinicaltrials.gov/ct2/show/NCT05661370.
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Purpose of Review: This scoping review maps recent literature on dermatology provider-to-provider asynchronous store-and-forward (SAF) electronic consult (eConsult) platforms with dermoscopy. It offers a descriptive overview, highlighting benefits and challenges. Recent Findings: Incorporating dermoscopy into SAF eConsults improves diagnostic accuracy for benign and malignant skin neoplasms. Diagnostic and treatment concordance with traditional face-to-face (FTF) visits is high. SAF eConsults with dermoscopy enhance access to dermatological care by improving triage and reducing wait times for FTF visits. Pediatric patients benefit with improved evaluation of melanocytic and vascular growths. eConsult platforms with dermoscopy serve as a telementoring opportunity for clinicians interested in improving their dermoscopy skills. Summary: Adding dermoscopy to SAF eConsults is valuable and results in improved diagnostic accuracy and reduced need for FTF visits. Implementation barriers can be overcome through collaboration between primary care and dermatology. Dermoscopy in SAF eConsults has significant potential for managing skin conditions and reducing the burden caused by unnecessary FTF visit and biopsies.
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Differentiating between benign and malignant skin lesions can be very difficult and should only be done by sufficiently trained and skilled clinicians. To our knowledge there are no validated tests for reliable assessments of clinicians' ability to perform skin cancer diagnostics. To develop and gather validity evidence for a test in skin cancer diagnostics, a multiple-choice questionnaire (MCQ) was developed based on informal interviews with seven content experts from five skin cancer centers in Denmark. Validity evidence for the test was gathered from May until July 2019 using Messick's validity framework (content, response process, internal structure, relationship to other variables and consequences). Item content was revised through a Delphi-like review process and then piloted on 36 medical students and 136 doctors using a standardized response process. Results enabled an analysis of the internal structure and relationship to other variables of the test. Finally, the contrasting groups method was used to investigate the test's consequences (pass-fail standard). The initial 90-item MCQ was reduced to 40 items during the Delphi-like review process. Item analysis revealed that 25 of the 40 selected items were level I-III quality items with a high internal consistency (Cronbach's α = 0.83) and highly significant (P ≤ 0.0001) differences in test scores between participants with different occupations or levels of experience. A pass-fail standard of 12 (48%) correct answers was established using the contrasting groups' method. The skin cancer diagnostics MCQ developed in this study can be used for reliable assessments of clinicians' competencies.