1. 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
2. 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.
3. 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
4. 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.
5. 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 Summit
March 29, 2016
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6. 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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8. Regulatory Compliance: Why We Need It
We 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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9. Increased Regulatory Oversight
Expectations 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 Name
CERT* Comprehensive Error Rate Testing Program
DOJ Department of Justice
HEAT Health Care Fraud Prevention and Enforcement Action Team
MAC* Medicare Administrative Contractor
Medicaid RAC* State Medicaid Recovery Audit Contractor
MFCU Medicaid Fraud Control Unit
MIC* Medicaid Integrity Contractor
MIP* Medicaid Integrity Program
OIG* Office of Inspector General
OMIG* State Office of Medicaid Inspector General
PERM Payment Error Rate Measurement Program
RAC* Medicare Recovery Audit Contractor
ZPIC* Zone Program Integrity Contractor
* Using data mining to conduct
audits
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10. 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 Direction
The 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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17. 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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19. Pyxis® Historical Investigation Process
Internal tip
System
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
ManualManual ManualReactive
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20. 20
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:
21. 21
Red Flags for Problems
• No eMAR
• No pain scale
• No waste
• Removals for other nurses’ patients
• Patient discharged
• Nonbiometric
• Patient expired
22. 22
Beauty of Pyxis®
Pyxis® “Automated”
• Biometric
• Time
• Date
• Unit
• Drawer
• Patient
• Provider
• Easy to generate reports
• Takes time to reconcile “Withdrawn”
vs. eMAR
25. 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