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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
VA · VA-24-462 · record R2104

Billing Claims Prediction

Department of Veterans Affairs · VHA: Veterans Health Administration

Overview

Development stage
In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation
High-impactSource: a) High-impact
Impact justification
Not reported
Start date
Not reported
Withheld from public reporting
Not reported

Mission

Topic area
Other
Operational functions
Forecasting and prediction, Clinical and medical Derived by keyword rules; see methodology

Problem the AI is intended to solve

The AI solution is designed to help the VHA Office of Finance, Revenue Operations in several ways: Identify missed revenue opportunities, ensuring no income potential is lost. Highlight, predict and analyze trends in actionable denials, helping to resolve systemic issues. Reduce the administrative burden on staff by simplifying processes. Develop a national denial management analytics platform for consistent and effective financial operations across the VA healthcare network.

Expected benefits

Increased revenue, decrease in denials, and increase efficiency and staff satisfaction.

System outputs

Predictions: ex. Forecasts about future events or trends based on historical data, such as predicting patient readmission rates or financial performance. Trends and insights: ex. Providing analysis and visualization of trends over time, such as tracking billing errors. Recommendations ex. Offering suggestions based on data analysis, such as recommending treatment plans for patients or optimizing resource allocation Visibility of analytics Automated actions: ex. Performing tasks automatically based on AI analysis, such as automating denial management processes or patient appointment scheduling.

Technology

AI classification
Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s)
Not reported
Custom-developed code
Not reported
Public source code
Not reported

Sourcing

How it was built
Not reported
Vendor (as reported)
Not reported
Vendors (standardized)
None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII
Not reported
Privacy Impact Assessment
Not reported
Authorization to Operate
Not reported
Demographic features
Not reported
Training and evaluation data
Not reported
Federal Data Catalog
Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported
AI impact assessmentNo answer reported
Independent reviewNo answer reported
Ongoing monitoringNo answer reported
Operator trainingNo answer reported
Fail-safeNo answer reported
Appeal processNo answer reported
User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported