Diagnostic Agreement Between Telemedicine on Social Networks and Teledermatology Centers

Sophia Serhrouchni; Alexandre Malmartel


Ann Fam Med. 2021;19(1):24-29. 

In This Article


Characteristics and Diagnoses

This study collected the responses of 270 health care professionals on social networks concerning 60 images: 39 images on Twitter and 21 on MedPics (Figure 1). Responses analyzed that contributed to social network diagnoses were submitted by 178 graduate doctors including 124 GPs and 25 dermatologists. A dermatologist response was present for 23 images (38.2%).

The most frequent diagnosis from social networks was mycosis (10.0%), from TDS was eczema (11.7%), and from the expert committee was purpura (8.3%). Viruses and viral rashes were among the 4 most frequent diagnoses in each group of evaluators (Table 1; Supplemental Table 1, available at https://www.AnnFamMed.org/content/19/1/24/suppl/DC1/). There was a recommendation for dermatologic consultation for 15 of the images (25.0%).

Diagnostic Agreement

According to Altman's classification,[12] the diagnostic agreement between social network diagnoses and TDS diagnoses was moderate for all images and on images from Twitter and MedPics. The agreement was good when a dermatologist's response was present on social networks but moderate when no dermatologist answered (Table 2).

Diagnostic agreement between social networks and the expert committee was moderate for all images and the Twitter images. It was good when a dermatologist answered in the social networks and in the MedPics images. In the absence of a dermatologist response, agreement was moderate (Table 2).

Correct Diagnoses

Based on the reference diagnoses made by the expert committee, 36 diagnoses (60%) were correct on Twitter and MedPics and 33 diagnoses (55%) were correct for TDS. There was no significant difference between the number of correct diagnoses made on social networks (Twitter and MedPics) and by TDS when all images were analyzed (P = .29).

The presence of a dermatologist response on Twitter and MedPics increased the probability of a correct diagnosis (65% vs 55%; P <.01), but no difference was found when analyzing the images without dermatologist responses (58% vs 65%; P = .8).