Benefits Contention Classification Model
Description
The Benefits Contention Classification model is intended to improve the current benefits adjudication process by providing an automated classification for all benefits claims contentions. The model will do this by providing a classification for each contention that is not currently covered by the existing process. This is intended to make the overall benefits adjudication process more efficient by reducing the necessary time for VA rating representatives to choose the appropriate disability questionnaire for the the given contention.
Detailed example
The model outputs an internal classification (e.g., 3140) which is used to classify free text into a medical category.
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 expected benefit of this model is increasing efficiency in the benefits adjudication process by automating the internal classification required to select the disability benefits questionnaire that should be sent to the Veteran.
Controls / human review
ATO: Not reported; PIA: Not published