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Using Advanced Analytics to Identify Drug-Seeking Behavior, Identity Fraud and Hospital-Based Drug Diversion Presenters: Tamara Neiman, MA, Director, National Special Investigations Unit, Kaiser Permanente Jay Loden, CHC, Assistant Director of Information Analytics and Compliance Technology "iACT," Kaiser Permanente Mark Horowitz, RPh, Fraud Control, National Compliance Office, Kaiser Permanente Law Enforcement Track Moderator: Michelle C. Landers, JD, Executive Vice President and General Counsel, Kentucky Employers’ Mutual Insurance, and Member, Rx and Heroin Summit National Advisory Board

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Using Advanced Analytics to IdentifyDrug-Seeking Behavior, Identity Fraud

and Hospital-Based Drug DiversionPresenters:• Tamara Neiman, MA, Director, National Special

Investigations Unit, Kaiser Permanente• Jay Loden, CHC, Assistant Director of Information Analytics

and Compliance Technology "iACT," Kaiser Permanente• Mark Horowitz, RPh, Fraud Control, National Compliance

Office, Kaiser Permanente

Law Enforcement Track

Moderator: Michelle C. Landers, JD, Executive Vice President and General Counsel, Kentucky Employers’ Mutual Insurance, and Member, Rx and Heroin Summit National Advisory Board

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Disclosures

Mark J. Horowitz, RPh; Tamara Neiman; Jay Loden, CHC; and Michelle C. Landers, JD, have disclosed no relevant, real, or apparent personal or professional financial relationships with proprietary entities that produce healthcare goods and services.

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Disclosures

• All planners/managers hereby state that they or their spouse/life partner do not have any financial relationships or relationships to products or devices with any commercial interest related to the content of this activity of any amount during the past 12 months.

• The following planners/managers have the following to disclose:– John J. Dreyzehner, MD, MPH, FACOEM – Ownership interest:

Starfish Health (spouse)– Robert DuPont – Employment: Bensinger, DuPont &

Associates-Prescription Drug Research Center

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Learning Objectives

1. Describe a large managed care organization’s advanced analytics and investigative techniques to identify drug-seeking behavior and identity fraud.

2. Analyze several cases of drug-seeking behavior and identify fraud from discovery to adjudication.

3. Explain how one managed care organization’s medical group uses analytics to improve patient care and safety.

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Using Advanced Analytics to Identify Drug Seeking Behavior, Identity Fraud, and Drug

Diversion in a Hospital Setting

Kaiser Permanente National Compliance, Ethics & Integrity Office • Tamara Neiman, Director, National Special Investigations Unit• Jay Loden, CHC, Assistant Director, Information Analytics, Compliance & Technology• Mark J. Horowitz, RPh, Information Analytics, Compliance & Technology

National RX Drug Abuse and Heroin SummitMarch 29, 2016

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Disclosures

• Tamara Neiman, Director, National Special Investigations Unit (NSIU), has disclosed no relevant, real, or apparent personal or professional financial relationships with proprietary entities that produce health care goods and services.

• Jay Loden CHC, Assistant Director, Information Analytics, Compliance & Technology (iACT), has disclosed no relevant, real, or apparent personal or professional financial relationships with proprietary entities that produce health care goods and services.

• Mark Horowitz, RPh, Compliance Consultant, Information Analytics, Compliance & Technology, has disclosed no relevant, real, or apparent personal or professional financial relationships with proprietary entities that produce health care goods and services.

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About Kaiser Permanente

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Regulatory Compliance: Why We Need ItWe need to continue to build a proactive fraud detection and prevention program to be in compliance with fraud prevention requirements such as:

• U.S. Sentencing Commission Guidelines, Chapter 8B2.1 – Effective Compliance & Ethics Program.

• Medicare 42 CFR 422.501(b)(vi) Subpart K – Contracts with Medicare Advantage Organizations.

• FEHB Program Industry Standards for Fraud and Abuse Programs (Section 1.9(a): Federal Employees Health Benefits Program.

• Medicare Modernization Act (MMA) Part D Compliance Plan Requirements, 42CFR 423.504(b)(4)(vi)/ CMS Part D Manual Chapter 9.

• Patient Protection and Affordable Care Act (aka Obamacare).

Noncompliance with federal guideline requirements for a fraud detection and prevention program can result in the loss of federal contracts and/or reimbursements, including Medicare; fines; and penalties.

