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Evidence-based Public Health Policy Models Development and Evaluation using Big Data Analytics and Web Technologies
Konstantinos Moutselos1, Ilias Maglogiannis1
1Department of Digital Systems, University of Piraeus, Greece.
Medical Archives (Sarajevo, Bosnia and Herzegovina)
|April 23, 2020
Summary
This study introduces a cloud-based Decision Support System to enhance evidence-informed public health policy development. The system connects public health policies (PHP) with key performance indicators (KPIs) for better decision-making.
Area of Science:
- Public Health
- Health Informatics
- Health Policy Analysis
Background:
- Health policy is crucial for societal health goals, as defined by WHO.
- Evidence-informed decision-making in health policy is often lacking in practice.
- Bridging the gap between scientific evidence and policy implementation is a significant challenge.
Purpose of the Study:
- To present a cloud-based Decision Support System (DSS) tailored for public health decision-making.
- To facilitate the creation and evaluation of public health policies using a systematic approach.
Main Methods:
- The CrowdHEALTH system links Public Health Policies (PHP) to Key Performance Indicators (KPIs).
- A Policy Development Toolkit was designed for creating policy models and generating analytical results.
- System design, technical implementation, and use case scenarios are detailed.
Main Results:
- The Policy Development Toolkit offers a user-friendly interface for policymakers.
- It enables the creation of policy models and provides analytical outcomes for evidence-based decisions.
- The system supports policy evaluation through quantitative analysis.
Conclusions:
- The Public Health Policy Model's hierarchical structure enhances policy creation and management.
- Health Analytics Tools Results Objects provide quantitative support for policies.
- The system lays the groundwork for advanced meta-analytic operations in public health.
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