Leveraging Innovative Technologies to Combat Health Care Fraud · Leveraging Innovative Technologies to Combat Health Care Fraud Dial: 888-437-3195 for webinar audio ... fraud detection

Leveraging Innovative Technologies to Combat

Health Care Fraud

Dial: 888-437-3195 for webinar audio

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.

5 Emdeon Proprietary & Confidential 5

Kelli Garvanian Vice President, Program Integrity

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


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


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.”


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


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


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


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


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



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


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


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


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.


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


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


Contact: Kelli Garvanian 847.597.4777

[email protected]



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

Tax Payer Dollars Are Under Attack...

Copyright © 2012 LexisNexis. All rights reserved.

24

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.”


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.


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


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.


28

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


29

Commercial and government health care organizations are seeking to provide controlled, secure access to their products, services and information

Key Challenges


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


31

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


32

Big Data as the Starting Point

33

ENTITY RESOLUTION

LINK ANALYSIS

CLUSTERING ANALYSIS

COMPLEX ANALYSIS

PUBLIC RECORDS

PROPRIETARY DATA

NEWS ARTICLE

UNSTRUCTURED RECORDS

STRUCTURED RECORDS


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


34

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


35

36

Linking People and Records Over Time


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


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


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.


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


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


41

KATHY MOSBAUGH DIRECTOR, STATE GOVERNMENT HEALTH PROGRAMS

LEXISNEXIS RISK SOLUTIONS [email protected]

813-418-2035 813.418.2035

Thank You

42

mailto:[email protected]

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.



http://www.ncsl.org/default.aspx?tabid=24777


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


http://www.ncsl.org/issues-research/health/medicaid-fraud-and-abuse.aspx

http://www.ncsl.org/issues-research/health/webinar-medicaid-fraud-and-abuse.aspx

http://www.ncsl.org/issues-research/health/webinar-medicaid-fraud-and-abuse.aspx

http://www.ncsl.org/issues-research/health/confronting-costs.aspx

Thank you!

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Leveraging Innovative Technologies to Combat Health Care Fraud · Leveraging Innovative Technologies to Combat Health Care Fraud Dial: 888-437-3195 for webinar audio ... fraud detection