Leveraging GenAI for Efficient Review of CDC Programmatic Reports
Description
Manual qualitative review of text data within programmatic reports, such as Annual Progress Reports (APRs) submitted by Injury Control Research Centers (ICRCs) and Drug Free Communities (DFCs), is resource and time intensive. Across multiple use cases, generative AI (GenAI) and natural language processing (NLP) are being leveraged to automate the analysis of programmatic data. This approach streamlines the review and evaluation of various programmatic documents, improves efficiency, and supports the assessment of performance, progress, and challenges in funded activities.
Detailed example
The output from the AI-based framework consists of automated analyses and summaries of insights and patterns extracted from programmatic reports, such as APRs. The AI system highlights critical barriers, challenges, key themes, and trends identified within the data, providing structured summaries and actionable information. These outputs can be compared with manual qualitative analysis outcomes for validation and further refinement. As the framework evolves, the AI will be expanded to analyze additional sections of programmatic reports, including progress toward goals, program impact, and other relevant metrics, supporting comprehensive evaluation and reporting.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
By automating the extraction and analysis of critical information from programmatic data, generative AI is expected to significantly reduce the time required for manual coding and review. For example, initial applications have shown that AI can decrease manual review time from an estimated 35 hours to just 8 hours per topic, greatly enhancing efficiency. This time savings enables staff to focus on higher-level evaluations and strategic planning, improving the consistency and accuracy of assessments across multiple program areas.
Controls / human review
ATO: Not reported; PIA: Not published