MEDICAID

Additional Reporting 

May Help CMS 

Oversee PrescriptionDrug Fraud Controls

Report to Congressional Requesters

July 2015

GAO-15-390

United States Government Accountability Office
United States Government Accountability Office

Highlights of GAO-15-390, a report to 

congressional requesters

July 2015

MEDICAID

Additional Reporting May Help CMS Oversee 

Prescription-Drug Fraud Controls

Why GAO Did This Study

Medicaid is a significant expenditure 

for the federal government and the 

states, with total federal outlays of 

$310 billion in fiscal year 2014. CMS 

reported an estimated $17.5 billion in 

potentially improper payments for the 

Medicaid program in 2014.

GAO was asked to review pharmacyrelated program-integrity efforts at 

selected states. Among other reporting 

objectives, this report (1) identifies and 

analyzes indicators of potentially 

fraudulent or abusive prescribing 

activities in fiscal year 2011, and (2) 

examines the extent to which federal 

and state oversight policies, controls, 

and processes are in place to prevent 

and detect instances of prescriptiondrug fraud and abuse. 

GAO analyzed Medicaid claims paid in 

fiscal year 2011, the most-recent 

reliable data available, for four states: 

Arizona, Florida, Michigan, and New 

Jersey. These states were chosen, in 

part, because they were among those 

with the highest Medicaid 

expenditures; the results are not 

generalizable to all states. GAO 

performed data matching with various 

databases to identify indicators of 

potential fraud, reviewed CMS and 

state Medicaid program-integrity 

policies, and interviewed CMS and 

state officials performing oversight 

functions. 

What GAO Recommends

GAO recommends that CMS require 

states to report information about 

specific drug-utilization review controls 

to determine whether additional 

guidance is needed. The agency 

concurred with the recommendation 

and stated that it will consider requiring 

states to report on these areas. 

What GAO Found

GAO found indicators of potential prescription-medication fraud and abuse 

among thousands of Medicaid beneficiaries and hundreds of prescribers during 

fiscal year 2011—the most-recent year for which reliable data were available in 

four selected states: Arizona, Florida, Michigan, and New Jersey. These states 

accounted for about 13 percent of all fiscal year 2011 Medicaid payments. 

Specifically, in these four states, GAO found the following:

• More than 16,000 of the 5.4 million beneficiaries potentially engaged in 

“doctor shopping,” by visiting five or more doctors to receive prescriptions for 

antipsychotics or respiratory medications valued at about $33 million.

• About 700 beneficiaries received more than a 1-year supply of the same drug 

in 2011 at a cost to Medicaid of at least $1.6 million. This is an indicator of

diversion, which is the redirection of prescription drugs for illegitimate 

purposes.

As required by federal law, the Medicaid Drug Utilization Review program is a 

two-phase review process states use to promote safety while also monitoring 

prescription-drug activity for fraud. Federal law requires each state to report on 

the operation of its review program, a key monitoring tool that the Centers for 

Medicare & Medicaid Services (CMS) uses to oversee the review process in 

states, but GAO identified additional actions that could improve oversight. In the 

first phase, states use tools and eligibility screening to promote patient safety and 

avoid abuse before the drugs are dispensed. The second phase involves 

ongoing and periodic examination of claims data to identify patterns of fraud, 

abuse, gross overuse, or medically unnecessary care, and implement corrective 

action when needed. 

However, GAO identified two potential controls that are not included in CMS’s 

current reporting requirements: 

• Lock-in programs for noncontrolled substances. Lock-in programs 

address doctor shopping by restricting beneficiaries who have abused the 

Medicaid program to one health-care provider, one pharmacy, or both, for 

receiving prescriptions. Lock-in programs have typically been used on 

controlled substances. Expanding lock-in programs that currently focus on 

controlled substances to restrict abusers of noncontrolled substances, such 

as the human immunodeficiency virus medications Atripla and Truvada, to a 

single prescriber or pharmacy may help address potential fraud and abuse. 

• Prohibition of automatic refills. Pharmacies permitting automatic refills 

automatically refill prescriptions for certain medications without any customer 

action. Concerns with pharmacy automatic refill include the potential for 

stockpiling, continued fill of discontinued medications, and increased cost 

and waste of prescription medications. Two states GAO reviewed—Florida 

and Arizona—have prohibited the practice. 

CMS does not collect information about lock-in programs for noncontrolled 

substances or automatic refill prohibitions, but doing so would help the agency 

View GAO-15-390. For more information, determine whether additional guidance is needed.

