BMJ Open (Aug 2023)

Diagnostic reliability in teledermatology: a systematic review and a meta-analysis

  • Adrienn N Bourkas,
  • Natasha Barone,
  • Matthew E C Bourkas,
  • Matthew Mannarino,
  • Robert D J Fraser,
  • Amy Lorincz,
  • Sheila C Wang,
  • Jose Luis Ramirez-GarciaLuna

DOI
https://doi.org/10.1136/bmjopen-2022-068207
Journal volume & issue
Vol. 13, no. 8

Abstract

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Objectives To compare teledermatology and face-to-face (F2F) agreement in primary diagnoses of dermatological conditions.Design Systematic review and meta-analysisMethods MEDLINE, Embase, Cochrane Library (Wiley), CINAHL and medRxiv were searched between January 2010 and May 2022. Observational studies and randomised clinical trials that reported percentage agreement or kappa concordance for primary diagnoses between teledermatology and F2F physicians were included. Titles, abstracts and full-text articles were screened in duplicate. From 7173 citations, 44 articles were included. A random-effects meta-analysis was conducted to estimate pooled estimates. Primary outcome measures were mean percentage and kappa concordance for assessing diagnostic matches between teledermatology and F2F physicians. Secondary outcome measures included the agreement between teledermatologists, F2F dermatologists, and teledermatology and histopathology results.Results 44 studies were extracted and reviewed. The pooled agreement rate was 68.9%, and kappa concordance was 0.67. When dermatologists conducted F2F and teledermatology consults, the overall diagnostic agreement was significantly higher at 71% compared with 44% for non-specialists. Kappa concordance was 0.69 for teledermatologist versus specialist and 0.52 for non-specialists. Higher diagnostic agreements were also noted with image acquisition training and digital photography. The agreement rate was 76.4% between teledermatologists, 82.4% between F2F physicians and 55.7% between teledermatology and histopathology.Conclusions and relevance Teledermatology can be an attractive option particularly in resource-poor settings. Future efforts should be placed on incorporating image acquisition training and access to high-quality imaging technologies.Trial registration number 10.17605/OSF.IO/FJDVG