Artificial Intelligence Supported Telehealth System for the Provision of Orthodontic Treatment to Public Patients

Authors

  • Oyku Dalci The University of Sydney
  • Hui Theng Chong The University of Sydney
  • Shilpi Ajwani Sydney Local Health District
  • M Ali Darendeliler The University of Sydney

Abstract

Background: Many children needing orthodontic treatment through public dental services miss the correct orthodontic treatment time due to long waiting time and limited resources. Remote orthodontic treatment monitoring has been shown to reduce face-to-face appointment. 

Aims: The aim of the study was to evaluate the feasibility of using an artificial intelligence supported telehealth system, Dental Monitoring (DM), and general dentists in providing orthodontic treatment to patients in the public system.

Methods: This prospective pilot study included 23 patients from the waiting list of Sydney Dental Hospital. Patients were treatment planned by 2 orthodontists and their appliances/treatment was provided by general dentists, under the orthodontists’ remote monitoring via DM.  Before and after observation period digital dental casts were scored to check the improvement in malocclusion/bite. For the patients with a Class II malocclusion, needing growth modification, lateral cephalometric analysis was also carried out. Patient experience with DM was appraised via a questionnaire.

Results: For patients compliant with aligner wear and use of DM, after a mean treatment duration of 9.2 months, there was significant improvement in the digital dental cast scores. Class II patients had significant improvement in their lower jaw position.  92% and 100% of patients indicated that DM scans were easy to do and use respectively. 1/3 of the patients preferred face-to-face appointments over DM.

Conclusions: The use of aligners by general dentists under orthodontists’ remote supervision via Dental Monitoring improved the malocclusion/bite scores and lower jaw position during the observation period of this study. 

Published

2022-07-27

Issue

Section

ePosters