AI Use Policy Tool
Description
Ensure public confidence in the integrity of DAB decisions by maximizing quality review standards and reducing errors.
Detailed example
Analysis of large volumes of data that can be used to address common errors and supports the development of targeted training and job aid.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The DAB is responsible for issuing fair, impartial, legally correct and defensible determinations which serve as the final decision of the DHHS Secretary. The AI quality review large language model (LLM) tool will use an LLM to create algorithms that run behind our case tracking system to randomly select certain DAB decisions to identify potential quality review issues. The LLM will scan DAB decisions to ensure compliance with quality review standards (e.g., protect PHI, PII and FTI). Benefits include more effective quality review and faster identification of data trends that may require additional analysis.
Controls / human review
ATO: Not reported; PIA: Not published