Joda, Tim and Waltimo, Tuomas and Pauli-Magnus, Christiane and Probst-Hensch, Nicole and Zitzmann, Nicola U.. (2018) Population-based linkage of big data in dental research. International journal of environmental research and public health, 15 (11). p. 2357.
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Abstract
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.
Faculties and Departments: | 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Chronic Disease Epidemiology > Exposome Science (Probst-Hensch) 03 Faculty of Medicine > Departement Public Health > Sozial- und Präventivmedizin > Exposome Science (Probst-Hensch) 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) |
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UniBasel Contributors: | Probst Hensch, Nicole |
Item Type: | Article, refereed |
Article Subtype: | Research Article |
ISSN: | 1660-4601 |
Note: | Publication type according to Uni Basel Research Database: Journal article |
Language: | English |
Identification Number: |
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edoc DOI: | |
Last Modified: | 22 Nov 2018 12:40 |
Deposited On: | 22 Nov 2018 12:40 |
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