Big Data and Oral Health Disparities: A Critical Appraisal

Area of Science:

• Public Health
• Health Informatics
• Dental Research

Background:

• Big data, including electronic health records (EHRs) and claims data, is increasingly vital for understanding health inequities.
• Oral health disparities persist across various demographic and socioeconomic groups.
• Existing research often lacks comprehensive analysis of data quality and causal relationships in big data studies of oral health.

Purpose of the Study:

• To critically review the evidence on big data analytics and oral health disparities.
• To identify knowledge gaps and discuss future implications for addressing oral health inequities.
• To evaluate studies using a data quality framework focusing on intrinsic and contextual dimensions.

Main Methods:

• A systematic review of published reports from 2014-2023 on big data, social determinants, and oral health disparities.
• Searches conducted in MEDLINE, Google Scholar, and Web of Science.
• Inclusion of 23 retrospective studies, critically appraised using intrinsic and contextual data quality dimensions.

Main Results:

• Big data analytics identified disparities in oral health outcomes and dental care utilization based on race, ethnicity, socioeconomic status, geography, and insurance.
• No studies reported on intrinsic data quality dimensions like missingness or consistency.
• Studies provided strong contextual data, with some offering novel insights into racial oral health inequities.

Conclusions:

• Big data effectively highlights oral health disparities but often relies on association-based analytics, limiting causal understanding.
• Gaps in study design and causal analytics were observed, particularly in the application of artificial intelligence.
• Future research should focus on improving data quality reporting and employing advanced analytical methods to establish causality in oral health disparities.