contact Seto J. Bagdoyan at (202) 512-6722

or bagdoyans@gao.gov.
Page i GAO-15-390 Medicaid Pharmacy Fraud

Letter 1

Background 7

Reliability Issues Limit Usefulness of Medicaid Data for Identifying 

Indicators of Potential Fraud and Abuse 9

Medicaid Prescription-Drug Claims Data Contained Indicators of 

Potential Fraud and Improper Payments in Four Selected 

States 14

Drug Utilization Reviews Help States Detect and Prevent 

Unnecessary Prescriptions, and Additional Reporting Would 

Help CMS Determine Whether More Guidance on Controls Is 

Needed 25

Conclusions 31

Recommendation for Executive Action 31

Agency Comments and Our Evaluation 32

Appendix I Objectives, Scope, and Methodology 38

Appendix II Comments from the Department of Health and Human Services 45

Appendix III Comments from the Social Security Administration 48

Appendix IV Comments from the Arizona Health Care Cost Containment 

System 49

Appendix V Comments from the State of Florida Agency for Health Care 

Administration 53

Appendix VI Comments from the New Jersey Department of Human Services 54

Appendix VII GAO Contact and Staff Acknowledgments 58

Contents
Page ii GAO-15-390 Medicaid Pharmacy Fraud

Tables

Table 1: Estimated Number of Beneficiaries in Four Selected 

States Who Received Prescriptions for the Same Drug 

Class from Five or More Prescribers 16

Table 2: Estimated Costs Associated with Beneficiaries in Four 

Selected States in Fiscal Year 2011 Who Received 

Human Immunodeficiency Virus (HIV) Medications but Did 

Not Have Outpatient Claims in Fiscal Year 2011 Indicating 

HIV 20

Table 3: Estimated Costs Associated with Beneficiaries in Four 

Selected States in Fiscal Year 2011 Who Received 

Certain Diabetes Medications but Did Not Have 

Outpatient Claims in Fiscal Year 2011 Related to the 

Disease 21

Figure

Figure 1: Potential Improper-Payment Indicators Related to 

Medicaid Claims for Prescription Medication for Four 

Selected States during Fiscal Year 2011 22
Page iii GAO-15-390 Medicaid Pharmacy Fraud

Abbreviations

2013 CMS DUR Summary Medicaid Drug Utilization Review State 

Comparison Annual Report

AHCA Florida Agency for Health Care 

Administration

AHCCCS Arizona Health Care Cost Containment 

System

CMS Centers for Medicare & Medicaid Services

DMAHS State of New Jersey, Department of Human 

Services, Division of Medical Assistance 

and Health Services

DMF Death Master File

DUR Drug Utilization Review

FFS fee-for-service

GSA General Services Administration

HHS Department of Health and Human Services

HIV human immunodeficiency virus

MCO managed-care organization

MMIS Medicaid Management Information System

MSIS Medicaid Statistical Information System

OIG Office of Inspector General

SAM System for Award Management

SSA Social Security Administration

SSN Social Security number

T-MSIS Transformed Medicaid Statistical 

Information System

This is a work of the U.S. government and is not subject to copyright protection in the 

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Page 1 GAO-15-390 Medicaid Pharmacy Fraud

441 G St. N.W.

Washington, DC 20548

July 8, 2015

Congressional Requesters

Established in 1965 by Title XIX of the Social Security Act, Medicaid is a 

joint federal–state program that finances health care for low-income and 

medically needy individuals. The Centers for Medicare & Medicaid 

Services (CMS), within the Department of Health and Human Services 

(HHS), is responsible for overseeing the Medicaid program, including 

disbursing federal matching funds, and provides guidance, technical 

assistance, and periodic assessments of state Medicaid programs. 

Federal laws prescribe responsibility for both federal and state entities to 

protect the Medicaid program from fraud, waste, and abuse. Specifically, 

federal law requires CMS to issue regulations to improve Medicaid 

program integrity, with which state Medicaid programs must comply.

Medicaid is a significant expenditure for the federal government and the 

states, with total federal outlays of $310 billion in fiscal year 2014. In 

February 2015, we reported that Medicaid remains at high risk because of 

concerns about the adequacy of fiscal oversight of the program, including 

improper payments to Medicaid providers.1 In fiscal year 2014, CMS 

reported an estimated improper payment rate of 6.7 percent, or $17.5 

billion for the Medicaid program, which is an increase over its 2013 

estimate of 5.8 percent, or $14.4 billion.2

While most improper payments are not related to fraud, and the full extent 

to which fraud, waste, and abuse related to prescription drugs affects 

Medicaid is unknown, we have previously identified potentially fraudulent 

or abusive practices in CMS’s health-care programs.3

 1

GAO has designated Medicaid as a high-risk program since 2003.

For example, in 

2

An improper payment is defined by statute as any payment that should not have been 

made or that was made in an incorrect amount (including overpayments and 

underpayments) under statutory, contractual, administrative, or other legally applicable 

requirements.

3

Fraud involves an intentional act or representation to deceive with the knowledge that the 

action or representation could result in gain. Waste includes inaccurate payments for 

services, such as unintentional duplicate payments. Abuse represents actions inconsistent 

with acceptable business or medical practices. 

Letter
Page 2 GAO-15-390 Medicaid Pharmacy Fraud

September 2009, we found tens of thousands of potential “doctor 

shoppers” of controlled substances in Medicaid.4 Doctor shopping is a 

beneficiary fraud scheme in which patients visit several doctors and 

pharmacies, receiving more drugs than any single physician would have 

prescribed. Additionally, in September 2011, we reported on indications of 

doctor shopping in the Medicare Part D program, which provides 

voluntary, outpatient prescription-drug coverage for eligible individuals 65 

years and older and eligible individuals with disabilities.5

Because of the substantial amount of funds that are expended in the 

Medicaid program and our prior work detailing potential fraudulent or 

abusive practices, you asked us to review any pharmacy-related 

program-integrity efforts at selected states. Specifically, for this review we

As part of that 

work, we found that about 170,000 Medicare beneficiaries received 

prescriptions from five or more medical practitioners for frequently abused 

controlled substances. In both of those reports we made 

recommendations that CMS improve efforts to address doctor shopping. 