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Increased Regulatory OversightExpectations are growing. Centers of Medicare & Medicaid Services (CMS) contracts with many specialty vendors to ensure sponsors compliance. The table below is indicative of the increased oversight, both federal and state:Federal Government Audit Entities

Acronym Program NameCERT* Comprehensive Error Rate Testing ProgramDOJ Department of JusticeHEAT Health Care Fraud Prevention and Enforcement Action TeamMAC* Medicare Administrative ContractorMedicaid RAC* State Medicaid Recovery Audit ContractorMFCU Medicaid Fraud Control UnitMIC* Medicaid Integrity ContractorMIP* Medicaid Integrity ProgramOIG* Office of Inspector GeneralOMIG* State Office of Medicaid Inspector GeneralPERM Payment Error Rate Measurement ProgramRAC* Medicare Recovery Audit ContractorZPIC* Zone Program Integrity Contractor

* Using data mining to conduct audits

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This technology enables us to data mine on suspected issues across all data sets (e.g., claims, payroll, payables).

Currently implemented, technology investments in progress will give us the ability to model potential threats . WE ARE HERE:

Long-term vision on Big Data analysis. Required to

enable analysis to proactively identify fraud.

Where we started in 2006. Support continues until

OneLink and Claims Connect implementations complete.

Data Mining – Technology Strategic DirectionThe technology investments underway are required to handle the expanding complexities of fraud, waste, and abuse scenarios and increasing size of data (commonly referred to as ‘Big Data’) including social networking information.

Nationalize the Analytics Program Achieve Future StateEnable Predictive Analysis

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Data Mining – Overview

LegislationEthical

Leadership & Culture

Governance

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IDENTITY FRAUDAnalytics and Case Study

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Link Analysis

Address

Street

City

DescriptionWeight

Height

Date of Birth

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DRUG SEEKING BEHAVIOR Analytics and Case Studies

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Drug Seeking Behavior Analytics Multiple Benefits From Analytics

Improve Patient Care

Fraud, Waste, and Abuse

Meet CMS Requirement

Cost Reduction

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PYXIS®

Analytics and Case Studies

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Hospital/Pyxis® Diversion

A Pyxis® is a medication dispensing machine most commonly used in hospitals.

It uses bar code scanning to help ensure accurate dispensing.

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Pyxis® Medica

tion Remov

al

Kaiser Permane

nte HealthConnect® eMAR

Pyxis® Return Medica

tion

Medication Administration Flow

Biometrics/login passwords used to access automatic dispensing cabinet for medications.

Records who, what, where, and when.

Patients permanent medication administration record. Use barcode scanning technology for electronic medical administration record (eMAR).

Common practice of disposing of excess medication not administered. Witness required.

Medication not administered or withdrawn in error and later return to Pyxis®/return bin. No witness required.

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Pyxis® Historical Investigation Process

Internal tipSystem

generated report review

Line by line comparison of

system generated

reports to Kaiser Permanente

HealthConnect eMAR

Investigator analyzes output from prior step

and incorporates

additional case information

Suspect interview:

culmination of lengthy process

Manual Manual Manual Reactive

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Proper Documentation

• Medication order• Pre and post pain scale• Medication dosage (matches medication

order for pain scale)• Proper documentation of eMAR• Waste accounted for

• Witness is responsible - DO NOT SIGN UNLESS YOU WITNESS

• Log out• Chart notes and read them• Proper access assigned to job

classification

Double Check For:

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Red Flags for Problems

No eMARNo pain scaleNo wasteRemovals for other nurses’ patientsPatient dischargedNonbiometricPatient expired

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Beauty of Pyxis®

Pyxis® “Automated”• Biometric

• Time• Date• Unit• Drawer• Patient• Provider

• Easy to generate reports• Takes time to reconcile “Withdrawn” vs.

eMAR

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PYXIS CASE STUDY

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Contacts:

Questions?

[email protected] (408) 366-4554• [email protected] (818) 592-2484• [email protected] (661) 251-1102

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Using Advanced Analytics to IdentifyDrug-Seeking Behavior, Identity Fraud

and Hospital-Based Drug DiversionPresenters:• Tamara Neiman, MA, Director, National Special

Investigations Unit, Kaiser Permanente• Jay Loden, CHC, Assistant Director of Information Analytics

and Compliance Technology "iACT," Kaiser Permanente• Mark Horowitz, RPh, Fraud Control, National Compliance

Office, Kaiser Permanente

Law Enforcement Track

Moderator: Michelle C. Landers, JD, Executive Vice President and General Counsel, Kentucky Employers’ Mutual Insurance, and Member, Rx and Heroin Summit National Advisory Board