1. Medical fraud and its implications Dr Vaikunthan Rajaratnam MBBS(Mal),AM(Mal),FRCS(Ed),FRCS(Glasg),FICS(USA),MBA(USA), Dip Hand Surgery(Eur), Dip MedEd(Dundee),FHEA(UK),FFSTEd,FAcadMEd(UK)Senior Consultant Hand Surgeon, KTPH Alexandra Health, Honorary Senior Lecturer, YYL School of Medicine, National University of Singapore, Core Faculty for Orthopaedic Surgery and Hand and Reconstructive Micro Surgery, NHG Residency Program , SINGAPORE

2. Healthcare expenditure lost to fraud annually Global estimate US$415 billion (~1.3 trillion MYR)Europe 56 billion euros (~240 billion MYR) Source: European Healthcare Fraud & Corruption Network 3. Annual cost of medical fraud Proportion of healthcare expenditure lost to fraud or error not knownEstimate: At least 3%, probably more than 7% and possibly as much as 10% Source: The Financial Cost of Healthcare Fraud 2011 Report, PKF (UK) LLP and University of Portsmouth 4. Medical Fraud Estimate Malaysia Health care is 4.75 % of 303.5B = 14.4B Medical fraud estimated at 3% - 10% US$ 0.4b to 1.4b or 5. Implications of medical fraudInsurance premiums Medical charges Taxes Health risks 6. Implications of medical fraud Fighting fraud in healthcare is the first and most effective step for governments and for private insurers when setting up cost cutting strategies in order to stop losses without reducing the access to and the quality of care. Paul Vincke President European Healthcare Fraud and Corruption Network 7. What is medical fraud?Fraud, waste or abuse of healthcare resources/funds, regardless of whether intent is proven (includes errors). 8. Why? 9. Types of medical fraud Opportunistic Fraud Commonplace Low $/incident Patients Healthcare professionals Healthcare managers & staffProfessional Fraud Less common High $/incident Organised criminalsFraud by contractors & suppliers High $/incident Drug & equipment companies 10. Examples of opportunistic medical fraud False claims by hospitals to get extra paymentsUsing Government grants for personal useManagers submitting false expenses claimsPatients lying about financial status to get free medical treatmentHealth professionals claiming for work that has not been donePatients pretending to be residents of countries to claim free treatment 11. Examples of professional medical fraudBillings Procedures Quality Prescriptions Devices and Implants were never provided 12. Examples of professional medical fraudBogus medical clinics set up to bill insurers for healthcare treatments that were never providedUse of stolen personal identities to claim for bogus proceduresCounterfeit drugs and devices 13. Fraud by contractors or suppliers 2009: Pfizer Inc. was ordered to pay US$2.3 billion for misbranding medicines and paying kickbacks to doctors April 2013: US Government accuses Novartis of paying multimillion-dollar kickbacks to doctors in exchange for prescribing its drugs. Drug companies in UK exploit loophole in the law to hike prices by as much as 2,000% 2012 400 fake thermometers seized in the UK 14. Attorney General Eric Holder, who announced the $2.2 billion settlement with Johnson & Johnson Monday, Nov. 4 in Washington, D.C. / CBSNEWS 15. Difficulties of detecting fraud Acceptance of fraud by health payers Health payers teams often work in silos Hotlines and rules engines Criminal dexterity Costly pay and chase model 16. Fraud Risk Management CycleCIMA UK 17. Anti Fraud Strategy 18. Solutions to detect & prevent fraud Need different approaches which combine: 1) Knowledge of existing fraud schemes 2) Powerful predictive analysis techniques 3) Comprehensive triage and case management capabilities. 19. Dynamic Rules Engines Claims are run against a predefined set of algorithms or business rules to detect known types of fraud or abuse based on specific patterns of activity, such as claims: Exceeding certain amounts Following changes to policies For services inconsistent with medical history 20. Dynamic Rules Engines ProsConsAble to filter large volumes of claims for further investigationMay uncover large numbers of suspicious claims for further investigation with many being false positives Fraudsters can easily learn the rules and work around them Rules are based on past fraud experiences so unable to spot new scamsSimple to set up and apply 21. Anomaly Detection Report events that exceed a threshold for a particular claims benchmark. ProsConsOutliers or anomalies could indicate a new or previously unknown pattern of fraud.It can be difficult to determine what to measure, what time period to use and appropriate threshold levels.Straight forward, easy to implement and intuitiveFraudsters can easily learn the rules and work around them Rules are based on past fraud experiences so unable to spot new scams 22. Predictive Modeling Uses data mining tools to build models to produce fraudpropensity scores. ProsConsTends to be more accurate than other fraud detection methodsModels degrade over timeInformation is collected and crossreferenced from a variety of sources providing a better balance of data than rules-based systems.Models need to be updated when fraudsters come out with new scams (statistical analysis can identify when updates are needed).Determines key metrics that are associated with claims that have a high fraud propensity score 23. Social Network Analysis & Multi-Entity Fraud Identifies links between entities to uncover abnormal claims patterns.ProsConsEffective in identifying organized fraud activities by modeling relationships between entities in claimsModels degrade over time and need updating when fraudsters come up with new scams.Can be fully automated, with the system continuously updating the interrelated networks with new claims and rescoring for fraud. Large volumes of seemingly unrelated claims can be checked, and then patterns and problems identified. 24. Claims development process Investigates the claims and associated documentation; Performs appropriate research regarding liability, benefit categories, statutory requirements, etc.; Determines if a payment error exists and the nature of the error; Notifies the beneficiary and provider/supplier; and Starts the payment reconciliation process. 25. selected target areas High volume of services High cost Dramatic change in frequency of use High risk problem-prone areas Recovery Auditor 26. minimize potential future losses to finaciers through targeted claims review while using resources efficiently and treating providers and beneficiaries fairly 27. Restoring integrity in the medical professionProfessionalism Accountability Legislation Probity 28. Sources & Suggested Reading The Financial Cost of Healthcare Fraud 2011 Report, PKF (UK) LLP and University of Portsmouth The Problem of Health Care Fraud, 2009, National Health Care Antifraud Association Pfizer drug breach ends in biggest US crime fine, 2 Sept 2009, Andrew Clark, The Guardian Justice Department Announces Largest Health Care Fraud Settlement in its History, 2 Sept 2009, U.S. Dept of Health & Human Services www.hhs.gov (U.S. Dept of Health & Human Services) www.ehfcn.org (European Healthcare Fraud & Corruption Network)www.nhcaa.org (National Health Care Anti-Fraud Association)