Teledermatology for the Diagnosis and Management of Skin Cancer: A Systematic Review
Open accessAbstract
Importance: As technology becomes more commonplace in dermatological practice, it is essential to continuously review the accuracy of teledermatology devices and services compared with in-person care. The last systematic review was conducted over 5 years ago. Objective: To synthesize and assess the quality of the evidence to address 3 research questions: (1) How accurate is teledermatology for skin cancer diagnosis compared with usual care (face-to-face [FTF] diagnosis)? (2) Does teledermatology save clinician and/or patient time, compared with usual care? (3) What are the enablers and barriers to adoption of teledermatology in clinical practice for the diagnosis of skin cancer? Evidence Review: The review protocol was registered in the PROSPERO database. Six databases (Cochrane, PubMed, Medline, Science Direct, Embase, and Web of Science) were searched for studies investigating the diagnostic accuracy and concordance, management accuracy and concordance, measures of time (waiting times, delay to diagnosis), and enablers and barriers to implementation. Potentially eligible articles were screened by 2 reviewers. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was used to evaluate the risk of bias and applicability of individual studies assessing diagnostic accuracy. Findings: Twenty-one studies were reviewed. The diagnostic accuracy (defined as agreement with histopathology for excised lesions or clinical diagnosis for nonexcised lesions) of FTF dermatology consultation remains higher (67%-85% agreement with reference standard, Cohen κ, 0.90) when compared with teledermatology (51%-85% agreement with reference standard, κ, 0.41-0.63), for the diagnosis of skin cancer. However, some studies do report high accuracy of teledermatology diagnoses. Most studies of diagnostic accuracy and concordance had significant methodological limitations. Studies of health service outcomes found teledermatology reduced waiting times and could result in earlier assessment and treatment. Patients reported high satisfaction and were willing to pay out of pocket for access to such services. Conclusions and Relevance: Robust implementation studies of teledermatology are needed, paying careful attention to reducing risk of bias when assessing diagnostic accuracy. Teledermatology services consistently reduced waiting times to assessment and diagnosis, and patient satisfaction was high.
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There is significant variability in diagnostic accuracy across pre-pandemic research on teledermatology.
“There is valid concern over the reliability of teledermatology given the significant variability in diagnostic accuracy predicted across pre-pandemic research.6”
From Diagnostic reliability in teledermatology: a systematic review and a meta-analysis (2023) · cites this paper as [6]
The date cut-off of 2010 means the dataset has little overlap with existing reviews and more heavily features new relevant technologies like smartphone apps for image acquisition.
“Our date cut-off of 2010 means our dataset has little overlap with existing reviews, and more heavily features new relevant technologies like smartphone apps for image acquisition.6 57”
From Diagnostic reliability in teledermatology: a systematic review and a meta-analysis (2023) · cites this paper as [6]
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Part II: Accuracy of Teledermatology in Skin Neoplasms
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Inpatient eDermatology (Teledermatology) Can Help Meet the Demand for Inpatient Skin Disease
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From diagnosis to intervention: a review of telemedicine’s role in skin cancer care
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- Authors
- Finnane, A., Dallest, K., Janda, M., & Soyer, H. P.
- Affiliations
- Translational Research Institute (AU)
- The University of Queensland (AU)
- Queensland University of Technology (AU)
- Venue
- JAMA Dermatology
- Publisher
- American Medical Association (AMA)
- Published
- 2017-03-01
- Volume
- 153
- Issue
- 3
- Pages
- 319
- ISSN
- 2168-6068 (ISSN-L)
- OpenAlex
- W2560712575
- Cited by
- 257
- References
- 40
- Citations by year
- 2026: 24 · 2025: 24 · 2024: 25 · 2023: 38 · 2022: 29 · 2021: 35 · 2020: 38 · 2019: 18 · 2018: 19 · 2017: 7
- FWCI
- 1.48
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Dermatology (publishedVersion)
- PubMed (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- Funders
- National Health and Medical Research Council (1045247)
- Topics
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- teledermatology, skin cancer diagnosis, diagnostic accuracy, telemedicine, waiting time, patient satisfaction, barriers to adoption, clinical implementation, delayed diagnosis
- MeSH terms
- Dermatology, Diagnostic Errors, Humans, Outcome and Process Assessment, Health Care, Skin Neoplasms, Time Factors, Patient Satisfaction, Telemedicine
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