Innovative Fraud Detection at CMS Mike Doane, Technical Director Federal Healthcare April 10, 2013

Agenda

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Fraud Characteristics CMS Requirements MarkLogic POC Functionality Use Cases Future Capabilities Q&A

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Healthcare Fraud is Huge FY 2012 90 80 70 60 50 40 30 20 10 0

$B

80

4.2 Total Fraud (FBI Est.) Amount Recovered

New approaches to detection are needed Slide 8

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1.6 Spending on Recovery

What does fraud look like?

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False storefronts Beneficiary shopping (compromised benes) Networks of fraudsters Ambulance trips – no check-in Home health Double-billing DME proliferation ID theft Prescriptions (forged, resold, etc.) Upcoding Kickbacks

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Today’s Approach

 Sharding of databases by states and territories  Manual correlation across states  Multiple versions of algorithms  Looking at only the claims  Looking at these claims well after they’ve been submitted  Not incorporating other available sources  Not sharing results

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CMS Asked For

 Scalability to evaluate the entire country’s data as a single, unified data set  The Agility and Flexibility needed to keep up with changing data sources and evolving data analysis strategies  Better Performance - a shorter Time To Market for its data  Facilitation of Enterprise Data Sharing within CMS and with CMS partners

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Scalability

Over 600M documents, 4+TB in the POC Deliver a 300TB+ cluster and eliminate sharding of data by geography Fifty states plus six territories Unknown additional sources

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Agility and Flexibility

Load data as-is Handle combination of full text (unstructured) and structured data Support in-line data descriptions or enrichment Allow composable queries across all data  Full-text search, geospatial constraints, and traditional and fielded constraints all in the same query

Handle Unpredictability  New data of any type readily incorporated without schema changes – indictment docs, Dunn & Bradstreet, Facebook, Property records

Support flexible Provider and Beneficiary profiles

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Flexible Profiles Provider

NPI

Associations

Beneficiary

Metadata

Statistics Assoc Hosp RxCount

Assoc -Prov

Providers Visit Bill-Amt

Addresses InclusionAddress reason

ID

Address Address

Benedistance

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Annual Billings

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Early- Distance TopschedII refill -Rx

Flexible Profiles Provider

NPI BoardMember Assoc Hosp RxCount

Associations

Beneficiary

Providers

Metadata

Statistics

Visit

Assoc -Prov

Exclusion

Addresses InclusionAddress reason

ID

Bill-Amt

Address Address

Benedistance

MRIcount Slide 15

Annual Billings

DEA

Indictment

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Early- Distance TopschedII refill -Rx

PersonalProperty Auto House $-value

Ambulancecount

$-value

Performance – Time to Market

Operate on valid and contemporary data Handle multiple disparate data sources with varying schemas  Enrich in place by reference and related data sources Architect for performance and flexibility  Distribute loading across servers in the cluster  No model changes for new incoming formats  Database and Data Warehouse are the same – no data staging between products

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Enterprise Data Sharing

Support direct data access from external systems  Connectivity via Java API, REST API, .NET, ODBC/SQL Facilitate sharing data back to the states or other parties  Expose data via SOAP or REST web services Provide efficient transformation of data to meet third party required exchange formats

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MarkLogic Delivered SAS, Excel

Fraud Review Application

Alerting

APS

Load data “as is”

MSIS Claims

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MDEM Claims

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NPI

Reference Data

Indictments

SAS AFRs

POC Functionality

 Provider and Beneficiary Profiles  Search  Detailed Views  Easy Risk Scoring

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Granular State Policy Document Search Contextual Enrichment of Alerts Incorporation of External Alerts Co-occurrence Analysis Link Analysis Geospatial Analysis

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Link/Network Analysis

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Geospatial Enrichment & Analysis 1214 Main Austin TX 98143

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State Policy Documents

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Contextual Enrichment of Alerts

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POC Findings

 Aberrant behavior based on NPI registration  Compromised beneficiaries  Value of external data sources to support link analysis  Aberrant behaviors based on high billings  Aberrant behaviors based on high procedure codes  Aberrant behaviors based on geospatial data  Providers that should have been excluded based on sanctions, exclusion lists Slide 24

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Use Case 1: Provider Profiles Clifford Ubani

NPI registration (data enrichment) Address coordinates Dunn & Brad Street incorporation (external data sources) Ability to link additional participants (unknown players)

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Profile of Clifford Ubani – Multiple NPI Clifford Ubani

Family Health Services 8313 Soutwest Fry, Suite 109 Houston, TX Home Health

Directcare Link 8313 Southwest Fry, Suite 113 Houston, TX DME

Family Health Services (Family DME) 8313 Southwest Fry, Suite 113 Houston, TX DME

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St. Michaels EMS 9896 Bissonet St. Suite 340 Houston, TX Ambulance

