Head to head comparison between neurology residents and a mobile medical application for diagnostic accuracy in cognitive neurology

Abstract

Background: A novel Mobile Medical Application (App) App was created on iOS platform (Neurology Dx®) to deduce Differential Diagnoses (DDx) from a set of user selected Symptoms, Signs, Imaging data and Lab findings. The DDx generated by the App was compared for diagnostic accuracy with differentials reasoned by participating neurology residents when presented with same clinical vignettes. Methods: Hundred neurology residents in seven leading Neurology centers across India participated in this study. A panel of experts created 60 clinical vignettes of varying levels of difficulty related to Cognitive neurology. Each neurology resident was instructed to formulate DDx from a set of 15 cognitive neurology vignettes. Experts in Cognitive Neurology made the gold standard DDx answers to all 60 clinical vignettes. The differentials generated by the App and neurology residents were then compared with the Gold standard. Results: Sixty clinical vignettes were tested on 100 neurology residents (15 vignettes each) and also on the App (60 vignettes). The frequency of gold standard high likely answers accurately documented by the residents was 25% compared with 65% by the App (95% CI 33.1-46.3), P < 0.0001. Residents correctly identified the first high likely gold standard answer as their first high likely answer in 35% (95% CI 30.7-36.6) compared with 62% (95% CI 14.1-38.5), P < 0.0001. Conclusion: An App with adequate knowledge-base and appropriate algorithm can augment and complement human diagnostic reasoning in drawing a comprehensive list of DDx in the field of Cognitive Neurology (CTRI/2017/06/008838).