3. Typical LTC Payment Approach
• Prospective
• Algorithmic in nature
• Ad hoc, claim‐by‐claim basis
• Uses underdeveloped claims systems
• Limited plan/payment logic
• Human‐based process
Customized Data Mining & Overpayment Recovery
4. Sources of Leakage
• Personnel changes
• Data entry errors
• Multiple billings/inconsistent cycles
• Peripheral data errors (vendor, policy,
enrollment, check writing)
• Manual overrides
• Manual checks
• Inconsistent connections between peripheral
data sources
Customized Data Mining & Overpayment Recovery
5. Traditional Countermeasures
• Random file reviews
• Paper audits
• Supervisory controls
• Case management
• Manual processes that are inefficient and
summary in nature
Customized Data Mining & Overpayment Recovery
7. The APU Process:
RECOVER OVERPAYMENTS
• Use existing client data extracts
• Automate production and delivery of inquiry
letters
• Follow up and resolve overpayment requests
• Handle all inquiries
• Receive and account for reimbursements
• Provide full accounting and a CHECK to client
Customized Data Mining & Overpayment Recovery
8. The Benefits
• Recover 1‐3% of total dollars paid
• Cleaner data
• Fundamental system errors identified
• Improved payment processing
• Outsourced solution frees up internal
resources
Customized Data Mining & Overpayment Recovery
10. The Result
APU … IT’S FOUND MONEY!
Customized Data Mining & Overpayment Recovery
11. FOR MORE INFORMATION,
PLEASE CONTACT
JIM DEL VECCHIO,
PRESIDENT & CEO
Phone: (866) 434‐8303
Fax: (806) 378‐9822
Email: jdelvecchio@apuinc.com
Customized Data Mining & Overpayment Recovery