Continuing Disability Review Model
Description
This AI use case identifies disability cases with the greatest likelihood of medical improvement and flag them for a continuing disability review to improve the accuracy of program administration.
Detailed example
The system outputs numerical scores for each case: the score represents the likelihood of medical improvement. The probabilities are binned according to low, medium, or high.
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
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Improving accurate claim processing: ensuring that only those who qualify for benefits remain on the rolls.
Controls / human review
ATO: No; PIA: Not published
Data needed
Model used data from disability program data sets including Master Beneficiary Record (MBR) and Supplemental Security Record (SSR). In addition for Title II (retirement, survivors, and disability benefits) models health data from Centers for Medicare and Medicaid Services (CMS) is utilized.