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What Data Should Be Included in a Modern Public Health Data System
Joie D Acosta1, Anita Chandra1, Douglas Yeung2
1RAND Corporation, Arlington, Virginia, USA.
Big Data
|September 7, 2022
Summary
Public health data systems need modernization to effectively measure health equity and well-being. Recommendations focus on data collection, prioritization, and technology to address current gaps and improve national health status reporting.
Area of Science:
- Public Health Data Systems
- Health Equity Measurement
- Health Informatics
Background:
- The public health data system faces a data deluge, with increasing volume and variety.
- Current data collection and prioritization methods are insufficient for addressing health inequities.
- There's a critical need to "reboot" how national health status is analyzed and acted upon.
Purpose of the Study:
- To summarize essential data for measuring health equity, positive health, and well-being.
- To identify technological and data sector contributions to fill existing measurement gaps.
- To inform the transformation of public health data systems.
Main Methods:
- Literature review.
- Environmental scan of existing data practices.
- Deliberations from the National Commission to Transform Public Health Data Systems.
Main Results:
- Identified key data elements crucial for measuring health equity and well-being.
- Highlighted the potential of technology and data sectors to enhance public health data capabilities.
- Provided a framework for prioritizing data for effective public health investments.
Conclusions:
- Modernizing public health data systems is essential for accurately assessing national health.
- Strategic data collection and technological integration can drive investments towards health equity.
- A transformed data system is vital for measuring and improving population health and well-being.
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