CMS agreed with our recommendations and implemented them. In May 

2015, we issued a report on our work associated with Medicaid 

beneficiary and provider fraud.

1. evaluated the reliability of Medicaid data from CMS and selected 

states for the purpose of identifying indicators of potential fraud or 

abuse;

2. identified and analyzed indicators, if any, of potentially fraudulent or 

abusive activities related to prescription drugs in Medicaid; and

3. examined the extent to which federal and selected state oversight 

policies, controls, and processes are designed to prevent and detect 

instances of prescription-drug fraud in Medicaid.

To evaluate the reliability of Medicaid data from CMS and state Medicaid 

programs for our selected states that could be used to identify indicators 

of potential fraud or abuse, we took several steps. We vetted 11 states for 

 4

GAO, Medicaid: Fraud and Abuse Related to Controlled Substances Identified in 

Selected States, GAO-09-957 (Washington, D.C.: Sept. 9, 2009).

5

GAO, Medicare Part D: Instances of Questionable Access to Prescription Drugs, 

GAO-11-699 (Washington, D.C.: Sept. 6, 2011). 
Page 3 GAO-15-390 Medicaid Pharmacy Fraud

possible inclusion in our study.6 We selected states based on high 

Medicaid beneficiary enrollment, geographic diversity, and availability of 

data. In the selection process, we also considered whether drugs were 

paid under fee-for-service (FFS) or managed care, by including states 

that included these program types in our review. We performed electronic 

testing to determine the validity of specific data elements in the federal 

and selected states’ databases that we used to perform our work. We 

also reviewed related documentation, including data layouts and agency 

reports. Specifically, we used a January 2013 Mathematica Policy Report

that details Medicaid Statistical Information System (MSIS) state data 

characteristics and anomalies to further vet states selected for our audit 

work.7 We also used published GAO and HHS Office of Inspector 

General (OIG) reports that detailed the limitations of the MSIS data we

used for our study.8 Additionally, we interviewed officials responsible for 

their respective databases to discuss data-reliability considerations, and 

reviewed prior work related to the quality of the MSIS data used for our 

study.9

 6

The states vetted were: Arizona, California, Florida, Illinois, Maryland, Michigan, New 

Jersey, New York, Ohio, Pennsylvania, and Texas.

On the basis of our discussions with agency officials and our own 

testing, we concluded that the data elements from four states—Arizona, 

Florida, Michigan, and New Jersey—used for this report were sufficiently 

reliable for the purpose of identifying indicators of potential fraud or 

abuse. However, in assessing the reliability of the data, we observed 

reportable shortcomings such as issues with timeliness, completeness, 

and accuracy in the data that may affect Medicaid administrators’ ability 

to effectively oversee their program. However, the results of the datareliability evaluation only apply to the states we selected for fiscal year 

2011 and cannot be generalized to other states or periods. We discuss 

these shortcomings in greater detail later in this report.

7

Mathematica Policy Research, Inc., MSIS State Data Characteristics/Anomalies Report 

(Jan. 7, 2013). 

8

Department of Health and Human Services, Office of Inspector General, Early 

Assessment of Review of Medicaid Integrity Contractors, OEI-05-10-00200 (Washington, 

D.C.: February 2012). GAO, National Medicaid Audit Program: CMS Should Improve 

Reporting and Focus on Audit Collaboration with States, GAO-12-627 (Washington, D.C.: 

June 14, 2012); and Medicaid: Data Sets Provide Inconsistent Picture of Expenditures, 

GAO-13-47 (Washington, D.C.: Nov. 29, 2012). 

9

Mathematica Policy Research serves as CMS’s contractor and performs reviews to 

ensure and report on the quality of MSIS data. The organization publishes information on 

unreconciled data in its anomalies report.
Page 4 GAO-15-390 Medicaid Pharmacy Fraud

To identify indicators of potentially fraudulent or abusive activities related 

to prescription drugs in Medicaid, we obtained and analyzed Medicaid 

claims paid in fiscal year 2011, the most-recent period from which we 

could draw reliable data, for four states: Arizona, Florida, Michigan, and 

New Jersey. Medicaid payments to these states constituted about 13 

percent of all Medicaid payments made during fiscal year 2011. These 

states were selected primarily because they had consistently comparable 

and reliable data and were among the states with the highest Medicaid 

expenditures. The results of our analysis of these states are not 

generalizable to other states.

