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A Modelling Framework for Evidence-Based Public Health Policy Making.

Marios Prasinos, Ioannis Basdekis, Marco Anisetti

    IEEE Journal of Biomedical and Health Informatics
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    This study introduces a novel ontology and integrated platform for evidence-based public health policy making. The model-driven solution utilizes big data analytics to improve decision-making for managing health conditions like hearing loss.

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    Area of Science:

    • Public Health
    • Health Informatics
    • Data Science

    Background:

    • Public health policy making requires evidence-based approaches supported by data analytics.
    • Heterogeneous data sources (e.g., device usage, lifestyle, environmental) are crucial for effective health management.
    • Existing decision-making tools lack tailored analytics for comprehensive public health policy development.

    Purpose of the Study:

    • To present a novel ontology and integrated platform for evidence-based public health policy making.
    • To demonstrate a model-driven approach utilizing big data analytics for policy development.
    • To support the EVOTION research program focused on hearing loss management.

    Main Methods:

    • Development of a model-driven ontology for public health policy decision making (PHPDM).
    • Implementation of an integrated web-based platform using Hadoop, Spark, and HBASE.
    • Utilizing big data analytics to process heterogeneous health-related data.

    Main Results:

    • The PHPDM models define data collection, analysis, and evidence generation for policy interventions.
    • The platform integrates diverse data types to support informed public health policy decisions.
    • The approach facilitates the analysis of evidence to support or contradict policy actions.

    Conclusions:

    • The novel ontology and platform offer a robust framework for evidence-based public health policy making.
    • Big data analytics and model-driven approaches enhance the management of health conditions at a policy level.
    • The EVOTION project demonstrates a practical application for hearing loss policy development.