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Special Care 8313 Southwest Fry, Suite 215 Houston, TX DME

Ubani – Common Address

Family Health Services 8313 Southwest Fry, Suite 109 Houston, TX Home Health

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CKCC 8313 Southwest Fry, Suite 109 Houston, TX Home Health

Ubani – Dunn & Bradstreet Dunn & Bradstreet links Clifford Ubani to:  Family Healthcare  Person of Interest – Princewill Njoku (CCK DME) 8313 Southwest Fry, suite 107

 Future EMS  Persons of Interest Monica Stahl, Franklin Godfrey, Wissam Moustafa Zanhar

 St. Michaels EMS  Person of Interest Stephen Onyechi

 Ballet Healthcare  Person of Interest Ededem Edem (Edison Medical Corporation)

 Special Care  Person of Interest Caroline Njoku

 UBA Holdings  Person of Interest Ezinne Ubani Slide 28

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Shared Beneficiaries Family Health Services and CKCC Home Health

Family Health Services DME and CKCC Home Health

Robert Hill

Robert Hill

Deborah Fenroy

Deborah Fenroy

Mitzie Wilson

Elbert McNeil

Elbert McNeil

Iva Parkhill

Iva Parkhill

Ester Dickey

Jeff Ferguson

Clarence Green

Ester B. Dickey

Esther Hunter

Clarence Green

Lee Parkhill

Esther Hunter

Ruth Johnson

Lee Parkhill

Gerald Daniels

Carolyn Schexnayder

Ruby Haywood

Ruth Johnson

Lulla Brooks

Gerald Daniels

Norma Lezine

Ruby Haywood

Morris Paul

Lulla Brooks

Zelda Paul

Norma Lezine

Dorothy Anderson

Morris Paul Zelda Paul Copyright © 2013 MarkLogic® Corporation. All rights reserved. Slide 29 Dorothy Anderson

Ubani - Medicare Indictment Medicare Indictment Document - June 20, 2010 Clifford Ubani, Ezinne Ubani, and Princewill Njoku (registered nurse) owners of Family Health Services Mary Ellen (vocational nurse) (recruiter) Rolondae Mitchel Straughter (recruiter) Caroline Njoku (recruiter) Michelle Turner (recruiter) Cynthia Garza Williams (recruiter)

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Use Case 2: Link Analysis Devon Michael Spicer Multiple NPI Brainex Consulting 1962702597

7447 Harwin Drive, Suite 217 Houston, TX 77036

Mindex Consulting 17506811466

POC Value – Linking Devon Michael Spicer multiple NPI Slide 31

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Indictment Link – Devon Michael Spicer Mobility Store

Devon Michael Spicer

Indictment

Adding external data sources – Indictments – elevates Devon Michael Spicer as Person of Interest and need to further examine his associations and ties to other Medicaid Providers

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Persons of Interest – Verona Spicer

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Linking Known Entities to Examine Aberrant Behaviors and Relationships Verona Spicer

Invision Pros Devon Michael Spicer

Elite Care Medical Services 7447 Harwin Drive, Suite 109 Houston, TX 77036 1740298868

Brainex Consulting 1962702597 Mindex Consulting 17506811466

POC Value – Linking Claims and Non Claims Data (Dunn & Bradstreet) to find Suspect relationships and billing behaviors Slide 34

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Use Case 3: Using Density Map to find “unknown” patterns and risk behaviors 8303 Southwest Freeway, Houston, Texas 7 Home Health Agencies – Do they share any beneficiaries – Any beneficiaries billed with aliases – High billable procedure codes  Coastal Medical Services – 1144305004 509249318 DANIELLE HAMILTON Coastal Medical Services 1144305004 510322382 DANNY HAMILTON Coastal Medical Services 1144305004 513606514 DE A HAMILTON Coastal Medical Services  Houston Optimum Care Associates – 1144305004 512127894 ROBERTHA COX Coastal Medical Services 1740300540 512127894 ROBERTHA COX Houston Optimum Care Associates – Suspicious Doctor – Doctor Emanuel Nwora – Vestibular Diagnostic Codes – one patient billed 800 times Slide 35

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What’s Next  More States, more claims, more fields provided  Enrichment of provider’s notes

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A better format for data delivery Additional Data Sources Access DMV and home ownership records Hadoop integration Enhance algorithms with profiles – run as UDFs Leverage Semantic Tech  Store Provider to Provider and Beneficiary to Provider as triples  Provider and Beneficiary profiles as hierarchical docs in XML  Traverse triples graph for relationships and focus using queries on profiles

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And There’s Too Much Waste Estimated Waste in US Healthcare Spending

Unnecessary Care Fraud & Abuse Administrative Inefficiency Medical Mistakes Preventable Conditions

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Any Questions?

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For More Information Mike Doane, Technical Director Federal Healthcare [email protected]

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