Course Description

This course covers the technology-driven strategies at the heart of Part II of the MOC framework. You will study the role of AI-powered claims auditing, the specific types of billing errors and anomalies these systems detect, payment integrity and payment accuracy standards, fraud, waste, and abuse detection methodologies, and the analysis of unusual claims patterns. This domain represents the highest-impact area for direct cost recovery in most self-insured plans.

Learning Objectives

  • Explain why traditional claims auditing is inadequate for modern health plans.
  • Describe the capabilities of AI-powered claims auditing platforms.
  • Identify the most common types of claims payment irregularities.
  • Develop a fraud, waste, and abuse detection framework using technology and analytics.
  • Analyze unusual claims patterns and distinguish normal from anomalous claims behavior.
  • Apply payment integrity standards to measure and improve claims accuracy.

Estimated Completion Time: 20 hours

Course Content

LESSON 4.1: Leveraging Technology to Audit Medical Claims
3 Topics
TOPIC 4.1.1: Why Traditional Auditing Fails
TOPIC 4.1.2: What Modern Claims Audit Platforms Do
TOPIC 4.1.3: Key Features to Evaluate in a Claims Audit Platform
LESSON 4.2: Payment Integrity and Payment Accuracy
3 Topics
TOPIC 4.2.1: Understanding the Scale of Payment Inaccuracy
TOPIC 4.2.2: Frequently Occurring Claims Payment Irregularities
TOPIC 4.2.3: Why Payment Integrity Is a Fiduciary Mandate
LESSON 4.3: Fraud, Waste, and Abuse Detection
2 Topics
TOPIC 4.3.1: The Scope of the Problem
TOPIC 4.3.2: Detection Methodologies
LESSON 4.4: Unusual Claims and Anomaly Detection
2 Topics
TOPIC 4.4.1: Normal vs. Unusual Claims
TOPIC 4.4.2: Building a Normal/Unusual Claims Framework
Final Quiz
COURSE 4 QUIZ: TECHNOLOGY-DRIVEN CLAIMS AUDITING AND PAYMENT INTEGRITY