Leveraging Innovative Technologies to Combat
Health Care Fraud
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Sponsored by the NCSL Transforming Health Care Through Technology FSL Partners Project
Leveraging Innovative Technologies to Combat
Health Care Fraud
Sponsored by the NCSL Transforming Health Care Through
Technology Foundation for State Legislatures Partners Project
Project Co-Chairs:
• Senator Richard T. Moore, Massachusetts, NCSL Immediate
Past President
• Senator Kemp Hannon, New York
Project Partners:
Agenda Co-Moderators:
• Senator Richard T. Moore, Massachusetts, NCSL
Immediate Past President
• Senator Kemp Hannon, New York
Speakers:
• Kelli Garvanian, Solutions Consultant, Emdeon Payment
Integrity Solutions, Illinois
• Kathy Mosbaugh, Director, State Government Health Care,
LexisNexis Risk Solutions, Florida
Q & A
Leveraging Innovative Technologies
to Combat Health Care Fraud
Kelli Garvanian
Kelli Garvanian is a Solutions Consultant with Emdeon Payment Integrity
Solutions in Illinois. With more than 30 years’ experience in the healthcare
industry, Ms. Garvanian is an accredited healthcare fraud investigator, a
certified fraud examiner and a founding member of the Midwest Anti-Fraud
Insurance Association. She is former chairperson of the National Health
Care Anti-Fraud Association and has served on its executive committee and
institute board. Ms. Garvanian is active in all national anti-fraud associations,
has spoken at numerous conferences and educational seminars, and is a
recognized authority on healthcare fraud. She is a member of the
International and National Association of Special Investigation Units.
6 Emdeon Proprietary & Confidential
Emdeon‟s Ubiquitous Network We Connect All Principal Healthcare Constituents
Consumers
Patients
500,000 Physicians (~88%)
5,000 Hospitals (~88%)
81,000 Dentists (~92%) (1)
Providers
Pre-Care (Benefits and Eligibility Verification)
Claims Management / Submission
Payment and Remittance Distribution and Denial / AR Management
60,000
(~100%)
Pharmacies
Pharmacies
Payers Connections and Solutions All Facilitated by Emdeon
Medicare
Medicaid
Blue Cross/Blue Shield
1,200 Commercial Plans
(~100%)
Positioned to Drive Healthcare from Paper-Based to Electronic Transactions
Note: (1) Based on electronic claim submitting dentists
7 Emdeon Proprietary & Confidential
State Issues and Concerns
• 46 States are forecasted to have declining revenues in 2012
• Increasing Medicaid populations
• Prevalence in fraudulent activity
• High cost of recovering “pay and chase” fraud dollars
• Continued staff reductions and budget cuts in fraud service areas
• Less public visibility and outcry to cut “back office” administration
vs. education and other direct services
• Regulations which do not allow for dollars saved under fraud
detection & prevention programs to fund the programs themselves
8 Emdeon Proprietary & Confidential
Ted Clark, Director Kansas Fraud Bureau and working Chair of anti-fraud committee of the NAIC “You would think that when the economy is tough and fraud by opportunists is increasing, that the states would devote more resources to fraud. But that isn‟t happening.” Chuck Gregory, Head of Fraud Unit, Arizona “There‟s a lot of fraud going on, and not having manpower is a very big problem. On a lot of cases we‟re doing, we‟re just putting out fires and working off of case referrals that are coming in. The rest are going by the wayside.”
9 Emdeon Proprietary & Confidential
Future State Current State
1 Pay and Chase
2
3
4
5
6
Government Centric
Inward Focused Communication
Stand Alone PI Programs
Legacy Processes
„One Size Fits All‟
Prevention and Detection
CMS Direction From Dr. Peter Budetti’s April 14th NCSL Spring Meeting
Risk-Based Approach
Engaged Public/Private Partners
Transparent and Accountable
Innovation
Coordinated & Integrated PI Programs
10 Emdeon Proprietary & Confidential
Putting Healthcare Fraud, Waste, and Abuse in Perspective…
Figure 1 Fair Isaac Fraud Estimates for 2004 based on data from various sources
Credit Card Fraud
Phishing
(email and web-based fraud)
Insurance Fraud
Identity Theft
Healthcare Fraud
$788M $1.2B $29B $52B $240B
11 Emdeon Proprietary & Confidential
Everyone Knows – This is a Huge Problem
“By taking the fraud, [waste], and abuse problem seriously, this
administration might be able to save 10 percent or even 20 percent from Medicare and Medicaid budgets. But to do that, one would have to spend 1 percent or maybe 2 percent (as opposed to the prevailing 0.1 percent) in order to check that the other 98 percent or 99 percent of the funds were well spent. But please realize what a massive departure that would be from the status quo. This would mean increasing the budgets for control operations by a factor of ten or twenty. Not by 10 percent or 20 percent, but by a factor of ten or twenty.”
