OMB Individually Reported

Qualitative Analysis

Low riskExact public inventory row

Description

How can thematic coding and trend analysis across qualitative data be done more efficiently? ACF staff often conduct surveys and interviews, which generate qualitative data that needs to be analyzed for themes and trends. The standard approach involves multiple human passes of labeling the data for analysis, which is very time-intensive.

Detailed example

ACF employees have several tools available to them to support qualitative analysis. Typically the tools are asked to assist with one of the following scenarios: - Take a user-provided list of topics and text passages to initially categorize passages by topic(s) - Suggest potential categories for organizing text passages - Identify thematic trends across a corpus of narrative data - Conduct sentiment analysis

AI / analytics pattern

Natural Language Processing: AI that processes, interprets, and shares information in human language.

Automation level / stage

c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.

Expected benefit

Faster initial labeling of qualitative data that human reviewers are then able to correct and iterate from

Controls / human review

ATO: Yes; PIA: To be posted on https://www.hhs.gov/pia/index.html, pending HHS OCIO action

Data needed

RAG implementation using commercially-available LLMs and user-provided narrative data