2nd Global Summit Healthcare Fraud: Prevention is better than cure October 2012 Beaumont Estate, Old Windsor, UK

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1 2nd Global Summit Healthcare Fraud: Prevention is better than cure October 2012 Beaumont Estate, Old Windsor, UK

2 Combating Fraud, Waste and Abuse With Predictive Analytics Global Summit Healthcare fraud: prevention is better than cure Old Windsor (London), UK October 25, 2012 Peter Budetti, MD, JD Deputy Administrator for Program Integrity United States Department of Health and Human Services Centers for Medicare & Medicaid Services

3 Health Insurance Coverage in the U.S., 2010 Uninsured 16% Employer- Sponsored Insurance 49% Medicaid 17% Medicare Private Non- 12% Group 5% * Medicaid also includes other public programs: CHIP, other state programs, military-related coverage. Numbers may not add to 100 due to rounding. SOURCE: KCMU/Urban Institute analysis of 2011 ASEC Supplement to the CPS.

4 U.S. Health Dollar, 2010: Where It Came From Other Third Investment Party Payers 6% and Programs 1 7% Out-ofpocket 2 12% Government Public Health Activities 3% Health Insurance 72% Medicaid (Title XIX) State and Local 5% Medicare 20% Medicaid (Title XIX) Federal 10% Private Health Insurance 33% VA, DOD, and CHIP (Titles XIX and Title XXI) 4% Health Insurance SOURCE: Centers for Medicare & Medicaid Services, Office of the Actuary.

5 The U.S. Health Dollar ($2.6 Trillion), 2010: Where It Went Dental Services and Other Professionals 7% Prescription Drugs 10% Government Administration and Net Cost of Health Insurance 7% Investment1 6% Nursing Care Facilities and Continuing Care Retirement Communities 6% Physicians and Clinics 20% Hospital Care 31% Other 14% Other Medical Products 2 3% Government Public Health Activities 3% Home Health Care 3% Other Health, Residential, and Personal Care 3 5% SOURCE: Centers for Medicare & Medicaid Services, Office of the Actuary, 5

6 CPI Strategic Direction Established Approach New Approach 1 Pay and Chase 2 One Size Fits All Legacy Processes Inward Focused Communications Government Centric Stand Alone PI Programs Prevention and Detection Risk-Based Innovation Transparent and Accountable Engaged Public & Private Partners Coordinated & Integrated 6

7 Agenda Twin Pillar Strategy Success Stories 7

8 Twin Pillars 8

9 Twin Pillars Video 9

10 National Fraud Prevention Program Application for Enrollment Claim For Payment Provider Enrollment Automated Provider Screening Integrated Data Repository Claims Processing Fraud Prevention System Rules Anomaly Detection Predictive Models Social Network Analysis IDR Zone Program CPI Integrity INFORMATION NOT RELEASABLE TO THE PUBLIC UNLESS AUTHORIZED BY LAW This information has not been publicly disclosed and may be privileged and confidential. It is for internal government Analytics Labuse only and must not be Contractors disseminated, distributed, or copied to persons not authorized to receive the information. Unauthorized disclosure may result in prosecution to the fullest extent of the law. NGD STARS One PI PECOS FID APS 10 FPS

11 Automated Provider Screening System Examples of Data Sources Leveraged for Automated Screening Identity and Address Criminal Background Demographics (e.g., name, address, phone number, languages spoken). Credentials (e.g., NPI, Licensure, Federal or State Sanctions, DEA) Social Security information (e.g., deceased/newly issued/misused SSNs) Application to Existing Medicare Providers Applied APS to all 800,000 physicians in PECOS (Provider Enrollment & Chain Ownership System) for licensure checks Completed a full screening of all 1.5 million current Medicare-enrolled providers to produce a baseline for future analysis. Monitoring certain fields for status changes (i.e., licensure, death, and criminal records) and will provide notification if changes occur. 11

12 Revalidation of Enrollment Revalidation All existing providers and suppliers must revalidate their enrollment information under new screening guidelines. Initial efforts have focused on providers and suppliers who do not have an established enrollment record in PECOS or have other indicators of potential problems. The later phases will focus on revalidating providers and suppliers already in PECOS. 12

