Independent Dispute Resolution (IDR) Eligibility Rules Engine
Description
The current Independent Dispute Resolution (IDR) Technical Assistance (TA) process is very manual and time intensive which limits throughput. The rules engine should significantly expedite processing and expand capacity. Automating more of the process may also increase consistency across recommendations and result in a more predictable timeframe for the workflow by better positioning disputes for analyst review.
Detailed example
Use of artificial intelligence (AI) models to identify the presence or absence of necessary data points within documentation. AI tool searches documentation to identify and store necessary data points such as document title, file type, payment date, service code, claim number, and date of service.
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
The AI tool will help automate the eligibility review process, reducing time-intensive manual steps and increasing consistency of results.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Federal Independent Dispute Resolution (IDR) Dispute Data