– Harvard professor Malcolm Sparrow, May 20, 2009, testimony to United States Senate
Judiciary Committee
Before cutting benefits, before cutting budgets – Fight Fraud First
12 Emdeon Proprietary & Confidential
Mandate Comprehensive Program Integrity in 2012 Program Integrity spans the continuum from errors to abuse to outright fraud
Definition: The ability to efficiently process and accurately pay only those claims which
are valid, while removing wasted dollars in the systems and identifying aberrant claims and providers that could be fraudulent or abusive.
The breadth and depth of payment integrity are important for all healthcare constituents: payers, providers, and consumers
Fraud and Abuse
Clinical Code Editing
Coordination of Benefits
Over / Under Pmt Analytics
Subrogation
13 Emdeon Proprietary & Confidential
Why Emdeon Program Integrity Solutions? Multiple Safety Nets for a Holistic Approach
Provider Data
Validation
• Dead doctors
• Licensure • Sanctions • Address
validation
Clinical Integrity for Claims
Predictive Analytics
Fraud Detection
Rules
Investigations
• Duplicates • Unbundled
pairs • CCI Editing • Custom edits
• Known and unknown schemes
• Phantom procedures
• Overutilization • Double billing • Policy gaps
• Provider specific • Clinically
appropriate thresholds
• Specialty-specific
• Triage or full outsource
• Pend/pay/deny recommendations
• Request and review medical records
Recovery Audit
Compliance
• Medical billing guidelines
• Contractual obligations
• Reimbursement rates and policies
Perform pre-payment across entire populations
15 Emdeon Proprietary & Confidential
Predictive and Data Driven Analytics complement existing fraud detection methods
Predictive/Data-Driven
Analytics Complex fraud and abuse patterns
Undiscovered schemes
New and emerging issues
Organized Fraud
Queries/Rules Simple schemes and billing errors
Known fraud and abuse patterns
16 Emdeon Proprietary & Confidential
Predictive Analytics & Residual Analysis
• Take large volume of historical claims data
• Look at each patient visit using quantitative input (variables)
o E.g. procedure code, dollar amount, number of lines, age of patient, etc.
• Fit a statistical model to the data to predict how a normal visit looks for those conditions
• Find providers with visits that charge much more than the model’s prediction
• Monitor on a pre-pay basis to see if providers continue the same pattern
• Sound mathematical basis prevents personal bias against specialties or individual providers
• Identifies known and unknown schemes before payment is made
Electronic Claims Data
• Patient visits
• Quantitative criteria
Statistical model
• Predicts “normal” behavior
• Finds providers/visits that deviate
Providers and patterns to monitor
• Investigate suspect claims identified by model
• Stop fraud and overpayment before it happens
17 Emdeon Proprietary & Confidential
Just Another Example: DME
Examples:
• Diabetic supplies
• Wheelchairs
• Walkers
• Bath benches
• Respiratory equipment
• Crutches
• Scooters
What is DME?
Durable Medical Equipment is equipment that primarily serves a
medical purpose, is designed for repeated use, and can be used
in the home.
• Ramps
• Cold compression units
• Hospital beds
Why DME Fraud?
• High-cost items (potential for quick profits) • High percentage of use by seniors • Lack of professional licensing requirements • Reliance on lack of patient awareness and cooperation • Overutilization of miscellaneous DME codes
18 Emdeon Proprietary & Confidential
DME Fraud Scenarios
Fraudulent providers obtain patient insurance information and bill for equipment never ordered or received. Common methods for suppliers to obtain this information include:
• Telemarketing scams
• Free screening offers
• Health surveys
• Illegal purchase of nursing home roster information
• Provider kickbacks
• Patients are offered free health consults. During the office visit, they are sent home with equipment they didn‟t request and/or don‟t need.
• Suppliers provide patients with medically appropriate scooters for increased mobility, but bill insurance payers for motorized wheelchairs (which are approximately double the cost of the scooters).
• Suppliers delay pickup of equipment no longer needed to try and bill for longer rental periods.
• Etc.