13 Customer Service Improvements to Enrollment Our goal is simultaneously to make it easier for legitimate providers to enroll while making it more difficult for fraudsters to do so. Our Provider Enrollment Operations Group made improving customer service a primary goal, and by doing so has begun to change the way providers view and interact with CMS, and the way those within CMS view provider enrollment. 13

14 Feature Customer Driven Enrollment Changes Launch Date Revalidation Option through PECOS Web Allow Providers to submit revalidations quickly via PECOS web. E-Signature Allow Providers to submit 855 Forms without mailing in a signed signature page. October 2011 February 2012 Fast Track View - Ability to view all enrollment application data on a single screen. February 2012 Searching and Filtering of Enrollment Records Ability for users to quickly search through hundreds of enrollment records. Special Screen for State Users Creation of special screen within PECOS Administrative Interface that gives State Users the ability to quickly view enrollment information. Reassignment Reporting Ability for Groups to see the status of all the Individual providers who have reassigned benefits to them. Collection of Digital Documents Ability to upload supporting documents when submitting an application, removing the need to mail in any additional information. Streamline AO and Surrogate Process Streamline workflow for Authorized Official Registration, and allow providers to have someone work on their behalf. Self-Service Password /Username Reset Ability to reset system password or regain username without calling help desk. Bulk Upload of Enrollment Applications Ability to upload hundreds of enrollment applications via an XML form rather then one at a time via the PECOS web interface. April 2012 April 2012 July 2012 August 2012 September 2012 November 2012 April 2013

15 Fraud Prevention System Overview Monitors 4.5 million claims (all Part A, B, DME) each day Alerts generated and consolidated around providers and subsequently prioritized based on risk. Regional results are provided to our field resources, the Zone Program Integrity Contractor ( ZPIC ) analysts and investigators. Results are available to CPI and law enforcement partners in a prioritized, national view. ZPICs work the top leads in each zone 15

16 Rules Rules to filter fraudulent claims and behaviors Examples - Individuals in databases that signify significant potential problems - Geodispersion beyond acceptable bounds Analytic Model Types Anomaly Detection Detect individual and aggregated abnormal patterns vs. peer group - # procedures / provider exceeds norm - Length of stay exceeds the norm - # units per day exceeds the norm Predictive Models Assessment against known fraud cases Social Network Analysis Knowledge discovery through associative link analysis Examples Examples Examples - Beneficiary not likely to be eligible for services - Billing behavior that distinguishes fraudulent providers - Indicators of connections among multiple providers with elevated risk - Continued involvement of revoked providers Known Patterns Unknown Patterns Complex Patterns Associative Link Patterns Industry: 100% Industry: 50% Industry: 22% Industry: 13% HIGH Rate of False Positives LOW

17 Fraud Prevention System Alerts are generated and consolidated around providers and subsequently prioritized based on risk. Rules Rules to filter fraudulent claims and behaviors Anomaly Detection Detect individual and aggregated abnormal patterns vs. peer group Predictive Models Predictive assessment against known fraud cases Social Network Analysis Knowledge discovery through associative link analysis Claims

18 Tools and Data: One PI and the Integrated Data Repository One PI is the set of analytic tools used on the Integrated Data Repository The IDR: Will replace numerous standalone warehouses Allows users to perform crossprogram analyses Contains harmonized data that facilitates easy comparison of data from multiple sources 18

19 Identity Theft and Compromised Numbers Currently, CMS is aware of: 4,901 compromised Medicare provider numbers Distribution of Part B, Part C and DME Provider Addresses in the CNC Database (May 2011) 166 compromised Medicare Part D provider numbers 277, ,248 compromised beneficiary numbers 19

20 Command Center The new Command Center opened in July

21 Command Center Missions Analytics Investigative Operational Training Purpose Develop effective new models for inclusion in the FPS or APS Purpose Establish standard, innovative investigative approaches to resolving suspect providers Purpose Work specific suspect providers in real-time and take appropriate administrative action Purpose Provide training or conduct meetings that require a collaborative environment Example Model Development Workgroup Collaborate to build effective model to identify entities with characteristics correlated with fraud Example Investigative Approach Bring together multi- disciplinary team to identify new approaches for investigating a type of provider; Identify new policy and data implications Example Regional Fraud Collaborative Collaborative across CPI, ZPICs, State, OIG, DOJ, FBI to work high priority leads Example FPS Pre-Release Training Train representatives from each user group on new models and functionalities in upcoming releases 21

22 Agenda Twin Pillar Strategy Success Stories 22

23 Supplier Scheme Uncovered FPS Lead A company was flagged as a high priority because the provider and beneficiary numbers on the claims were previously compromised. Investigation FPS Data Confirmed: A company in one state was billing Medicare for providing a specific type of equipment that requires close clinical connection with beneficiaries but the beneficiaries billed for were in a distant state. Providers associated with claims had already been revoked. Beneficiary Interviews Confirmed : Beneficiaries did not receive any supplies from the company. The beneficiaries had no link to and had never seen the ordering providers. Further Analysis Confirmed: A broader scheme exists across a number of similar companies. 23

24 Outcomes Administrative Actions Supplier revoked. Paid over $700,000 last year Case referred to law enforcement. Other entities linked to the scheme are now under investigation with actions pending. New entities already identified earlier for billing in other high-risk patterns. Value New beneficiary IDs added to database of known compromised numbers Developing a new link analysis model to systematically identify providers or suppliers collaborating in scam Developing a new model that will systematically identify providers or suppliers with similar characteristics 24

25 Another Scheme Uncovered FPS Lead A company was flagged as high priority because it hit a new Predictive Model. Investigation 80% 8 FPS Data Confirmed Percent of the company s claims were for highly suspicious services Average number of services per week for each beneficiary, compared with national average of 1 Beneficiary Interviews Confirmed: Beneficiaries were not being provided the services billed. Pattern of services is not covered per Medicare policy 25

26 Outcomes Administrative Actions The company is under prepay review and payment suspension. Paid over $500,000 last year. Value Early Detection: The pattern of behavior was identified quickly for new providers one provider had only been paid $4,000 at detection Command Center: The case was discussed in the Command Center with CPI and OIG staff. Decisions were made quickly to pursue payment suspension. Model Success: The results of the predictive model confirm a high success rate with the leads. 26

27 Healthcare Fraud Prevention Partnership The Secretary of the Department of Health and Human Services and the Attorney General of the United States announced the Partnership on July 26, 2012 The new Partnership is designed to share information and best practices to improve detection and prevent payment of fraudulent health care billings across a number of public and private payers. The Healthcare Fraud Prevention Partnership is intended to enable the exchange of data and information among the partners 27

28 Healthcare Fraud Prevention Partnership: current members America s Health Insurance Plans Amerigroup Corporation Blue Cross and Blue Shield Association Blue Cross and Blue Shield of Louisiana Centers for Medicare & Medicaid Services Coalition Against Insurance Fraud Federal Bureau of Investigations Health and Human Services Office of Inspector General Humana Inc. Independence Blue Cross National Association of Insurance Commissioners National Association of Medicaid Fraud Control Units National Health Care Anti-Fraud Association National Insurance Crime Bureau New York Office of Medicaid Inspector General Travelers Tufts Health Plan UnitedHealth Group U.S. Department of Health and Human Services U.S. Department of Justice WellPoint, Inc. 28

29 The New Approach to Combating Fraud, Waste and Abuse Yesterday Providers suspected of fraudulent activity are put on prepay review, sometimes indefinitely CMS initiates overpayment recovery Law enforcement determines if an arrest is appropriate Today & Future State CMS will deny individual claims CMS and its contractors will use prepay review as an investigative technique CMS will revoke providers for improper practices CMS and Law Enforcement collaborate before, during and after case development CMS will address the root cause of identified vulnerabilities 29

30 Comprehensive Strategy Detect suspicious claims prior to payment Prevent fraudulent providers from enrolling Revoke bad actors from Medicare and Medicaid Focus on risk and reduce burden on legitimate providers Predictive Analytics (Claims) Provider Screening (Enrollment) Keep bad actors from re-enrolling Share information with States, law enforcement and private plans to target and track fraudsters 30

31 2nd Global Summit Healthcare Fraud: Prevention is better than cure October 2012 Beaumont Estate, Old Windsor, UK