Health Data in Dentistry: An Attempt to Master the Digital Challenge

Abstract

Background: Biomedical research has recently moved through three stages in digital healthcare: (1) data collection; (2) data sharing; and (3) data analytics. With the explosion of stored health data (HD), dental medicine is edging into its fourth stage of digitization using artificial intelligence (AI). This narrative literature review outlines the challenge of managing HD and anticipating the potential of AI in oral healthcare and dental research by summarizing the current literature. Summary: The basis of successful management of HD is the establishment of a generally accepted data standard that will guide its implementation within electronic health records (EHR) and health information technology ecosystems (HIT Eco). Thereby continuously adapted (self-) learning health systems (LHS) can be created. The HIT Eco of the future will combine (i) the front-end utilization of HD in clinical decision-making by providers using supportive diagnostic tools for patient-centered treatment planning, and (ii) back-end algorithms analyzing the standardized collected data to inform population-based policy decisions about resource allocations and research directions. Cryptographic methods in blockchain enable a safe, more efficient, and effective dental care within a global perspective. Key Message: The interoperability of HD with accessible digital health technologies is the key to deliver value-based dental care and exploit the tremendous potential of AI.