We obtained MSIS beneficiary, provider, prescription-drug, and other 

services claims data, as well as state Medicaid Management Information 

Systems (MMIS) crosswalk data (with personal identifiers) to perform our 

work.10

We reviewed literature related to health-care fraud, including reports 

discussing fraud, waste, and abuse related to prescription drugs. We 

interviewed federal, state, and private-sector auditors, program 

administrators, and other relevant officials that had published work that 

investigated or researched prescription-drug fraud. On the basis of this 

research, we identified areas at greater risk of fraud and abuse such as 

drugs at high risk for diversion and types of prescribing patterns that 

warranted additional review. We used this information to develop our 

analytic approach to identify indicators of potential fraud and abuse 

related to prescription drugs in Medicaid. To identify potential overuse, we 

reviewed beneficiaries who received more than a 480-day supply of the 

same medication in a single year based on the national drug code. To 

identify potential doctor-shopping activities, we examined beneficiaries 

who received prescriptions for drugs within one of two therapeutic classes 

of drugs from five or more prescribers. We focused on beneficiaries who 

received prescriptions for antipsychotics or respiratory medications from 

five or more different prescribers over the course of 1 year. We selected 

medications in these therapeutic classes because they had a large 

number of individuals who received drugs from five or more prescribers 

The crosswalk data we used contained specific identifying 

information on prescribers, pharmacies, and beneficiaries that were not 

collected in the MSIS data, such as name and address.

 10MMIS crosswalk data contained information such as provider and beneficiary name and 

address. The quality of this information was not used to vet states for inclusion in this 

work. 
Page 5 GAO-15-390 Medicaid Pharmacy Fraud

relative to other classes of noncontrolled substances we considered, have 

a known diversion risk, and are relatively expensive.11 We selected the 

five-or-more prescribers threshold based on our review of drug diversion 

literature and prior GAO work. We also looked for prescribers and 

pharmacies with a high proportion of prescribing or dispensing activities 

for brand-name drugs (versus generics) compared to the average activity 

of other prescribers and pharmacies12 and we looked for pharmacies 

without any adjusted or voided claims.13 To identify potentially 

unnecessary prescription-drug activities, we reviewed claims paid on 

behalf of beneficiaries who received human immunodeficiency virus (HIV) 

and diabetes medications despite having no HIV or diabetes-related 

indicators related to such ailments in their fiscal year 2011 Medicaid 

outpatient claims listed in the MSIS “other services” file.14

We also matched the Medicaid data to other external sources to identify 

potential fraud and improper payments. These matches sought to identify 

individuals who may be ineligible to receive Medicaid benefits or 

providers who should not have received Medicaid payments due to 

residency, death, or other exclusionary factors. We used the beneficiary 

files to identify individuals who had payments made on their behalf 

concurrently by two or more of our selected states. We compared the 

beneficiary and prescriber identity information shown in the Medicaid 

claims data to the Social Security Administration’s (SSA) complete file of 

death information to determine whether any individuals were reportedly 

deceased when they purportedly prescribed, dispensed, or received

 11Drugs and other substances that are considered controlled substances under the 

Controlled Substances Act are divided into five schedules. An updated and complete list 

of the schedules is published annually in 21 C.F.R. §§ 1308.11 – 1308.15. Substances are 

placed in their respective schedules based on whether they have a currently accepted 

medical use in treatment in the United States, their relative abuse potential, and likelihood 

of causing dependence when abused. Drugs that are not considered controlled 

substances are known as noncontrolled substances.

12Our analysis did not control for medications where there was not a generic version 

available. 

13When a change to a prescription is made or when a beneficiary fails to pick up the 

prescribed drugs, the pharmacy must adjust the claim transaction. According to officials in 

New Jersey, instances of pharmacies with too many or too few adjustments may be red 

flags for concern.

14This analysis was based on diagnosis codes for HIV or diabetes. We did not account for 

prescribing of these medications for other ailments. 
Page 6 GAO-15-390 Medicaid Pharmacy Fraud

prescription drugs from Medicaid. To identify prescription-drug claims that 

might have been improperly processed and paid by the Medicaid program 

because either the prescribers or beneficiaries were incarcerated, we 

compared the Medicaid claims to data files listing incarcerated individuals 

from the four selected states. To identify claims that might have been 

improperly processed and paid by the Medicaid program because the 

federal government had banned the corresponding prescribers from 

providing services to Medicaid beneficiaries, we compared the Medicaid 

claims to the exclusion and debarment files from the HHS OIG and the 

General Services Administration (GSA). We compared files from the 

different states to identify beneficiaries who received concurrent benefits 

from multiple states.

To determine the extent to which federal and state oversight policies, 

controls, and processes are designed to prevent and detect indicators of 

prescription-drug fraud in Medicaid, we reviewed CMS and state Medicaid 

policies pertinent to program integrity over pharmaceuticals, met with 

CMS officials, and visited state Medicaid offices that perform oversight 

functions for the four states we selected. We used federal standards for 

internal control,15 GAO’s Fraud Prevention Framework,16

To determine the reliability of the data used in our analysis, we performed 

electronic testing to determine the validity of specific data elements in the 

federal and selected states’ databases that we used to perform our work. 

We also interviewed officials responsible for their respective databases 

and reviewed documentation related to the databases and literature 

related to the quality of the data. On the basis of our discussions with 

agency officials and our own testing, we concluded that the data elements 

used for this report were sufficiently reliable for our purposes.

and Medicaid 

statutes and regulations addressing the administration of pharmacy 

benefits to evaluate these functions.

