Fraud, Waste & Abuse: Capture low hanging fruit and more…

Using Analytics to Detect, Predict and Change Behavior

ACAP WebinarMay 19, 2016

Leon EdelsackPresidentTPG Data Services

Craig Stern, RPh, PharmD, MBASenior ConsultantProData Analytics

Marjorie Zimmerman MS, BS PharmSenior ConsultantThe Pharmacy Group

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Introduction to

TPG Data Services (TPG-DS) has the knowledge, expertise and resources to provide your organization with the tools necessary to efficiently manage your prescription drug program and potential FWA issues.

Our team helps clients:• Manage the financial performance of healthcare transactions to help

payors

• Continually monitor the marketplace, arming us with up-to-date business intelligence to deliver unbiased information tailored to individual client needs

• Mitigate F/W/A via an innovative and multidisciplinary approach necessary to effectively combat losses and change behavior

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Webinar Overview

• Defining F/W/A• F/W/A Statistics • Market Challenges • Case Study • Predictive Analytics• Solutions• Key Takeaways

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Defining F/W/A Fraud: “… an intentional deception or misrepresentation made by a person with the knowledge that the deception could result in some unauthorized benefit to himself or some other person. It includes any act that constitutes fraud under applicable Federal or State law.”

Waste: Not explicitly defined by rules but “generally understood to encompass over- utilization, underutilization or misuse of resources, and typically is not a criminal or intentional act.”

Abuse: “... provider practices that are inconsistent with sound fiscal, business, or medical practices, and result in an unnecessary cost to the Medicaid program, or in reimbursement for services that are not medically necessary or that fail to meet professionally recognized standards for health care. It also includes beneficiary practices that result in unnecessary cost to the Medicaid program.”

Definitions, 42 C.F.R. § 455.2 5

Types of Fraud, Waste and Abuse

• Overutilization• Billing for unnecessary services or items• Billing for services or items not rendered• Upcoding• Unbundling• Billing for non-covered services or items• Beneficiary fraud

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F/W/A By the Numbers

• Every hour, the United States loses $28.5 million to healthcare F/W/A.

• That is over ten times the amount an average American will earn in their lifetime.

• Totaling as much as $234 billion annually, F/W/A is becoming a growing problem which is too large to overlook.

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Market Challenges

• Growth in F/W/A driving up healthcare costs and increasing risk for plans and members

• Absence of real-time approach to identify fraud before it happens

• Fraud management processes lack sophistication and preventative measures

• Outdated technology systems • Lack of technical knowledge at Plans to know

how to assess the vast amounts of data

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F/W/A Players and Flow of Information

• By combining point of sale, patient and prescriber information, you gain a total situational view

• Resulting in efficient identification and timely resolution of problems

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Multidisciplinary Approach

• Assessment of the nexus of activity between the member/patient, the prescriber and the pharmacy

• Evaluation of transactions and activity among those three entities

• Map the relationship between these different constituents

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F/W/A Program ElementsCapture low-hanging fruit and more..

• Protect• Predict• Monitor • Change Behavior

Impacting the cycle of behavior is critical to the success of the program…

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Predictive Analytics

• Predictive analytics can identify patterns of behavior that indicate areas of potential F/W/A

• Technology by itself will not change behavior

• By proactively developing and implementing targeted communications programs to reach out and suggest corrective action we have seen results

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Preventing Payments

• Ways we work to identify a F/W/A profile as soon as the transaction happens

• Leveraging predictive tools to prevent payment

• Aligning with the current direction of CMS – to prevent wrongful payments before they happen

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Integrating Analytics & Behavior Modification

• Specific analytics • Technical & Clinical support • Results help change the behavior of the

doctor or a pharmacy, and potentially even members

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Case Study – Industry Example

• Large Medicare program• Concerns over PBM detection and internal

Strategic Investigation Unit (SIU) focus • Focus on independent pharmacies • Budget year impact net savings >$8M

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Predictive Model Considerations

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• Analytical flags cover financial, utilization, geographic, severity, day/time, risk flags

• Input based on financial threshold/provider• Analyze prescribers, pharmacies, patients – roll up

results to one or more, contact points• Output based on:• Severity, geography, provider type• Flag findings weighted by frequency and probability of risk• Contact providers selected by threshold of risk

Predictive Modeling OutputDowntown Drugs has been identified in Fraud-Waste-Abuse audits as an outlier with more than 75% above multiple FWA metrics. Downtown Drugs was compared to other Independent pharmacies with similar severity populations so that results indicate significant above average variance.

State and Federal agencies have increased their vigilance on Healthcare Fraud, Waste, and Abuse (FWA). This has prompted implementation of FWA Alarm Trigger Programs. The prescription(s) below have initiated a FWA Excess Alarm Trigger for excess quantity (Qty), an excess daily dose (OD), an excess dollar amount (Amt), excess day supply (OS), etc. This Alarm notice serves to identify patients and medications that trigger an FWA Audit.

Recommendation: In addition to high risk from multiple edits, the claims below indicate paid amounts that vary significantly over comparable claims filled by network pharmacies. These issues require reconciliation and corrective action plans.

Note to Physician Providers: Please review the patient's chart and/ or medical condition and consider the necessity for the trigger entity. In many cases, doses, quantities, and/or medication can be adjusted.

This report relies on the validity ofthe Medical and Pharmacy claims

submitted by Clients and PBMs. 17

Predictive Modeling Output

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Name: DOWNTOWN DRUGS Type: INDEPENDENT Severity: Mid Severity Pharmacy ID: 2318663

Summary Potential Financial Impact(s)

• F/W/A metrics impact 14% to 25% of total paid

• F/W/A financial impact ranges from $1.5M - $6M for pharmacy only

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Segmented Potential Financial Impact

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Lessons Learned

• Capture the low hanging fruit and more…• Validated and surpassed visibility of SIU and PBM• Fraud is legal issue and resource intensive• Indicated greater than 4X ROI• Demonstrated Waste & Abuse as significant as

Fraud• Changing behavior takes time

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Our Recommendations & Solutions

• Considerations include:• Re-examine current internal practices for F/W/A• Question whether you are sufficiently bending

the cost curve• Work proactively, not reactively to mitigate

losses...

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Key Takeaways

• Focus on prevention (CMS emphasis)• Identifying and managing Waste & Abuse

should be high priority• Bending the cost curve takes more than

technology• Achieving high rate of return will take time

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Questions?

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THANK YOU

For additional information, please contact:

Leon Edelsack President, TPG Data Services leon.edelsack@tpg-ds.com(c) 412-720-8955www.tpg-ds.com

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