19 Emdeon Proprietary & Confidential
Future State Current State
1 Pay and Chase
2
3
4
5
6
Government Centric
Inward Focused Communication
Stand Alone PI Programs
Legacy Processes
„One Size Fits All‟
Prevention and Detection
CMS Direction From Dr. Peter Budetti’s April 14th NCSL Spring Meeting
Risk-Based Approach
Engaged Public/Private
Partners
Transparent and Accountable
Innovation
Coordinated & Integrated PI
Programs
Emdeon‟s Solutions
20 Emdeon Proprietary & Confidential
What Can You as Legislators Do?
Ensure you have adequate legislation in place to address the problem. The legislation should include/ensure:
• Funding for Program Integrity can be generated from the Medical dollars saved
• Mandates to accelerate all aspects of Section 6028, regardless of the challenges to Healthcare Reform
o Fraud isn’t going away – Fight Fraud First
• Use of comprehensive, state-of-the art technology to minimize false positives and manual resource requirements
• Move to a prospective detection position, eliminating the “pay-and-chase”
Consider a total population approach – mandating the use of a prospective, predictive analytics detection system for maximum efficiency, regardless of beneficiary enrollment in public or MCO run benefit programs
Understand that cutting budgets and doing nothing is a blank check to your coffers
o Perpetrators of fraud are savvy and move to less restrictive areas
o When one State acts, those that don’t are impacted
Leveraging Innovative Technologies
to Combat Health Care Fraud
Kathy Mosbaugh
Kathy Mosbaugh is Director of State Government Health Care for LexisNexis Health
Care Solutions. In her current role, Ms. Mosbaugh works with government health care
agencies to identify opportunities where information-rich analytic tools can be
leveraged to address the key challenges of health information exchange, fraud, waste
and abuse and identity management. Prior to her current position, Ms. Mosbaugh held
several positions within Reed Elsevier’s Clinical Decision Support division involving
projects such as chronic disease management, medication reconciliation, quality
measurement (pay-for-performance) reporting, and health data standards. Ms.
Mosbaugh has more than a decade of experience in developing health information
technology solutions including ICERx.org, a national collaboration to support the
continuity of care for patients affected by a disaster. Ms. Mosbaugh holds a Masters
degree in public health from University of South Florida.
Leveraging Innovative Technologies to Combat Health Care Fraud Kathy Mosbaugh, Director State Government Health Care
NCSL Webinar 2012
Boston Herald, October 30, 2011 “Four alleged schemes to defraud MassHealth of $10 million were uncovered after a months long investigation by the Attorney General that found agencies billing taxpayers for care to dead people, widespread kickbacks, or exaggerated claims, prosecutors said.”
Paying for Care to Dead People
Hartford Courant, June 11, 2012 “Federal authorities said Monday they have indicted an unlicensed dentist charged previously with using hidden ownership in a string of Connecticut clinics to steal more than $20 million in dental benefits from low-income families. ….with offenses related to his involvement in a Medicaid fraud scheme. At the time of his arrest, he was charged with fraud. The subsequent indictment, a common occurrence in such cases, accuses him in greater specificity of conspiracy, health care fraud, two counts of wire fraud, four counts of making false statements to the government in connection with its Medicaid program, and concealing a prior arrest for health care fraud in Massachusetts.”
Copyright © 2012 LexisNexis. All rights reserved.
25
“At its heart, the gang, based largely in Los Angeles, resembled a giant identity-theft ring that stole doctors’ dates of birth and Social Security and medical license numbers and paired them up with legitimate Medicare recipients, whose names and information were also stolen. About 3,000 of those patients’ names came from the Orange Regional Medical Center in Middletown, N.Y., the authorities said”.
People Committing Fraud
NY Times, October 13, 2010 “By inventing 118 bogus health clinics in 25 states, prosecutors said, a band of Armenian-American gangsters billed Medicare for more than $100 million, and managed to collect $35 million over at least four years. Preet Bharara, the United States attorney in Manhattan, called it the “single largest Medicare fraud ever perpetrated by a single criminal enterprise.”
Eighteen people were charged in the Medicare indictment unsealed on Wednesday, part of a larger ring of 44 people prosecutors said had engaged in a variety of swindles, including bilking auto insurance companies by falsifying, staging or exaggerating the severity of fender-benders. Charges included racketeering, health care fraud, identity theft, money laundering and bank fraud. Forty-one of the defendants had been arrested as of Wednesday afternoon.
Copyright © 2012 LexisNexis. All rights reserved.
