EventsThe 1st International Online Conference on Dentistry
Published
This submission belongs to the session S3. Pediatric Dentistry and Orthodontics of the event The 1st International Online Conference on Dentistry
Published date
02 Oct, 2026
Academic Editor
author-avatarGeorgios Romanos
Citation
Ajay K Kubavat, Khyati V Patel, Clinical Decision Support Systems in Orthodontics and Pediatric Dentistry: Enhancing Diagnostic Accuracy, Treatment Efficiency, and Evidence-Based Care Delivery, in Proceedings of The 1st International Online Conference on Dentistry, 7 October–9 October 2026, MDPI: Basel, Switzerland
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Clinical Decision Support Systems in Orthodontics and Pediatric Dentistry: Enhancing Diagnostic Accuracy, Treatment Efficiency, and Evidence-Based Care Delivery

1. Academic Affairs, Orthodntics , AIDM, Paris Regional Health, 1401 Philomena Street Austin, TX 78723, USA
2. Sure Align Orthodntix n Dentistry, Ahmedabad, India
3. Department of Orthodontics and Dentofacial Orthopaedics Narsinhbhai Patel Dental College and Hospital, Sankalchnad Patel University, Visnagar, India
Abstract

Background: Clinical Decision Support Systems (CDSS) are health information technologies designed to assist clinicians in making evidence-based decisions at the point of care. By integrating patient-specific data with curated knowledge bases, CDSS tools generate actionable recommendations that reduce diagnostic variability, minimize clinical errors, and standardize treatment protocols across orthodontic and pediatric dental practice settings.
Objectives: This study evaluates the clinical utility, accuracy, and user acceptability of CDSS tools in orthodontic and pediatric dental settings, focusing on diagnostic consistency, treatment planning quality, and adherence to evidence-based guidelines.
Methods: A mixed-methods design combined a systematic review of CDSS applications in dentofacial care (2017–2025) with a prospective observational cohort of 180 clinicians across three university dental teaching hospitals. The EHR-integrated CDSS provided real-time alerts, differential diagnoses, and treatment pathway suggestions during consultations. Performance was assessed via sensitivity, specificity, and positive predictive value. Clinician experience was evaluated using Technology Acceptance Model (TAM) questionnaires, and inter-rater agreement was analyzed using Cohen’s Kappa.
Results: CDSS integration significantly improved diagnostic concordance among junior clinicians, with Cohen’s Kappa increasing from 0.61 to 0.84 (p < 0.001). Sensitivity and specificity for early malocclusion detection reached 89.3% and 85.7%, respectively. Guideline adherence in treatment planning improved by 34.2%. Caries risk stratification alerts achieved a 91.1% clinician acceptance rate. TAM analysis indicated high perceived usefulness (4.3/5.0), while alert fatigue and workflow disruption were identified as key adoption barriers.
Conclusions: CDSS tools meaningfully enhance diagnostic accuracy and evidence-based care delivery in orthodontics and pediatric dentistry. Successful implementation requires clinician training, user-centered design, and seamless EHR integration. Longitudinal studies assessing patient outcome improvements attributable to CDSS-guided care are warranted.

Keywords
Keywords: clinical decision support systems
CDSS
orthodontics
pediatric dentistry
evidence-based dentistry
diagnostic accuracy
electronic health records
treatment planning
digital health
caries risk assessment
malocclusion detection
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