English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

PURPOSE With increasing delays in obtaining a dermatological consultation, general practitioners (GPs) are using social networks for telemedicine to obtain advice on dermatological images. The objective was to analyze diagnostic agreement between telemedicine on social networks (Twitter and MedPics) and standard teledermatology services (TDS). METHODS This retrospective observational study included images published on Twitter and MedPics by GPs in 2016. The contextualized images were evaluated by 2 teledermatology services in Paris, France and an expert committee. Diagnoses obtained from telemedicine on social networks, TDS, and the expert committee were collected for each image. The agreement between the diagnoses made on social networks and by TDS was measured using Cohen κ statistic. The number of correct diagnoses obtained using social networks and TDS as determined by agreement with the expert’s diagnoses were compared with χ2 tests. RESULTS Two hundred and seventy health professionals responded to the 60 selected images from social networks. The main diagnoses, according to the experts were: purpura (8.3%), eczema (6.7%), mycosis (6.7%), and viral infections (6.7%). Diagnostic agreement between telemedicine on social networks and TDS was moderate over the entire set of images (κ = 0.55; 95% CI, 0.42-0.68) and good for images containing dermatologist’s answers (κ = 0.63; 95% CI, 0.45-0.85). The number of correct diagnoses was not statistically different between telemedicine on social networks and TDS on all images (60% vs 55%; P = .28) but was higher on social networks when a dermatologist answered (65% vs 55%; P <.01). CONCLUSIONS Diagnostic agreement using social network images showed that use of this telemedicine tool could be a reliable means to alleviate the difficulties of accessing dermatology consultations although data safety probably needs to be improved.

Diagnostic Agreement Between Telemedicine on Social Networks and Teledermatology Centers