Healthcare Fraud: Auditing and Detection Guide » (1st Edition)

Rebecca S. Busch, RN, MBA, CCM, CBM, CHS-III, CFE, FHFMA, is President and CEO of Medical Business Associates, Inc., a consulting firm specializing in healthcare audits for employers, hospitals, and insurance companies. She has over twenty years of achievement in the healthcare management industry. She is a faculty member of the Association of Certified Fraud Examiners (ACFE), has published numerous articles, and is a frequent public speaker.

Healthcare Fraud

Auditing And Detection Guide

According to private and public estimates, approximately $24 million is lost per hour to healthcare waste, fraud, and abuse. Still, the impact of healthcare fraud cannot be measured in terms of dollars alone. In addition to burdening the nation with enormous financial costs, it also threatens the quality of healthcare and steals the very essence of human life.

A must-have reference for auditors, fraud investigators, and healthcare managers, Healthcare Fraud: Auditing and Detection Guide provides tips and techniques to help readers spot the "red flags" of fraudulent activity and reveals the steps to take when fraud is suspected.

Clearly structured to identify what is normal at any point in the healthcare continuum on both individual and cumulative scales, this timely guidebook helps auditing professionals in the healthcare industry to sharpen their fraud detection skills to see beyond the eclipse created by healthcare fraud. Healthcare Fraud: Auditing and Detection Guide features:

• Comprehensive guidance on auditing and fraud detection for healthcare providers and company healthcare plans
• A look at how data mapping and mining can be used as a key tool to maximize both the effectiveness and efficiency of fraud investigations
• Insightful discussion from a number of perspectives—clinical, research, internal audit, investigative, data intelligence, and forensic
• Building blocks for understanding the entire healthcare market and its respective players
• Cases and methodologies providing actual audit and investigative tools
• Useful outlines of healthcare fraud prevention, detection, and investigation methods

Healthcare Fraud: Auditing and Detection Guide serves as an invaluable tool equipping healthcare professionals, auditors, and investigators to detect every kind of healthcare fraud, from false statements and claims to elaborate collusive schemes.