 15GAO, Standards for Internal Control in the Federal Government, GAO/AIMD-00-21.3.1 

(Washington, D.C.: November 1999).

16GAO, Individual Disaster Assistance Programs: Framework for Fraud Prevention, 

Detection, and Prosecution, GAO-06-954T (Washington, D.C.: July 12, 2006).
Page 7 GAO-15-390 Medicaid Pharmacy Fraud

We conducted this performance audit from March 2014 to July 2015 in 

accordance with generally accepted government auditing standards. 

Those standards require that we plan and perform the audit to obtain 

sufficient, appropriate evidence to provide a reasonable basis for our 

audit findings and conclusions based on our audit objectives. We believe 

that the evidence obtained provides a reasonable basis for our findings 

and conclusions based on our audit objectives. More details on our 

objectives, scope, and methodology can be found in appendix I.

State Medicaid programs do not directly purchase prescription drugs but 

instead reimburse pharmacies for covered prescription drugs dispensed 

to Medicaid beneficiaries. States operate their Medicaid programs by 

paying qualified health-care providers (including prescribers and 

pharmacies) for a range of covered services provided to eligible 

beneficiaries and then seeking reimbursement for the federal share of 

those payments. States may directly pay health-care providers for 

services rendered using a FFS delivery system or may delegate these 

responsibilities to managed-care organizations (MCO). Under managedcare arrangements, states contract with MCOs to deliver care through 

networks. States typically pay the MCOs a fixed amount each month, 

called a capitation payment. All four of the states included in our review—

Arizona, Florida, Michigan, and New Jersey—had MCO arrangements in 

place.

Although the federal government establishes broad requirements, each 

state has flexibility in managing its Medicaid program. Guidelines 

established by federal statutes, regulations, and policies allow each state 

to (1) broaden its eligibility standards; (2) determine the type, amount, 

duration, and scope of services; (3) set the rate of payment for services; 

and (4) administer its own program, including enrollment of providers and 

beneficiaries, processing and monitoring of medical claims, payment of 

claims, and maintenance of fraud-prevention programs. CMS is 

responsible for administering legislation and regulations affecting the 

Medicaid program. CMS also provides guidelines, technical assistance, 

and periodic assessments of state Medicaid programs.

Background

Medicaid PrescriptionDrug Programs
Page 8 GAO-15-390 Medicaid Pharmacy Fraud

The federal government requires coverage for certain mandatory services 

under Medicaid, but states may decide to include other optional services 

as well. Some of the largest and most commonly included services 

include nursing facilities, home and community-based care, and hospital 

inpatient care. Although pharmacy coverage is an optional service under 

federal Medicaid law, all 50 states currently provide coverage for 

prescription drugs. States may pay for drugs dispensed through MCOs 

using either the “carve-in” or the “carve-out” approach. To use the carvein approach, states include payment for the drugs dispensed to 

beneficiaries in the MCOs’ fixed monthly payment amounts. In the carveout approach, states exclude payment for the drugs dispensed to 

beneficiaries from the MCOs’ fixed monthly payment amounts and 

instead pay for these drugs using the traditional FFS system. States may 

also use a combination of carve-out and carve-in approaches.

The Medicaid prescription-drug programs, such as the Drug Utilization 

Reviews (DUR), include the management, development, and

administration of systems and the data collection necessary to operate 

them. As part of data-collection efforts, states are mandated to report FFS 

claims and individual encounter data for managed-care enrollees to CMS. 

MSIS is the mechanism by which CMS requires states to report these 

data on a quarterly basis, although delays in reporting data occur.17 The 

database is used for analytical research, program integrity, planning, 

budgeting, and policy analyses associated with Medicaid.

Federal law prohibits Medicaid providers and beneficiaries from taking 

certain actions related to billing for or receiving Medicaid services. For 

example, the Federal False Claims Act makes it illegal to submit false 

claims to Medicare, Medicaid, and other government health-care 

programs for payment.18

 17

Violation of these or other relevant laws and 

regulations may constitute fraud. We and other federal oversight entities 

have recently issued a number of reports related to fraud and other types 

GAO-13-47. Changes to MSIS, including requirements for reporting time frames, began 

implementation in July 2014. The updated system is known as the Transformed Medicaid 

Statistical information System (T-MSIS). 

18The False Claims Act prohibits certain actions, including the knowing presentation of a 

false claim for payment by the federal government. 31 U.S.C. § 3729(a)(1)(A).

