ArticleJMIR dermatology2025
Diagnostic Accuracy, Implementation Barriers, and Equity Implications of Teledermatology in Rural Skin Cancer: Scoping Review.
Article in JMIR dermatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Assessing Telemedicine Implementation Potential in High-Referral Specialties: A Cross-Sectional Study in Iran.Health science reports · 2026Article
- Cutaneous Squamous Cell Carcinoma Across the Pre-COVID-19, COVID-19 and Post-COVID-19 Eras: Epidemiology, Risk Stratification, Tumour Aggressiveness, and Clinical Outcomes.Dermatopathology (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Skin cancer is the most commonly diagnosed malignancy in the United States, with rural populations facing disproportionate delays in diagnosis due to geographic isolation, workforce shortages, and limited access to dermatologic care. These delays contribute to higher rates of late-stage diagnosis and poorer outcomes. Teledermatology has emerged as a promising solution to expand access to dermatologic evaluation and treatment in underserved settings. Objective: The review aims to evaluate the diagnostic performance, implementation challenges, and equity considerations of teledermatology in the context of rural skin cancer care, and to assess its potential to improve clinical outcomes in underserved populations. Methods: A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and Google Scholar to identify studies published between January 2015 and March 2025. Search terms included "teledermatology," "skin cancer," "rural health services," "telemedicine," "diagnostic accuracy," and "health disparities." Studies evaluating diagnostic metrics, time to diagnosis, patient satisfaction, and implementation barriers were included. Results: Nine key studies spanning various countries and health care settings were included. Diagnostic sensitivity ranged from 41.9% to 100%, and specificity from 46% to 90%, depending on modality and lesion type. Teledermatology consistently reduced time to diagnosis, in some cases by over 75%, and was associated with high patient satisfaction due to increased convenience and reduced travel. Key barriers included technological limitations, inconsistent imaging protocols, and reimbursement variability. Successful implementation was facilitated by standardized workflows, dermoscopy integration, and centralized platforms. Conclusions: Teledermatology is a viable and effective approach to addressing disparities in rural skin cancer care. It offers diagnostic accuracy comparable to face-to-face evaluations while reducing wait times and improving patient satisfaction. Overcoming technological and systemic barriers is critical to ensuring equitable, long-term integration of teledermatology in rural health systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.