Preface     xiii
Acknowledgments     xvii
Introduction to Healthcare Fraud     1
What Is Healthcare Fraud?     2
What Does Healthcare Fraud Look Like?     4
Healthcare Fraud in the United States     8
Healthcare Fraud in International Markets     9
Who Commits Healthcare Fraud?     10
What Is Healthcare Fraud Examination?     11
The Healthcare Continuum: An Overview     13
Healthcare Fraud Overview: Implications for Prevention, Detection, and Investigation     14
Defining Market Players within the Healthcare Continuum     17
The Patient     18
Who Is the Patient?     18
What Are Some Examples of Patient Fraud?     22
How Does the Patient Role Relate to Other Healthcare Continuum Players?     23
The Provider     23
Who Is the Provider?     23
What Are Some Examples of Provider Fraud?     33
How Does the Provider Role Relate to Other Healthcare Continuum Players?     35
The Payer     35
Who Is the Payer?     35
What Are Some Examples of Payer Fraud?     38
How Does the Payer Role Relate to Other Healthcare Continuum Players?     41
The Employer/Plan Sponsor     42
Who Is the Employer/Plan Sponsor?     42
What Are Some Examples of Employer/Plan Sponsor Fraud?     43
How Does the Employer/Plan Sponsor Role Relate to Other Healthcare Continuum Players?     43
The Vendor and the Supplier     44
Who Are the Vendor and the Supplier?     44
What Are Some Examples of Vendor and Supplier Fraud?     44
How Do the Vendor and Supplier Roles Relate to Other Healthcare Continuum Players?     44
The Government     45
Who Is the Government?     45
What Are Some Examples of Government Fraud?     45
How Does the Government Role Relate to Other Healthcare Continuum Players?     46
Organized Crime     46
Who Is Organized Crime?     47
How Does the Organized Crime Role Relate to Other Healthcare Continuum Players?     48
Market Players Overview: Implications for Prevention, Detection, and Investigation     48
Protected Health Information     51
Health Insurance Portability and Accountability Act of 1996     51
Audit Guidelines in Using PHI     52
Protected Health Information Overview: Implications for Prevention, Detection, and Investigation     54
Health Information Pipelines      57
The Auditor's Checklist     57
What Are the Channels of Communication in a Health Information Pipeline?     58
The Patient     58
The Provider     60
The Payer     61
The Employer/Plan Sponsor     63
The Vendor/Supplier     65
The Government Plan Sponsor     66
Unauthorized Parties     67
HIP Overview: Implications for Prevention, Detection, and Investigation     69
Accounts Receivable Pipelines     71
Overview of Healthcare Reimbursement     72
Types of Reimbursement Models     74
Fee-for-Service Model     74
Prospective Model     74
Capitation-Structured Model     77
Data Contained in Accounts Receivable Pipelines     77
Accounts Receivable Pipelines by HCC Player     79
The Patient     80
The Provider     84
The Payer     87
The Employer/Plan Sponsor     92
Others     95
ARP Overview: Implications for Prevention, Detection, and Investigation     99
Operational Flow Activity     101
Operational Flow Activity Assessment     101
The Patient      102
The Provider     103
The Payer     103
The Employer     105
The "Other"     107
OFA Overview: Implications for Prevention, Detection, and Investigation     108
Product, Service, and Consumer Market Activity     109
Product Market Activity     110
Service Market Activity     111
Consumer Market Activity     112
PMA, SMA, and CMA Overview: Implications for Prevention, Detection, and Investigation     120
Data Management     123
Data Management     124
Market Example: Setting Up a Claims RDBMS     128
Data Management Overview: Implications for Prevention, Detection, and Investigation     129
References     129
Normal Infrastructure     131
Normal Profile of a Fraudster     132
What Types of People or Entities Commit Fraud?     132
What Is the Key Element of a Fraudster?     133
Anomalies and Abnormal Patterns     134
Normal Infrastructure Overview: Implications for Prevention, Detection, and Investigation     135
Normal Infrastructure and Anomaly Tracking Systems     137
The Patient     137
Sample Patient Fraud Scenarios      138
Data Management Considerations     139
The Untold Story     139
The Provider     139
Sample Provider Fraud Scenarios     140
Data Management Considerations     142
The Untold Story     142
The Payer     143
Sample Payer Fraud Scenarios     144
Data Management Considerations     145
The Untold Story     145
The Vendor/Other Parties     146
Sample Vendor/Other Fraud Scenarios     147
Data Management Considerations     148
The Untold Story     149
Organized Crime     150
Sample Organized Crime Fraud Scenarios     150
Data Management Considerations     151
The Untold Story     151
Normal Infrastructure and Anomaly Tracking Systems Overview: Implications for Prevention, Detection, and Investigation     152
Components of the Data Mapping Process     153
What Is Data Mapping?     153
Data Mapping Overview: Implications for Prevention, Detection, and Investigation     158
Components of the Data Mining Process     159
What Is Data Mining?     159
Data Mining in Healthcare     160
Components of the Data Mining Process within the HCC     161
Data Mining Overview: Implications for Prevention, Detection, and Investigation     162
Components of the Data Mapping and Data Mining Process     165
Forensic Application of Data Mapping and Data Mining     167
Data Mapping and Data Mining Overview: Implications for Prevention, Detection, and Investigation     170
Data Analysis Models     173
Detection Model     173
Pipeline Application     175
Detection Model Application     176
Investigation Model     176
Mitigation Model     181
Prevention Model     182
Response Model     189
Recovery Model     194
Data Analysis Model Overview: Implications for Prevention, Detection, and Investigation     204
Clinical Content Data Analysis     207
What Is SOAP?     208
The SOAP Methodology     209
Electronic Records     225
Analysis Considerations with Electronic Records     226
Narrative Discourse Analysis     229
Clinical Content Analysis Overview: Implications for Prevention, Detection, and Investigation     237
Profilers     239
Fraud and Profilers     239
Medical Errors and Profilers     244
Financial Errors and Profilers     249
Internal Audit and Profilers     253
Recovery and Profilers     256
Anomaly and Profilers     257
Fraud Awareness and Profilers     259
Profiler Overview: Implications for Prevention, Detection, and Investigation     260
Market Implications     261
The Myth     261
"Persistent"     264
"Persuasive"     265
"Unrealistic"     266
Market Overview: Implications for Prevention, Detection, and Investigation     268
Conclusions     271
Micromanagement Perspective     271
Macromanagement Perspective     278
Overview of Prevention, Detection, and Investigation     279
Index     283