Medicaid Data Collection 

and Reporting

Medicaid Pharmacy Fraud
Page 9 GAO-15-390 Medicaid Pharmacy Fraud

of improper payments in CMS’s health-care programs, including 

Medicaid.19 For example, in May 2014 we reported that neither state nor 

federal Medicaid entities were well positioned to identify improper 

payments made to MCOs due to a gap in state and federal efforts to 

ensure Medicaid managed-care program integrity. A report released by 

the HHS OIG in August 2014 found over 1,500 Medicare beneficiaries 

who had questionable utilization patterns for HIV drugs, including 

beneficiaries who had no indication of HIV in their Medicare histories, 

received an excessive dose or supply of HIV drugs, or received HIV drugs 

from a high number of pharmacies or prescribers. In October 2014, we 

reported on 23 practices for addressing prescription-drug fraud, waste, 

and abuse in Medicare developed from a detailed literature review as well 

as interviews with relevant stakeholders.20

According to CMS guidance to state Medicaid directors, programs with 

the size and scope of Medicaid require robust, timely, and accurate data 

to identify potential fraud or waste. However, CMS’s MSIS data continue

 19See for example: GAO, Medicaid Program Integrity: Increased Oversight Needed to 

Ensure Integrity of Growing Managed Care Expenditures, GAO-14-341 (Washington, 

D.C.: May 19, 2014); Medicaid Program Integrity: CMS Pursues Many Practices to 

Address Prescription Drug Fraud, Waste, and Abuse, GAO-15-66 (Washington, D.C.: Oct. 

24, 2014); and Department of Health and Human Services, Office of Inspector General, 

Part D Beneficiaries with Questionable Utilization Patterns for HIV Drugs, OEI-02-11-

00170 (Washington, D.C.: August 2014).

20GAO-15-66.

Reliability Issues 

Limit Usefulness of 

Medicaid Data for 

Identifying Indicators 

of Potential Fraud 

and Abuse
Page 10 GAO-15-390 Medicaid Pharmacy Fraud

to have limited usefulness for identifying fraud, waste, and abuse due to 

issues with accuracy, completeness, and timeliness.21

We analyzed 11 states to possibly include in our study, but had to 

exclude data from four states—California, Maryland, Ohio, and 

Pennsylvania—due to fiscal year 2011 data-availability and quality 

issues.22

• In California, officials expressed concerns regarding the reliability of 

their data due to issues of reporting from the health plans and data 

conversions to other systems. Officials also had concerns about the 

ability to identify prescribing providers in the MCO data.

• The January 2013 Mathematica Policy Research report noted that for 

Maryland fiscal year 2011 MSIS data, National Provider Identifier (a 

unique identifier for Medicaid providers) and physician-specialty 

information were missing on managed-care prescription transactions.

• Similarly, the January 2013 Mathematica Policy Research report 

identified that Ohio MSIS data were missing provider-identifying 

information and prescription-drug and pharmacy information.

• The January 2013 Mathematica Policy Research report identified that 

Pennsylvania had not reported any data related to managed-care 

encounters through at least the fourth quarter of fiscal year 2011, 

even though the majority of the state’s Medicaid-eligible population 

was enrolled in comprehensive managed care.

Although the MSIS data from Arizona, Florida, Michigan, and New Jersey 

were sufficiently reliable for the purpose of identifying indicators of 

potential fraud or abuse, we identified issues with their timeliness and 

completeness. For example, the most-recent validated data available 

 21The results of our data-reliability work are not generalizable to other states or time 

frames other than fiscal year 2011. 

22State Medicaid officials from Illinois, New York, and Texas reported that their programs 

were shifting away from FFS to an MCO system. We excluded data from these three 

states because the most-recent data available (fiscal year 2011) would not reflect this 

transition and not because of data availability or quality concerns. We did not 

independently analyze data from California, Maryland, Ohio, or Pennsylvania to 

corroborate state officials’ statements or findings in the January 2013 Mathematica Policy 

Research report.
Page 11 GAO-15-390 Medicaid Pharmacy Fraud

from CMS for Arizona, Florida, Michigan, and New Jersey were more 

than 3 years past the date when they should have been validated.23 The 

fiscal year 2011 claim files were the most-current claim files contained in 

the MSIS system.24

In October 2012, we reported that MSIS data were not timely because of 

late state submissions and the time it takes CMS to review and validate 

data.

In addition, about 20 million (26 percent) of the 

records included filler data (e.g., 01-01-0001) in the prescribed date 

fields. While the data help identify potential vulnerabilities to Medicaid 

prescription-drug fraud, waste, and abuse, they are not sufficiently timely 

to enable investigation of specific transactions. These problems with the 

MSIS data used for this review are consistent with concerns raised in 

previous GAO and HHS OIG reports.

25

In addition, we reported in June 2012 that MSIS-based audits were 

hampered by deficiencies in the data, and noted that CMS had initiatives 

to transition into a new system called the Transformed Medicaid 

In that report we found that 37 states were late with their quarterly 

data by six quarters in July 2012. We further reported that even though 

CMS requires states to submit MSIS data within 45 days, states’ reporting 

of MSIS data and the subsequent validation process can be up to 3 years 

late. In interviews for this review, both CMS and state Medicaid officials 

agreed that this validation process can be lengthy. For example, CMS 

officials may identify a data-quality issue during the validation process in 

which they analyze the data and ensure that errors do not exceed a 

predetermined threshold. If the threshold is exceeded, CMS will then 

request the state to resubmit corrected data, which can take several 

additional months, according to both CMS and state Medicaid officials.

 23In response to a draft of this report, New Jersey Medicaid program officials stated that 

for New Jersey the concern regarding the timely submission of MSIS data is related solely 

to the time required for CMS to validate New Jersey claims file submissions. According to 

the New Jersey officials, CMS was validating the state’s quarterly claims file submissions 

for calendar years 2012 and 2013 in calendar year 2014.

