Decoding Dental Insurance Claims Data for Oral Health Research and Policy: Challenges, Validation, and Opportunities in Biomedical Informatics—A Scoping Review

Background: Dental insurance claims data are vital for research in oral health, epidemiology, and policy. However, issues like data quality, coding standards, validity, interoperability, and analytical approaches hinder their use. This review outlines these challenges. Methods: Following PRISMA-ScR and Arksey-O’Malley, we searched Web of Science, Scopus, and PubMed through April 2026 for peer-reviewed studies on dental insurance data issues. Two reviewers screened and extracted data, identifying key challenges and implications. Results: Out of 563 records, 389 remained after deduplication; 45 studies met criteria. Data sources included Medicaid, Medicare, insurers, and national systems from various countries. Six main challenges emerged: (1) coding errors and lack of standardization; (2) data validity and quality concerns; (3) interoperability and linkage barriers; (4) fraud detection issues; (5) analytical limitations; (6) policy insights on disparities. Validation showed variable accuracy, with diagnosis codes more reliable than procedure codes. Conclusions: Challenges limit data use in research and policy. Standardized coding, validation, interoperability, transparency, and causal inference are essential for leveraging these data to improve oral health research and policies.