WHY IDENTITY MANAGEMENT MATTERS TO MEDICAID. Clint Fuhrman National Director Government Healthcare

Transcription

1 WHY IDENTITY MANAGEMENT MATTERS TO MEDICAID Clint Fuhrman National Director Government Healthcare

2 Opportunities 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?

3 Overview of a Data Aggregation/Risk Solution Provider We assess the risks and opportunities associated with people, businesses and assets. Identity Analytics Who are you? Where are you? Who are you related to, and how? How much of a risk do you present? Health Care Background Screening Collections Financial Services Legal Government Insurance Data 34 billion public records 1 million documents added every day 36,000 legal, business, news sources Linking 250M+ unique individuals 1B unique business contacts Analytics Real time analytics Scores to support customer workflow for remote transactions Scores around individual risk/ opportunity Computing 30M transactions/hr <500 millisecond avg search response time ~34 Terabytes in use Health Care Solutions for Commercial Payers 3

4 Data Aggregation Through our proprietary inking technology, profiles have been built on over 500 million Through proprietary inking technology, profiles have been built on over 500 million identities. Our databases have in excess of 45,000 data sources providing these updates as identities. These databases have in excess of 45,000 data sources providing these updates frequently as each data provider allows including daily, bi weekly, weekly and monthly that as frequently as each data provider allows including daily, bi weekly, weekly and monthly include, but is not limited to: that include, but is not limited to: Tri bureau Credit Header data Traditional landline and wireless Phone data Utility Files Concealed Weapons Permits Firearms & Explosive Licenses Corporation Filings Court Records Department of Corrections data Real Property Deed & Mortgages Property Professional Licenses Tax Liens & Judgments Planes & Pilots Hunting & Fishing Licenses UCC Filings Assessment DEA Controlled Vehicle Registrations SEC Filings Foreclosures Deaths Substance Licenses Marriages and Divorce Records Education Records Various Contributory Data Sources Watercraft 4

5 Utilizing Advanced Technology to Establish Identity and Risk PUBLIC RECORDS PROPRIETARY DATA ENTITY RESOLUTION NEWS ARTICLE LINK ANALYSIS UNSTRUCTURED RECORDS CLUSTERING ANALYSIS STRUCTURED RECORDS COMPLEX ANALYSIS Health Care Solutions for Commercial Payers

6 Identity Analytics Provide Valuable Insight for Health Care In real-time, data from tens of thousands of disparate sources can be brought together to form a multifaceted view that can enable health care payers to resolve, verify, and authenticate identity with 99.9% confidence

7 Create a Unique ID Advanced Linking Technology assigns a unique and persistent identifier to a person Dynamic updates as new public records are available Extremely Accurate - based on multiple public record and proprietary sources 7

8 The Role of Identity Analytics Key Challenge: Commercial, government and non-profit organizations are seeking to provide controlled, secure access to their products, services and information 8

9 Member/Beneficiary Applications Identify and verify individuals Ensure accuracy of identity information for program efficiency and risk mitigation Compliance with access to online enrollment by 2014 as mandated by the Affordable Care Act (ACA) Identity verification Knowledge-Based Authentication Individual Information Death Records Primary Address Outside of State Identity Risk Out-of-State Driver s License Property Value Greater than $500,000 Ownership of 2 or More Properties More than 2 Registered Motor Vehicles New Motor Vehicles Possible Employment Business Affiliations 9

10 Identity Management is the Framework Identity Management is traditionally defined as the security discipline that enables the right individual to: Access the right resource At the right time For the right reason Given the right circumstance Identity Management decisions impact a company s technology, customer service, marketing, sales and privacy policies. Going forward, Identity Management must also include new methods for determining if someone IS the right individual, and whether changes in identity background alter these decisions

11 ASSESSMENT ENROLLMENT Knowing Who s Participating { DISCOVER { VERIFY AUTHENTICATE EVALUATE ALERT Discover the identity Undertake data capture, identity resolution and identity enrichment. Tell us who you are. Verify the identity Establish that the identity exists. Does Bob Jones exist? Authenticate the identity Determine whether an individual or business owns the identity. Are you Bob Jones? Evaluate the identity Assess against legislation, regulations and rules to determine if an individual or business meets regulatory requirements. Alert to identity changes Receive notification when an individual or business is exhibiting high-risk behavior (continuous evaluation). Copyright 2012 LexisNexis. All rights reserved.

