AI Disability Benefits Continuing Eligibility Review Playbook

A state disability benefits program administrator is conducting continuing eligibility reviews for 1,200 long-term recipients not reviewed in over 5 years. The program has a $240M annual budget. Prior audits suggest 8-12% of long-term recipients no longer meet eligibility criteria.

When to use this playbook

• Use this playbook when the decision looks like the situation above: A state disability benefits program administrator is conducting continuing eligibility reviews for 1,200 long-term recipients not reviewed in over 5 years.
• It is a fit when you have source files in hand and need a structured, reviewable analysis — not a generic chat answer about "Disability Benefits Continuing Eligibility Review".
• Do not use it as a substitute for licensed, legal, clinical, or authorized official judgment in the domain.

What you'll need

• Recipient database (diagnosis codes, benefit amounts, last review date, age)
• State wage database cross-match
• SSA CDR methodology documentation
• State disability program eligibility criteria
• Legal requirements for due process in benefit termination

Attachments: Documents (Documents)

You are a benefits program administrator designing a continuing disability review process for 1,200 long-term recipients. I am attaching:

Work only from the attached source files. If a conclusion is not supported, say so.

Produce:
1. Segment the 1,200 recipients by medical improvement likelihood: which diagnosis categories have the highest probability of changed circumstances?
2. Flag recipients showing wage database activity inconsistent with disability status.
3. Identify recipients who have aged into or out of program eligibility criteria since their last review.
4. Design the review prioritization: which 200 cases to review first given staff capacity constraints.
5. Tell me the due process requirements for suspension or termination and the required notice and appeal timeline.

Call out where independent models are likely to disagree, and list follow-up documents a reviewer should request.

What to expect

• Medical improvement likelihood segmentation
• Earned income activity flag list
• Age-based eligibility change identification
• 200-case review priority list
• Due process requirements and notice/appeal timeline

Review before you act

• Validate this output against source files before relying on it: Segment the 1,200 recipients by medical improvement likelihood: which diagnosis categories have the highest probability of changed circumstances?.
• Validate this output against source files before relying on it: Flag recipients showing wage database activity inconsistent with disability status.
• Validate this output against source files before relying on it: Identify recipients who have aged into or out of program eligibility criteria since their last review.
• Validate this output against source files before relying on it: Design the review prioritization: which 200 cases to review first given staff capacity constraints.
• Confirm every cited figure, date, counterparty, or requirement against the attached originals — models compress and can drop a qualifier.
• Treat disagreement between models as a review item, especially on classification, materiality, and recommended next action.
• Do not authorize an operational, clinical, legal, credit, or enforcement action solely because the models agree.