Content Analysis of Social Determinants of Health Accelerator Plans Using Artificial Intelligence: A Use Case for Public Health Practitioners.

Journal: Journal of public health management and practice : JPHMP
Published Date: Feb 26, 2025

Abstract

CONTEXT: Public health practice involves the development of reports and plans, including funding progress reports, strategic plans, and community needs assessments. These documents are valuable data sources for program monitoring and evaluation. However, practitioners rarely have the bandwidth to thoroughly and rapidly review large amounts of primarily qualitative data to support real-time and continuous program improvement. Systematically examining and categorizing qualitative data through content analysis is labor-intensive. Large language models (LLMs), a type of generative artificial intelligence (AI) focused on language-based tasks, hold promise for expediting content analysis of public health documents, which, in turn, could facilitate continuous program improvement.

Authors

  • Kelli DePriest
    Author Affiliations: Research Triangle Institute: RTI International, Research Triangle Park, North Carolina (Dr DePriest, Mr Feher III, Ms Gore, Dr Glasgow, and Mr Chew); Association of State and Territorial Health Officials (ASTHO), Arlington, Virginia (Mr Grant); National Association of County and City Health Officials (NACCHO), Washington, District of Columbia (Mr Holtgrave); Centers for Disease Control and Prevention (CDC), Atlanta, Georgia (Dr Hacker).
  • John Feher Iii
  • Kailen Gore
  • LaShawn Glasgow
  • Clint Grant
  • Peter Holtgrave
  • Karen Hacker
  • Robert Chew
    Center for Data Science, RTI International, Research Triangle Park, NC, United States.

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