Population-Based Linkage of Big Data in Dental Research

• Main Authors: Tim Joda, Tuomas Waltimo, Christiane Pauli-Magnus, Nicole Probst-Hensch, Nicola U. Zitzmann
• Format: Article
• Language: English
• Published: MDPI AG 2018-10-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: big data; patient-generated health data (PGHD); register-based controlled (clinical) trials [RC(C)T]; epidemiological research; public health
• Online Access: https://www.mdpi.com/1660-4601/15/11/2357

Population-based linkage of patient-level information opens new strategies for dental research to identify unknown correlations of diseases, prognostic factors, novel treatment concepts and evaluate healthcare systems. As clinical trials have become more complex and inefficient, register-based controlled (clinical) trials (RC(C)T) are a promising approach in dental research. RC(C)Ts provide comprehensive information on hard-to-reach populations, allow observations with minimal loss to follow-up, but require large sample sizes with generating high level of external validity. Collecting data is only valuable if this is done systematically according to harmonized and inter-linkable standards involving a universally accepted general patient consent. Secure data anonymization is crucial, but potential re-identification of individuals poses several challenges. Population-based linkage of big data is a game changer for epidemiological surveys in Public Health and will play a predominant role in future dental research by influencing healthcare services, research, education, biotechnology, insurance, social policy and governmental affairs.