24At the time of our data request, the most-recent validated CMS claims data available for 

Michigan were from the second quarter of fiscal year 2013. However, for consistency in 

our analysis, we used fiscal year 2011 data for all states. The oldest claims in our data 

were paid in October 2010, more than 3 years before we received the last file in February 

2014. 

25GAO-13-47.
Page 12 GAO-15-390 Medicaid Pharmacy Fraud

Statistical Information System (T-MSIS).26

Our review of prior HHS OIG work and our discussions with officials from 

our four selected states indicate there may be challenges related to 

implementing the T-MSIS initiative. In January 2013, the HHS OIG 

analyzed results of the early implementation of T-MSIS among 12 

volunteer states to refine and enhance the MSIS data set and modernize 

the ongoing submission and quality-review process for the data set.

According to August 2013 

CMS guidance to state Medicaid directors, T-MSIS is intended to 

modernize and enhance the way states will submit operational data about 

beneficiaries, providers, claims, and encounters and will be the 

foundation of a robust state and national analytic data infrastructure. 

Additionally, in the August 2013 CMS guidance to state Medicaid 

directors, CMS stated that this change will enhance the agency’s ability to 

observe trends or patterns indicating potential fraud, waste, and abuse in 

the state Medicaid programs to prevent or mitigate the effect of these 

activities. States may also have enhanced capabilities to counter fraud, 

waste, and abuse capabilities. The guidance also indicates CMS and the 

states will be able to analyze the data submitted by the states along with 

other information in the CMS data repositories, including Medicare data, 

enhancing abilities to better identify potential anomalies for further 

investigation. CMS officials stated that they will not begin to analyze the 

benefits derived from T-MSIS until the transition reaches the point where 

data for at least half of the Medicaid population in the United States are 

included in T-MSIS.

27

 26GAO, National Medicaid Audit Program: CMS Should Improve Reporting and Focus on 

Audit Collaboration with States, 

The 

HHS OIG found that, as of January 2013, CMS and 12 volunteer states 

had made some progress in implementing T-MSIS; however, early 

T-MSIS implementation outcomes raised questions about the 

completeness and accuracy of T-MSIS data upon national 

implementation. According to the HHS OIG report, none of the 12 

volunteer states could make all T-MSIS data elements available. Both 

CMS and the 12 states expressed concerns about the accuracy of the 

data they could provide upon implementation. The HHS OIG 

recommended that CMS ensure that states report complete, accurate, 

GAO-12-627 (Washington, D.C.: June 14, 2012). 

27Department of Health and Human Service, Office of Inspector General, Early Outcomes 

Show Limited Progress for the Transformed Medicaid Statistical Information System, OEI05-12-00610 (Washington, D.C.: September 2013).
Page 13 GAO-15-390 Medicaid Pharmacy Fraud

and timely information to T-MSIS to support effective oversight. According 

to the Fiscal Year 2016 HHS OIG Justification of Estimates for 

Appropriations Committees, this recommendation remains a priority 

unimplemented recommendation.28

CMS began implementing T-MSIS with states on a rolling basis in July 

2014 and is working towards full implementation in 2015. Specifically, 

CMS officials stated that the T-MSIS project is in the midst of 

implementation with all states. Moreover, all states are working towards 

completion of the T-MSIS implementation in 2015, according to CMS. 

CMS went live with its federal T-MSIS platform in May 2015, and

estimates that at least half the Medicaid population in the United States 

will be available through submitted T-MSIS files by the end of 2015. 

However, officials from the four states included in our review told us that 

they are experiencing challenges with implementing T-MSIS 

requirements. Specifically, officials from three of the states explained that 

CMS continues to change data-field requirements for the data 

submissions.

 28The HHS OIG 2015 Compendium of Unimplemented Recommendations did not provide 

a timeline for implementing this recommendation, but noted that CMS work in this area 

was ongoing from March 2014. 
Page 14 GAO-15-390 Medicaid Pharmacy Fraud

Our analysis of fiscal year 2011 Medicaid prescription claims data from 

four selected states identified several indicators of potential fraud.29

Specifically, we found indicators of potential fraud among beneficiaries, 

prescribers, and pharmacies (1) with questionable patterns related to 

received, prescribed, and dispensed drugs; (2) who received drugs for 

certain conditions for which the beneficiaries had no other indicators in 

their fiscal year 2011 Medicaid outpatient claims; and (3) with concerns 

identified using data matching—such as prescribers who appeared to be 

deceased by the prescribed date. Because of the age of the data, we did 

not independently investigate individual transactions to confirm whether a 

particular beneficiary, prescriber, or pharmacy actually engaged in fraud, 

waste, or abuse.30

Beneficiaries who receive large numbers of drugs, especially of the same 

drug, can indicate possible overutilization and, in more-egregious cases, 

drug diversion.31

• Beneficiaries with high quantities of the same drug. About 700 of 

the 5.4 million beneficiaries we reviewed received more than a 1-year 

supply (a 480-day supply) of the same drug in 2011 at a cost to 

Additionally, beneficiaries obtaining services from many 

different prescribers can raise questions. In our analysis of potentially 

excessive prescription claims, we found the following:

 29We reviewed prescription-drug activity for about 5.4 million beneficiaries, 251,000 

prescribers, and 26,000 pharmacies that received, prescribed, or dispensed prescriptions 

drugs paid for by Medicaid during fiscal year 2011. These counts are based solely on 

fields in the MSIS data so it is possible that a beneficiary, prescriber, or pharmacy with 

multiple records in the MSIS data may have been counted multiple times. 

