Training Course on Healthcare Fraud Detection and Prevention

Module 1 – Introduction to Healthcare Fraud and Abuse
Subtopics:
Defining fraud, waste, and abuse in healthcare.
Global and regional burden of healthcare fraud.
Common types of fraud: billing fraud, insurance fraud, identity theft, procurement fraud, kickbacks.
Key actors: providers, insurers, suppliers, patients.
Financial, ethical, and social implications.
Practical Activities:
Case Study: Review a real-world healthcare fraud scandal (e.g., overbilling, ghost patients).
Group Discussion: Why is healthcare particularly vulnerable to fraud?

Module 2 – Fraud Schemes and Red Flags in Healthcare Systems
Subtopics:
Fraud in health insurance and claims processing.
Provider-level fraud: phantom billing, upcoding, unnecessary procedures.
Pharmaceutical and supply chain fraud: counterfeit drugs, procurement fraud, diversion.
Red flags and early warning signals in health records and billing data.
Fraud in public health programs and donor-funded projects.
Practical Activities:
Exercise: Identifying red flags in sample insurance claim datasets.
Role Play: Fraud risk assessment in a hospital procurement process.

Module 3 – Investigative and Auditing Techniques
Subtopics:
Role of internal audit and compliance units.
Investigative approaches: document reviews, interviews, site visits.
Tracing fraudulent financial transactions.
Evidence gathering and chain of custody.
Collaboration with law enforcement and regulatory bodies.
Practical Activities:
Simulation: Conducting a mini-investigation into suspicious claims.
Group Exercise: Designing a hospital fraud risk audit checklist.

Module 4 – Data Analytics and Technology for Fraud Detection
Subtopics:
Role of big data, AI, and machine learning in fraud detection.
Data mining and pattern recognition in billing systems.
Use of predictive analytics to detect anomalies.
Electronic Medical Records (EMR) and digital surveillance for fraud prevention.
Cybersecurity considerations in healthcare fraud prevention.
Practical Activities:
Hands-On Exercise: Analyze sample claims data to detect anomalies.
Case Example: Using predictive models to flag fraudulent provider behavior.

Module 5 – Legal, Regulatory, and Organizational Safeguards
Subtopics:
National and international legal frameworks for combating healthcare fraud.
Role of compliance programs, whistleblower protections, and corporate governance.
Policies and internal controls for fraud prevention.
Ethics, accountability, and building a culture of transparency.
Future trends in healthcare fraud prevention.
Practical Activities:
Simulation: Drafting a healthcare fraud prevention policy for an insurance company.
Capstone Project: Participants design a fraud detection and prevention strategy for their institution or health system.
Course outcomes:
Comprehensive understanding of healthcare fraud risks and types.
Ability to identify and investigate fraud schemes.
Practical skills in auditing, data analytics, and fraud detection.
Knowledge of legal and regulatory frameworks.
Tools for building organizational resilience against fraud.
A capstone project: fraud prevention strategy tailored to participant’s context.
Certificate of completion.