Registration and Intro

I. Introduction to Healthcare/Insurance fraud

• a. What Is Healthcare/Insurance fraud?
• b. What Does Healthcare/Insurance fraud Look Like?
• c. Healthcare/Insurance fraud in the United States
• d. Healthcare/Insurance fraud in International Markets
• e. Who Commits Healthcare/Insurance fraud?
• f. What Is Healthcare/Insurance fraud Examination?
• g. Latest Trends & Challenges Globally in Health Insurance Fraud System
• h. The Healthcare Continuum: An Overview
• i. Healthcare/Insurance fraud Overview: Implications for Prevention, Detection, and Investigation

II. Defining Market Players within the Healthcare Continuum

• a. The Patient
  • i. Who is the patient?
  • ii. What are some examples of patient fraud?
  • iii. How does the patient role relate to other healthcare continuum players?
• b. The Provider
  • i. Who is the provider?
  • ii. What are some examples of provider fraud?
  • iii. How does the provider role related to other healthcare continuum players?
• c. The Payer
  • i. Who is the payer?
  • ii. What are some examples of payer fraud?
  • iii. How does the payer role related to other healthcare continuum players?
• d. The Employer/Plan Sponsor
  • i. Who is the employer/plan sponsor?
  • ii. What are some examples of employer/plan sponsor fraud?
  • iii. How does the employer/plan sponsor role relate to other healthcare continuum players?
• e. The Vendor and the Supplier
  • i. Who are the vendor and the supplier?
  • ii. What are some examples of vendor and supplier fraud?
  • iii. How do the vendor and supplier roles relate to other healthcare continuum players?
• f. The Government
  • i. Who is the government?
  • ii. What are some examples of government fraud?
  • iii. How does the government role relate to other healthcare continuum players?
• g. Market Players Overview: Implications for Prevention, Detection, and Investigation

III. Protected Health Information

• a. How to Recognize & Avoid Health Insurance Fraud
• b. Is Health insurance Fraud Victimless?
• c. Health Insurance Portability and Accountability Act (HIPAA) of 1996
• d. Audit Guidelines in Using PHI
• e. Healthcare insurance Fraud: Penalties & Consequences
• i. Global Perspective: compare and contrast
• f. Cracking Down on Healthcare Insurance Fraud
• g. Protected Health Information Overview: Implications for Prevention, Detection, and Investigation

IV. Health Information Pipelines

• a. The Auditor’s Checklist
• b. What Are the Channels of Communication in a Health Information Pipeline?
  • i. The patient
  • ii. The provider
  • iii. The employer/plan sponsor
  • iv. The vendor/supplier
  • v. The government plan sponsor
• c. Unauthorized Parties
• d. HIP Overview: Implications for Prevention, Detection, and Investigation

V. Accounts Receivable Pipelines

• a. Overview of Healthcare Reimbursement
• b. Types of Reimbursement Models
  • i. Fee-for-service model
  • ii. Prospective model
  • iii. Capitation-structured model
• c. Data Contained in Accounts Receivable Pipelines
• d. Accounts Receivable Pipelines by HCC Player
  • i. The patient
  • ii. The provider
  • iii. The payer
  • iv. The employer/plan sponsor
  • v. Other
• e. ARP Overview: Implications

VI. Operational Flow Activity

• a. Operational Flow Activity Assessment
  • i. The patient
  • ii. The provider
  • iii. The payer
  • iv. The employer
  • v. The “other”
• b. OFA Overview: Implications for Prevention, Detection, and Investigation

VII. Product, Service, and Consumer Market Activity

• a. Product Market Activity
• b. Service Market Activity
• c. Consumer Market Activity
• d. PMA, SMA, and CMA Overview: Implications for Prevention, Detection, and Investigation

VIII. Data Management

• a. Data Management
• b. Market Example: Setting Up a Claims RDBMS
• c. Data Management Overview: Implications for Prevention, Detection, and Investigation
• d. References

IX. National Infrastructure

• a. Normal Profile of a Fraudster
  • i. What types of people or entities commit fraud?
  • ii. What is the key element of a fraudster?
• b. Anomalies and Abnormal Patterns
• c. Normal Infrastructure Overview: Implications for Prevention, Detection, and Investigation

X. Normal Infrastructure and Anomaly Tracking Systems

• a. The Patient
  • i. Sample patient fraud scenarios
  • ii. Data management considerations
  • iii. The untold story
• b. The Provider
  • i. Sample provider fraud scenarios
  • ii. Data management considerations
  • iii. The untold story
• c. The Payer
  • i. Sample payer fraud scenarios
  • ii. Data management considerations
  • iii. The untold story
• d. Organized Crime
  • i. Sample organized crime fraud scenarios
  • ii. Data management considerations
  • iii. The untold story
• e. Normal Infrastructure and Anomaly Tracking Systems Overview: Implications for Prevention, Detections, and Investigation

XI. Components of the Data Mapping Process

• a. What Is Data Mapping?
• b. Data Mapping Overview: Implications for Prevention, Detection, and Investigation

XII. Components of the Data Mining Process

• a. What is Data Mining?
  • i. Data mining in healthcare
  • ii. Components of the data mining process within the HCC
• b. Data Mining Overview: Implications for Prevention, Detection, and Investigation

XIII. Components of the Data Mapping and Data Mining Process

• a. Forensic Application of Data Mapping and Data Mining
• b. Data Mapping and Data Mining Overview: Implications for Prevention, Detection, and Investigation

XIV. Data Analysis Models

• a. Detection Model
  • i. Pipeline Application
  • ii. Detection Model Application
• b. Investigation Model
• c. Mitigation Model
• d. Prevention Model
• e. Response Model
• f. Recovery Model
• g. Data Analysis Model Overview: Implications for Prevention, Detection, and Investigation