26
Accounts for approximately 3% of all identity crimes and is 10 times more expensive1
• Average payout for regular identity theft is $2,000 • Average payout for medical identity theft is $20,000
According to World Privacy Forum, stolen medical information has 50 times more street value than a stolen social security number2
• Street cost for stolen social security number is $1.00 • Street cost for stolen medical identity information is $50.00
Anyone with medical insurance is a potential victim
Scope of Medical Identity Theft Problem
1AHIMA e-HIM Work Group on Medical Identity Theft. "Mitigating Medical Identity Theft." Journal of AHIMA 79, no.7 (July 2008): 63-69. 2Dixon, Pam. World Privacy Forum. USA Today interview. 02/12/2012. http://www.usatoday.com/news/health/story/health/story/2012-02-12/Data-breaches-put-patients-at-risk-for-identity-theft/53065576/1
Copyright © 2012 LexisNexis. All rights reserved.
27
Incidence of Medical Identity Theft in the U.S.
Red dots indicate the number of medical identity theft incidents reported in a given area. The larger the dot, the more reported incidents. Source: World Privacy Forum Interactive Map. http://www.worldprivacyforum.org/medicalidentitytheft-map.html
Incidence of Medical Identity Theft in the U.S.
Copyright © 2012 LexisNexis. All rights reserved.
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Types of Medical Identity Theft Large-scale organized crime where information about large group of individuals
is fraudulently submitted for reimbursement of goods or services never received by the individual
• Generally perpetrated by someone within the health care delivery system or someone presenting themselves as operating from within the system
• Majority of all medical identity thefts fall into this category
An individual’s purse or wallet is lost or stolen and the thief or person who finds it uses the individual’s information to obtain medical goods or services
An individual “loans” an uninsured friend or family member their medical ID information so that they may receive medical goods or services that would otherwise be unavailable to them
Types of Medical Identity Theft
Copyright © 2012 LexisNexis. All rights reserved.
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Commercial and government health care organizations are seeking to provide controlled, secure access to their products, services and information
Key Challenges
Copyright © 2012 LexisNexis. All rights reserved.
30
Transform the “Pay and Chase” status quo by looking to other industries, private sector for successful approaches and technologies:
• Identity Proofing/Verification • Predictive Claims Analytics
Greater focus on the individuals and entities in the program
• Are beneficiaries enrolling who they claim to be? • Have they disclosed all assets, income, correct state of residence, etc? • What are the true backgrounds of the practitioners, officers, agents, etc? • What is the risk profile of a provider based on background, associations, etc.? • What significant events are occurring between enrollment periods?
How Do States Proactively Address Fraud
Copyright © 2012 LexisNexis. All rights reserved.
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How Does It Work
Government
Background Screening
Collections
Legal
Insurance
Financial Services
Who are you?
Where are you?
Who are you related to, and how?
How much of a risk do you present?
Identity Proofing/Verification Health Care
Assess the risks and opportunities associated with people, businesses and assets.
Data
250M+ unique individuals
1B unique business
contacts
Analytics
30M transactions/hr
<500 millisecond avg search response time
~34 Terabytes in use
Computing
Real time analytics Scores to support customer workflow for remote
transactions Scores around individual
risk/ opportunity
Linking
34 billion public records
1 million documents
added every day
36,000 legal, business, news
sources
Copyright © 2012 LexisNexis. All rights reserved.
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Big Data as the Starting Point
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ENTITY RESOLUTION
LINK ANALYSIS
CLUSTERING ANALYSIS
COMPLEX ANALYSIS
PUBLIC RECORDS
PROPRIETARY DATA
NEWS ARTICLE
UNSTRUCTURED RECORDS
STRUCTURED RECORDS
Copyright © 2012 LexisNexis. All rights reserved.
Public Records and External Data for Prevention
Reduces beneficiary fraud and ensures accuracy of identity information for
program efficiency and risk mitigation
In a recent analysis of a Medicaid beneficiary file:
• over 2% of beneficiaries had a primary address in another state
• 0.59% were deceased
• 2% of adults presented with severe identity fraud risk
Test Criteria Fraud Risk
Deceased High
Identity Fraud Risk High
Incarcerated High
Occupancy Outside State High
Real Property Value and Ownership Medium
Motor Vehicle Age and Ownership Medium
High Risk Address Medium
Copyright © 2012 LexisNexis. All rights reserved.
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Test Criteria Fraud Risk
Deceased High
HHS OIG Exclusion List High
GSA Exclusion List High
Felony conviction High
State of Licensure, status Medium
Known Associates Excluded Medium
Maintains visibility into provider risk
In a recent analysis of a Medicaid provider file:
Over 1% were deceased
1.7% of providers were sanctioned
A few providers were incarcerated
Public Records and External Data for Prevention
Copyright © 2012 LexisNexis. All rights reserved.