12 Identity Verification Solutions Help to confirm the validity of a customer s identity and address identity protection compliance requirements. Searches billions of reliable identity records in each verification search to give up-todate results Includes comprehensive built-in logic that considers changes of address, data input errors and name changes to reduce false positives and improve verification accuracy Uses identity validation to confirm the data is real, while the verification confirms the data pieces belong together to fit the applicant Summarizes results in an easy-to-interpret 0-50 index. The higher the result the more verified the data 12

13 Identity Verification Solutions Use configurable verification checks designed for specific business process to help determine if an identity exists. Searches billions of reliable identity records in each verification search to give up-to-date results Users can select from a series of checks to meet their business rules, including: Name/Driver s License Number match Address occupancy and ownership SSN verification Age verification (with Instant Age Verify) Users determine the number of verification checks needed for a passing outcome Seamlessly integrates into workflow Users can access transaction-level reporting export data into their internal reporting processes 13

14 Authentication Solutions Knowledge-Based Authentication quiz helps to establish the ownership of the identity in real-time, greatly reducing the likelihood of fraud during higher risk transactions. Dynamic knowledge-based authentication (KBA) question and answer process Increases identity assurance during account setup and other high risk activities Allows authentication efforts to be uniform across customer contact channels Minimizes the impact to customer experience with a less invasive and more customizable approach Uses questions that are easy for consumers to answer and difficult for fraudsters to analyze Multiple configuration options and numerous question types Flexible language offerings for bilingual call center representatives 14

15 Examples Florida Department of Children and Families Pre-Enrollment Identify Verification and Authentication Services for Beneficiaries Prior to starting the eligibility process, individuals are verified and authenticated into the online application system. Reduces improper enrollments, increases efficiencies, and allows FL the confidence to grow the use of the system. Over 90% of applications received through the FL ACCESS system are received online. Massachusetts Health Connector Identity and residency verification for health insurance applicants Prior to starting the enrollment process, individual identities are verified and addresses are confirmed as being in Massachusetts and NOT a business. Reduces improper access to the Health Benefit Exchange and prepares the Health Connector for expansion under the Affordable Care Act.

16 Examples Blue Cross Blue Shield Michigan Pre-Enrollment Identify Verification and Authentication Services for Beneficiaries CVS

17 Did you know Over 40 million Americans change their address each year Six billion pieces of mail are returned as undeliverable as addressed each year The cost to the United States Postal Services is approximately $2 billion a year On average, organizations will experience an undeliverable rate of 3-5%. For some the rate will be as high as 30% For managed care organizations, Medicaid re-enrollment can drop as much as 30% due to incorrect member contact information. How much is your data costing you? 17

18 Our customers experience 5-10% of individual contact information provided by commercial carriers is incorrect % of individual contact information provided by employers is incorrect % of individual contact information provided by Medicare is incorrect % of contact information provided by Medicaid is incorrect. How much is your data costing you? 18

19 Reducing hard costs from undeliverable mail Undeliverable mail impacts many aspects of your organization, leading to reduced contact ratios, affecting collection efforts and generating higher administrative costs. On average, health plans and disease management organizations experience a 30% undeliverable rate on outgoing U.S. mail For managed care organizations, Medicaid re-enrollment can drop as much as 30% due to incorrect member contact information How much is your data costing you? 19

20 Member Data Hygiene Initial Verification of Member Contact Information Will provide monthly data feed with new MCO member contact information to ensure they have the most current information before they do initial outreach, improving member experience and contact success from the very beginning Will provide monthly data feed with existing member information on monthly basis to capture changes in contact information as quickly as possible with as little inconvenience to the member as possible Member Surveys Distributing member surveys to targeted populations to identify services that may have been received in locations other than a primary care provider s office Maximizing Personnel Resources Corrected phone information reduces the amount of time required to conduct phone blast campaigns, making this a more effective outreach program than it had been in the past HEDIS/Medicare Five Star Rating Program A recent analysis of a Medicaid Managed Care plan member file produced a 35% improvement in current address information 20

