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LEARN > Use Cases > A Vital Source: How Birth and Death Data Inform Decision-Making to Support Public Health Outcomes

A Vital Source: How Birth and Death Data Inform Decision-Making to Support Public Health Outcomes

13 Jun 2024
Use Cases



This use case delves into the significance of vital records in informing decision-making for public health outcomes. Vital records, such as birth and death certificates, provide official documentation of identity, relationships, and ownership rights, and offer insights into birth and mortality trends. The United States' current system comprises 57 separate state and local vital records offices. Data from death certificates are particularly valuable for understanding causes of death and identifying trends in public health, while birth data provide critical health information and insights into social determinants of health. The National Center for Health Statistics (NCHS) operates the National Vital Statistics System, which gathers and analyzes vital records data to support public health research and policy decisions. Vital records data are utilized at various levels, ranging from county to national, to inform public health interventions, resource allocation, and policy development. This use case presents three examples of how vital records data have been used to inform decision-making and impact public health outcomes at the county, state, and national levels. These examples include the use of birth data for ethical predictive modeling in Allegheny County, Pennsylvania, the use of individual-level data linkage in Massachusetts to address the opioid epidemic, and the creation of the Johns Hopkins University Coronavirus Resource Center to track the spread of COVID-19. In addition, this use case highlights the challenges and opportunities in the vital records data infrastructure and emphasizes the need for sustained federal investment and modernization to support more efficient and effective public health policymaking.



This paper is a product of the Data Foundation. The findings and conclusions expressed by the authors do not necessarily reflect the views or opinions of the Data Foundation, its funders and sponsors, or its board of directors.

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