XV. Clinical Content Data Analysis

• a. What Is SOAP?
• b. The SOAP Methodology
• c. Electronic Records
• d. Analysis Considerations with Electronic Records
• e. Narrative Discourse Analysis
• f. Clinical Content Analysis Overview: Implications for Prevention, Detection, and Investigation

XVI. Profilers

• a. Fraud and Profilers
• b. Medical Errors and Profilers
• c. Financial Errors and Profilers
• d. Internal Audit and Profilers
• e. Recovery and Profilers
• f. Anomaly and Profilers
• g. Fraud Awareness and Profilers
• h. Profiler Overview: Implications for Prevention, Detection, and Investigation

XVII. Market Implications

• a. The Myth
• b. “Persistent”
• c. “Persuasive”
• d. “Unrealistic”
• e. The Types of Healthcare/Insurance fraud
• f. Market Overview: Implications for Prevention, Detection, and Investigation

XVIII. Conclusions

• a. Micromanagement Perspective
• b. Micromanagement Perspective
• c. Overview of Prevention, Detection, and Investigation

I. Market Background

• a. E – Health
• b. How Is Electronic Health Information Created?
• c. Information Technology Considerations
• d. Review of Primary HCC Market Players
  • i. Patients
  • ii. Providers
  • iii. Third-party vendors
  • iv. Payers
• e. Review of HCC Market Players
• f. Major Initiative for E – Health
• g. Audit Implication Overview

II. Industry Applications

• a. Public Uses
• b. Private Uses
• c. Information Continuum
• d. Market Standards and Initiatives
• e. Agency for Healthcare Research and Quality
• f. Health Level Seven
• g. Certification Commission for Healthcare Information
• h. Technology
• i. Department of Defense Records Management Program
• j. Association of Records Managers and Administrators
• k. Audit Implication Overview

III. Impact of E – Health on Case Management

• a. Financial Picture
• b. Hospital-based FCM Application
  • i. Background information and provider perspective
  • ii. Problem: Getting paid correctly for services provided
  • iii. Findings
  • iv. Additional findings
  • v. Summary
• c. Consumer-based FCM Application
• d. Market Problems: The Industry as It Operates Today
• e. Consumer FCM Model
• f. Healthcare Portfolio Application
• g. Virtual Case Management
  • i. VCM Payer Model
  • ii. VCM Patient Model
  • iii. VCM Hospital Model
  • iv. VCM Physician Model
  • v. VCM Allied Health Services
  • vi. VCM Nontraditional Health Services Model
• h. Audit Implication Overview

IV. Data in an E – Health Environment

• a. Data Library
• b. Data Intelligence
• c. New Data
• d. More New Data
• e. Processed Data
• f. Data Warehouse
• g. Audit Implication Overview

V. Algorithms

• a. Background
• b. Understand Algorithms
• c. Data Elements
• d. Case Study
• e. Algorithm Selection
• f. Auditor Implication Overview

VI. Data-driven Health Decisions in an E – Health Environment

• a. Knowledge Models
  • i. Primary Healthcare Continuum
  • ii. Secondary Healthcare Continuum
  • iii. Information Continuum
• b. Third-party Vendor Knowledge Model
• c. Knowledge Models for White-collar and Organized Crime
• d. Sample Identity Theft Case
• e. Medical Identity Theft
• f. How Medical Identity Theft Occurs
• g. Damages to Primary Victims
• h. Medical Identity Theft from a Consumer Perspective
  • i. When the consumer is not aware
  • ii. When the consumer is involved
  • iii. When an individual wants products or services
• i. Damages to Secondary Victims
• j. Medical Identity Theft from an Entity’s Perspective
• k. Auditor Considerations
• l. Sample Fraud Case
• m. Sample Pharmaceutical Fraud Case
• n. Audit Implication Overview
• o. Examples of Worldwide Activity

VII. Analytic Tools and Audit Checklists

• a. E – Health and Healthcare Business Processes
• b. Patient Business Process
  • i. Problem #1: Financial Case Management Advocacy
  • ii. Problem #2: Clinical Case Management Advocacy
• c. Provider Business Process
  • i. Problem #1: Lack of Electronic Internal Controls
  • ii. Problem #2: Lack of Internal Controls with User Identity
  • iii. Problem #3: Lack of Internal Controls for Services Provided and Charged
• d. Payer Business Process
  • i. Problem #1: Use and Loss of Health Information – Handling Subcontracted Vendors
  • ii. Problem #2: Lack of Insurance – Processing Fraudulent Claims for Enrolled Beneficiaries
• e. Plan Sponsor Business Process
  • i. Problem #1: Employee Working Environments
  • ii. Problem #2: Employer Increase in Healthcare Expenditures
• f. Third-party Vendor Business Process
  • i. Problem: Increase in Pharmaceutical Expenditures
• g. Audit Implication Overview

VIII. Electronic Health Records

• a. Current E – Health Offerings
• b. Market Evolution
• c. E – Health Content Standards
• d. E – Health Offering Vulnerabilities
• e. Audit Implication Overview

IX. Healthcare Portfolio

• a. Health Infomediary Support
• b. PHR Attributes
• c. Future Considerations
• d. Major Market Activity
• e. Compulsory Insurance Program: i.e. Medicaid & Medicare Fraud, Government sponsored Canada, and Germany
• f. Audit Implication Overview

X. Conclusions

• a. Market Overview
  • i Market standards
  • ii. Market conflicts
  • iii. Market intelligence
  • iv. Market audits
  • v. Market directions
• b. Consumer Response to PHRs
• c. Audit Implication Overview