21 Examples United examples Amerigroup examples

22 Population Intelligence: Analytics for Improved Program Enrollment Our data, analytics and advanced linking technologies help customers maximize participation in disease management programs by providing information that enables them to target members with a tailored approach. Customer ROI TAILORING ANALYTICS Uncover relationships among members and identify the optimal contact method for each individual to maximize likelihood of enrollment. CONTACT INFO ENHANCEMENT Improve the quality of member data with up-to-date addresses, cell phone numbers and mailing addresses. TARGETING ANALYTICS Identify which members will be most receptive to program outreach in order to focus attention and maximize resource effectiveness. Sophistication of Analytics BY INTRODUCING DATA THAT GOES BEYOND ENROLLMENT AND CLAIMS, CUSTOMERS CAN MAKE BETTER, MORE EFFICIENT DECISIONS. 22

23 What about identity management more broadly?

24 Taxpayer Dollars Are Under Attack

25 Challenges Facing Health Care Enterprises Disparate data is spread across separate physical locations Scale of data. BIG Data is getting BIGGER. Adding relationships exponentially expands the size of the BIG Data analytics challenge. Companies like LexisNexis have leveraged parallel-processing computing platforms and large scale graph analytics for more than a decade. 25

26 Graphic Analysis and Social Network Analytics Graph Analysis - Twitter uses Graph Analysis to help the site determine who s connected to whom in the Twittersphere. - Google uses Graph Analysis to power its PageRank feature. - LexisNexis uses Graph Analysis to resolve identities and establish relationships Social Network Analysis - Graph Analysis that specifically focuses on graphs built on social relationships. 26

27 Trends in Social Network Analytics Addition of External Data Mixes First Party data with Public and Third Party data sources Adds fidelity to existing entities Adds new linkages into the analysis Ads new entities into the analysis Exposes ring leaders and brokers that don t directly participate 27

28 Trends in Social Network Analytics Reliance on Created Data Transform straw into gold Process numerous discrete data points into high-value data LexisNexis LexID (example) Resolve numerous names, addresses, phones, and other info into a Person ID Better accuracy than other resolution techniques Resilient to name, address, and other info changes (i.e. stable over time) Improves detection, simplifies processing, makes results easier to understand Copyright 2012 LexisNexis. All rights reserved 28

29 LexisNexis Targets Fraud Using Large Scale Graph Analytics Powered by HPCC Systems, the LexisNexis massive parallel-processing open-source computing platform. Graph \ Network 3 Billion derived public data relationships between people merged with risk indicators. Graph Analytics examine up to 20 billion data points to create variables that allows for predictive analysis incorporating relationship context and associated risk. Targets fraud across all sectors including Health Care, Financial Services and Government. Copyright 2012 LexisNexis. All rights reserved 29

30 Case Study: Social Network Analysis for Fraud, Waste and Abuse in Medicaid High Value Assets GSA, EPLS Beneficiaries Providers 3,900, ,981 12,848

31 Case Study: Social Network Analysis for Fraud, Waste and Abuse in Medicaid High-end Vehicles GSA EPLS Beneficiaries 3,900, ,848 2 Providers 348,981 Mr. X Interesting Indicators 2009 Acura RL White (base price $50K) Medicaid Beneficiary Exclusions & Sanctions 02/20/2006 DHS: Debarred / Excluded 09/14/2006 OPM: Debarred / Suspended Registered Provider Numerous Medical Business Ownerships (discussed below)

32 Case Study: Social Network Analysis for Fraud, Waste and Abuse in Medicaid Clusters of interesting asset variables in tight social networks are often associated with coordinated activities. 3 Billion Public Data Relationships Leverage SNA Intelligence Identifying the key actors and activities Example Interesting Vehicles (2010) Red Ferrari California ($192,000), (2009) Black GMC SLT Yukon ($ 44,750), (2010) Black GMC K1500 SLT Sierra ($ 41,775), (2011) Mercedes-Benz E350 ($ 494,00), (2009) Black Mercedes-Benz AMG SL63 ($135000) (2011) White Audi 5.2 QUATTRO R8 ($161000), (2011) White BMW M3 ($ 55400) (2010) Black Mercedes-Benz S600 ($149700), (2010) Mercedes-Benz 4 MATIC GL550 ($ 82850) (2010) White Mercedes-Benz AMG CL63 ($145200) Example Interesting Residences DI IRIS D 15 [CITY] $167, F, NEYSA M 60 [CITY] $499, G YENEY 23 [CITY] $670, G, EFRAIN 76 [CITY] $550, G, LAZARO 22 [CITY] $489, G, MARLA 43 [CITY] $800, (2009) Red Audi 4.2 QUATTRO R8 ($112500) 32 32

