The case time series design: a new tool for big data analysis

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Biomedical research has been transformed by the recent development of big data technologies. For instance, the collection of health records in linked electronic databases provide information on demographics, health events, medications, and lifestyle factor for large samples of patients. Similarly, portable devices such as mobile phones provide the possibility to recruit large number of participants, and to collect real-time and geo-located individual-level measurements. While these resources offer the possibility to answer research questions that could not be feasibly addressed using traditional studies, they require innovative analytical approaches.This project contributes to address this issue through the development of a novel analytical method called case time series design. This design combines features of existing approaches to generate a more adaptable tool, particularly well-suited for the analysis of highly-informative big data resources. The case time series design is applicable in different research areas for investigating health effects associated with various risk factors, such as environmental exposures, clinical conditions, or drug use. The research proposal is structured in a detailed work plan that includes the methodological development of the case time series design and examples that illustrate its application in various research areas within biomedical research.