Mobile Health Technology can Remotely Screen Traumatic-Dental-Injuries With Adequate Accuracy

Objectives: Traumatic dental injury (TDI) is an important issue in dentistry. Appropriate assessments and diagnoses by emergency health professionals can improve the treatment outcome of TDIs. This preliminary study aimed to evaluate the validity and reliability of the photographic assessment of TDIs by trained oral health professionals.
Methods: An image acquisition app was developed to facilitate the acquisition and transferal of dental images. Prior to data collection, ethics approval was obtained from the University of Minnesota Institutional Review Board. One hundred and eight participants aged 7 to 77 years were recruited at a large state fair event. Each participant’s teeth were photographed by a trained assistant using a smartphone camera (Galaxy S20 FE 5G, Samsung, Seoul, South Korea). The images were directly uploaded from the app to a data management system (Remote-I, CSIRO, Canberra, Australia), and then remotely reviewed by five independent reviewers including a dental consultant, two general dentists, and two dental therapists. The TDI diagnoses by the latter four oral health professionals were compared with that of the dental consultant in order to evaluate the performance of the mobile health (mHealth) approach.
Results: A total of 1,404 teeth were reviewed. The prevalence of incomplete crown fracture and complete crown fracture was 41.7% and 1.2%, respectively. The sensitivity of TDI diagnosis by dental images ranged from 75% to 94%, indicating acceptable to excellent levels of diagnostic sensitivity. The specificity of TDI diagnosis ranged from 60% to 82%, indicating moderate to acceptable levels of diagnostic specificity. The Cohen's kappa coefficient ranged from 0.28 to 0.57, indicating moderate levels of inter-rater reliability.
Conclusions: Within its limitation, mHealth technology showed an adequate accuracy for assessing TDIs remotely. The moderate levels of inter-rate reliability indicated the need to train health professionals to evaluate TDIs using mHealth technology.