33 Linkages and Associations: Example 3 Numerous close associates also operating medical business Provider Cluster Beneficiary Cluster Business Associate 1 Garcia, C Medicaid Provider, R Alma, R 38 Barry, L 40 Cole, D 79 Daniel, L 42 Medicaid Provider, R 78 Franco, R 56 Jones, L 38 Diaz, C 80 Wright, A 12 Wright, S 81 Wright, E 72 Bono, M 50 Rodriguez, I 33 GARCIA, C 40 Borrero, I 53 Ayala, I 60 Tyke, E 72 Jezza, A 18 Medicaid Provider, R is on an Exclusion list and a Beneficiary Business Associate 1 is related to beneficiaries in the Medicaid Provider s beneficiary network Copyright 2012 LexisNexis. All rights reserved. 33

34 Multiple Businesses Single Address Name: A Plus Medicaid Services Address: Name: A Plus Medicaid Services, Inc. Address: Name: A Plus Medical Supplies Inc. Address: Name: A Plus Pharmacy Address: Name: AAA Diagnostic Center Address: Name: A to A Mortgage Address: Name: AA Pharmacy & Discount Address: Name: A to Z Pharmacy Address: Name: Little A Pharmacy Inc Address: Name: A Plus Diagnostic Corp Address: Copyright 2012 LexisNexis. All rights reserved. 34

35 Thank You! Clint Fuhrman National Dir, Government Healthcare LexisNexis Risk, Inc Linked In Group: LexisNexis Health Care Solutions Twitter: LexisHealthCare Blog: 35

36 Bringing Big Data & Analytics Together - Providers Identity Analytics help provide insight into the risk associated with providers. Deceased Test Criteria Fraud Risk High Medicare Exclusion List (LEIE) GSA Exclusion List (EPLS) Felony conviction State of Licensure, status High High High Medium Known Associates Excluded In a recent analysis of a Medicaid provider file: Medium Over 1% were deceased 1.7% of providers were sanctioned or excluded.5% were registered sex offenders Incarcerated individuals were active providers Undisclosed associations to excluded providers were identified

37 Provider Risk Screening Make intelligent information connections beyond the obvious by drawing insights from both traditional and new sources of data. Personal/Corporate Information Other names, aliases, DBA s DOB SSN (actual and associated) Current and historical addresses Landline & wireless phone # s Death records (SSA Death Master File and other sources) National criminal background Bankruptcies, liens, judgments Family members Corporate officers & owners Known associates TIN & FEIN Licensure, Sanctions, Certifications, Etc. States of licensure; status Sanctions (with detail) HHS OIG exclusion list (LEIE) GSA exclusion list (EPLS) NPI DEA number Practice address Specialty certifications Educational background; residence Hospital affiliations Group practice associations Shared address, business association Provider Screening assists payers in verifying and monitoring health care provider licensing and credentials, and detecting and preventing fraudulent or criminal provider activity.

38 An Approach to Comprehensive Provider Management Program Integrity begins with knowing your providers Screen all current network providers Implement robust provider screening at credentialing Assign dynamic risk scores and track provider files between credentialing periods for pertinent activity; alerts generated for changes Extend screening standards to include out of network providers 38

39 Bringing Big Data & Analytics Together Beneficiaries Identity Analytics reduce beneficiary fraud and ensures accuracy of identity information for program efficiency and risk mitigation Test Criteria Fraud Risk Deceased Incarcerated Identity Fraud Risk Occupancy Outside State Real Property Value and Ownership Motor Vehicle Age and Ownership High Risk Address High High High High Medium Medium Medium 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