Content and features of electronic dental record systems: A study in a developing country

Abstract

A comprehensive evaluation of the features and content of Electronic Dental Record (EDR) systems is essential for the effective implementation of these systems. The present study aimed to determine the content and features of EDR systems in dental clinics. In this cross-sectional research conducted in 2020, the EDR data elements of 22 dental clinics in Tehran, Iran, were compared based on the data elements outlined in the standards of the American Society for Testing and Materials (ASTM), the American Dental Association (ADA), and the University of Pittsburgh. Additionally, the EDR features were compared with the features proposed by the Health Level Seven (HL7) functional model, Healthcare Information and Management Systems Society (HIMSS) adoption model, and Certification Commission for Healthcare Information Technology (CCHIT) model. Moreover, descriptive statistics were employed to analyze the data. Among the 219 data elements identified, 23 were supported across all systems—with the ‘medical care’ category being the only one where all its data elements were fully included. Conversely, 55 data elements were entirely absent across all systems, resulting in complete omission in categories such as ‘contact with hazardous substances,’ ‘diagnostic tests,’ ‘extra oral examination,’ and ‘risk assessment.’ Regarding system features, out of 74 features evaluated, 11 were present in all systems, whereas 22 were completely absent, including all features under the ‘drug administration’ and ‘support for treatment plans, guidelines, and protocols’ categories. Current EDR systems, rather than being comprehensive clinical systems, function primarily as basic administrative and information recording tools. The complete lack of clinical decision support features and critical clinical data elements represents a significant gap. Future developments of EDR systems should prioritize the inclusion of standardized clinical data sets and decision support functions to enhance their practical application and efficiency in dental offices and clinics.

The authors' abstract, as published at the source. Scientific Reports, 2026 · DOI ↗