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Prevention by Predicting Fraudulent Claims
Claim Edits
Provider Data
Diagnosis Data
Treatment Data
Inte
rnal
(Pa
yer)
Dat
a Ex
tern
al D
ata
Claims Fraud Identification
“Provider of Interest” Identification
Subrogation Identification
Social Network Analytics
And more…
Edits
Public Records Data
Sanctions Data
Fee Schedules
PREDICTIVE MODELING
TEXT MINING
BUSINESS RULES
IDENTITY MATCHING
TEXT SEARCH
SOCIAL NETWORK ANALYTICS
VISUALIZATION
DATA SMART ORDER
USER INTERFACE
REPORTING ENGINE
SCORING ENGINE
DATA MART
DATA EXCHANGE
FUN
CTI
ON
AL
CO
MP
ON
ENTS
ST
RU
CTU
RA
L C
OM
PO
NEN
TS
Copyright © 2012 LexisNexis. All rights reserved.
37
Fraud is hidden in a sea of valid
claims
Without Anything
With Predictive Modeling
Fraud
High
Low
CLAIM
NUMBER
SUSPICION
SCORE ADJUSTOR STATE
144618 993 UF NJ
138514 991 YN NJ
143949 989 UE NJ
145594 988 YZ NJ
148531 986 UJ PA
152506 983 LB AR
152787 982 UL PA
146937 981 UL PA
157651 976 WH PA
141970 973 J0 LH LT MD
152271 970 93 06 MA
138703 969 YS NJ
149491 968 59 RI
139439 963 YQ NJ
158952 950 34 MA
149319 948 YX NJ
152602 945 UN PA
152793 944 YT NJ
155448 943 YV NJ
Some fraud is captured but
much is missed
With Rules
Create the target rich environment
Predictive analytics provides a score for each claim, policy, etc., allowing activity to be concentrated on areas that have the highest probability of financial return
Claim Scoring Using Predictive Models
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38
Using Public Records and External Data to Improve Detection
A top insurer flagged 7 claims as “collusion claims”
Using carrier data alone, there was a connection between 2 of the 7 claims.
Copyright © 2012 LexisNexis. All rights reserved.
39
Family 1
Family 2
Collusion AFTER Advanced Linking Technology is Applied Assigned unique IDs to all parties and added 2 additional degrees of relative data
Showed 2 family groups interconnected on the 7 original claims plus linked to 11 more
Using Public Records and External Data to Improve Detection
Copyright © 2012 LexisNexis. All rights reserved.
40
Support proactive strategies to reduce fraud and increase cost savings:
• Identity Proofing/Verification Services for Enrollees • Identity Proofing/Verification and Screening for Providers • Pre-Payment Predictive Modeling for Claims Processing
Make Identity Verification Services a state priority:
• Beneficiary Eligibility Systems • Medicaid Provider Enrollment • Medicaid Program Integrity • Health Insurance Exchanges • Health Information Exchanges
Where to Start
Copyright © 2012 LexisNexis. All rights reserved.
41
KATHY MOSBAUGH DIRECTOR, STATE GOVERNMENT HEALTH PROGRAMS
LEXISNEXIS RISK SOLUTIONS [email protected]
813-418-2035 813.418.2035
Thank You
42
Please type your questions in the Q & A box at the bottom right corner of your screen.
Note: This webinar will be archived and will be available for viewing within about one week on the NCSL Transforming Health Care Through Technology website: www.ncsl.org/default.aspx?tabid=24777.
Leveraging Innovative Technologies
to Combat Health Care Fraud
Transforming Health Care Through
Technology Project
The Transforming Health Care Through Technology project recognizes the
important role of states in promoting emerging technologies aimed at improving
health care delivery.
To view the archived webinar, visit
www.ncsl.org/default.aspx?tabid=24777
For additional information and project resources, visit:
www.ncsl.org/default.aspx?tabid=22228
NCSL contacts:
Jo.Anne.Bourquard and Pam Greenberg, NCSL Denver Office
James Ward, NCSL Washington D.C. Office
303-364-7700 / 202-737-1069
NCSL's Medicaid Fraud & Abuse Contact:
Megan Comlossy [email protected]
303.856.1389
NCSL Medicaid Fraud & Abuse Resources: • Medicaid Fraud & Abuse Overview • Containing Medicaid Costs: State Strategies to Fight Medicaid
Fraud and Abuse, NCSL Webinar Archive • Confronting Costs & Medicaid Fraud Fighters, State
Legislatures Magazine