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REDUCING FRAUD RISK IN
HEALTHCARE PROVIDERS' CONTRACTS
Aavenir
with Automated Obligation Management
Table of Content
Healthcare Frauds Healthcare Compliance Program
Applicable Laws &
Regulations
Obligation Management for Fraud
Prevention
Common types of Healthcare fraud
detected across the US
Best practices & a well-designed
compliance program to combat fraud
Types of agreements and regulatory
compliance obligations
Ongoing obligation and compliance
management-powered by AI
TYPES OF
HEALTHCARE FRAUDS
Billing for services not rendered
Misrepresenting date, location, or
service provider
Incorrect reporting of diagnosis or
procedures
Corruption and kickbacks
False issuance of drugs prescription
Healthcare Frauds
LAWS & REGULATIONS IN THE
UNITED STATES HEALTHCARE
The Stark Law
Federal Anti-Kickback Law
False Claims Act
The Joint Commission on Accreditation of
Healthcare Organizations (JCAHO)
Health Insurance Portability and
Accountability Act (HIPAA)
The Health Information Technology for
Economic and Clinical Health (HITECH) Act
Healthcare Regulations
COMPLIANCE PROGRAM
HEALTHCARE
Speed up and optimize proper payment of
claims
Minimize billing and “creative” invoicing
mistakes
Reduce the chances of a HealthCare
Financing Administration (HCFA) or Office
of Inspector General (OIG) audit
Avoid conflicts with self-referral and anti-
kickback statutes
Compliance Practices
OBLIGATION MANAGEMENT
FOR FRAUD PREVENTION
Implement written policies, procedures, and
standards of conduct.
Designate Compliance Officer and a
compliance committee.
Conduct effective training & education
Identify, Track, Manage, & Monitor
obligations at each level
Obligation Management
AI-ENABLED
OBLIGATION & COMPLIANCE MANAGEMENT SOLUTION
helps you achieve
70% 35%
98% 71%
faster obligation identification cycle
time
cost savings with centralized
obligations fulfilment approach
on-time obligation fulfillment improvement in compliance
To learn more, FREE download
E-BOOK
E-BOOK
REDUCING HEALTHCARE
REDUCING HEALTHCARE
FRAUDS
FRAUDS
PRODUCT BRIEF
PRODUCT BRIEF
OBLIGATION MANAGEMENT
OBLIGATION MANAGEMENT
SOLUTION
SOLUTION

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Automated Obligation Management to Reduce Fraud RIsks in Healthcare Provider Contracts.pdf

  • 1. REDUCING FRAUD RISK IN HEALTHCARE PROVIDERS' CONTRACTS Aavenir with Automated Obligation Management
  • 2. Table of Content Healthcare Frauds Healthcare Compliance Program Applicable Laws & Regulations Obligation Management for Fraud Prevention Common types of Healthcare fraud detected across the US Best practices & a well-designed compliance program to combat fraud Types of agreements and regulatory compliance obligations Ongoing obligation and compliance management-powered by AI
  • 4. Billing for services not rendered Misrepresenting date, location, or service provider Incorrect reporting of diagnosis or procedures Corruption and kickbacks False issuance of drugs prescription Healthcare Frauds
  • 5. LAWS & REGULATIONS IN THE UNITED STATES HEALTHCARE
  • 6. The Stark Law Federal Anti-Kickback Law False Claims Act The Joint Commission on Accreditation of Healthcare Organizations (JCAHO) Health Insurance Portability and Accountability Act (HIPAA) The Health Information Technology for Economic and Clinical Health (HITECH) Act Healthcare Regulations
  • 8. Speed up and optimize proper payment of claims Minimize billing and “creative” invoicing mistakes Reduce the chances of a HealthCare Financing Administration (HCFA) or Office of Inspector General (OIG) audit Avoid conflicts with self-referral and anti- kickback statutes Compliance Practices
  • 10. Implement written policies, procedures, and standards of conduct. Designate Compliance Officer and a compliance committee. Conduct effective training & education Identify, Track, Manage, & Monitor obligations at each level Obligation Management
  • 11. AI-ENABLED OBLIGATION & COMPLIANCE MANAGEMENT SOLUTION
  • 12. helps you achieve 70% 35% 98% 71% faster obligation identification cycle time cost savings with centralized obligations fulfilment approach on-time obligation fulfillment improvement in compliance
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