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A Data-informed Public Health Policy-Makers Platform.

Dario Brdarić1,2, Senka Samardžić1, Ivana Mihin Huskić1

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Data-driven modeling aids public health policy for growing hearing loss challenges. This approach supports policymakers in addressing noise exposure and aging populations to improve health outcomes.

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Area of Science:

  • Public Health
  • Health Informatics
  • Epidemiology

Background:

  • Hearing loss is a growing public health concern, influenced by factors like noise exposure and an aging population.
  • Effective public health policies are crucial for managing and mitigating the impacts of hearing loss.
  • Data-driven modeling is essential for informed policymaking in disease management.

Purpose of the Study:

  • To outline a data-driven policymaking process for addressing hearing loss.
  • To present a platform designed to support public health policy development for hearing loss.
  • To demonstrate the practical application and usability of the platform for policymakers.

Main Methods:

  • Described the steps of a data-driven policymaking process.
  • Developed a platform to support hearing loss policy development.
  • Conducted preliminary analytics and presented initial results.
  • Collected survey feedback from health system policymakers.

Main Results:

  • Demonstrated the capabilities and usability of the proposed policymaking support platform.
  • Presented initial analytical results within a policy-making context.
  • Validated the utility of the data-driven approach through user feedback.

Conclusions:

  • The data-driven approach and supporting platform are valuable tools for public health policymakers.
  • The presented methodology can effectively aid in developing policies to address hearing loss.
  • The approach was positively received and validated by health system policymakers in Croatia.