30The categories for our analysis are not mutually exclusive. Individuals may be included 

in more than one analysis detailed in the report. 

31Drug diversion is the redirection of prescription drugs for illegitimate purposes. Data 

errors and legitimate need due to severe illness may also explain why certain beneficiaries 

received large quantities of drugs during our analysis. 

Medicaid 

Prescription-Drug 

Claims Data 

Contained Indicators 

of Potential Fraud 

and Improper 

Payments in Four 

Selected States

Questionable Patterns 

Related to Drugs 

Received in Four Selected 

States Indicate Potential 

Fraud

Potentially Excessive 

Prescription Claims
Page 15 GAO-15-390 Medicaid Pharmacy Fraud

Medicaid of at least $1.6 million.32

• Beneficiaries visiting five or more prescribers. Doctor shopping is 

a beneficiary fraud scheme in which Medicaid beneficiaries visit 

multiple prescribers to obtain more prescriptions for the same or 

similar drugs than a single physician would prescribe.

About 50 of these beneficiaries 

received more than 2 years’ worth (a 730-day supply) of the same 

drug. One beneficiary appeared to receive more than 3-1/2 years’

worth of the same respiratory medication at a cost to Medicaid of at 

least $10,000. Another beneficiary received more than 1 year’s worth 

of seven different drugs at a cost to Medicaid of at least $30,000.

33 Specifically, 

when a beneficiary obtains drugs from many prescribers or 

pharmacies, it could mean the beneficiary is seeking drugs to divert 

for profit or that the beneficiary’s identification number was stolen. 

Another concern is that the beneficiary is getting excessive doses or 

supplies. According to CMS data, more than 16,000 beneficiaries out 

of the 5.4 million we reviewed visited five or more prescribers to 

receive prescriptions for antipsychotics or respiratory medications 

valued at about $33 million.34

 32We calculated the days of supply using 365 days or 1 year’s worth of Medicaid data 

based on the dispense date. While it is possible that the beneficiary had a legitimate 

medical reason for obtaining a high volume of drugs, we considered it to be potentially 

fraudulent or improper if the total was more than 480 days for the same drug. We used 

480 days instead of 365 to allow for one 90 day prescription for use in the next fiscal year 

and because it was divisible by 30. This is also the threshold HHS OIG officials used in 

their work on HIV medications in Medicare Part D (see HHS OIG, OEI-02-11-00170).

For example, a single beneficiary visited 

15 prescribers and 10 pharmacies to obtain various antipsychotics at 

a cost to Medicaid of about $23,000 in 1 year. Another beneficiary 

33The excess drugs are then consumed by the beneficiary, often for recreational 

purposes, or are diverted to another party for financial gain. The Medicaid program incurs 

excessive costs for both the prescription drugs purchased during the doctor-shopping 

scheme as well as the associated office visits. Estimates suggest costs associated with 

the office and emergency room visits used to illicitly obtain drugs by means of doctor 

shopping can cost 14 times more than the drugs themselves. In this regard, our prior work 

has shown that Medicaid is vulnerable to doctor shopping for controlled substances. See

GAO-09-957.

34For this analysis, we focused on beneficiaries who received prescriptions for 

antipsychotics or respiratory medications from five or more different prescribers over the 

course of 1 year. We selected medications in these therapeutic classes because they had 

a large number of individuals who received drugs from five or more prescribers relative to 

other classes of noncontrolled substances we considered, had the strongest doctorshopping indicators (among noncontrolled substances), have a known diversion risk, and 

are relatively expensive.
Page 16 GAO-15-390 Medicaid Pharmacy Fraud

received prescriptions for respiratory medications at 11 pharmacies 

written by 21 prescribers at a cost to Medicaid of at least $4,800 in 1 

year. Table 1 shows the number of potential doctor shoppers and the 

costs associated with the purchased drugs for these therapeutic 

classes, by prescribers visited.35

Table 1: Estimated Number of Beneficiaries in Four Selected States Who Received Prescriptions for the Same Drug Class 

from Five or More Prescribers during Fiscal Year 2011

Drug class

Received 

prescriptions from 

5 to 6 providers

Received 

prescriptions from 

7 to 10 providers

Received 

prescriptions from 11 

or more providers Total

Antipsychotic Number of beneficiaries 4,800 850 30 5,720

Cost (dollars in thousands) $17,200 $3,400 $224 $20,865

Respiratory Number of beneficiaries 9,100 1,560 90 10,730

Cost (dollars in thousands) $10,100 $2,300 $163 $12,620

Total Number of beneficiaries 13,900 2,400 130 16,440

Cost (dollars in thousands) $27,400 $5,700 $387 $33,485

Source: GAO analysis of Arizona, Florida, Michigan, and New Jersey data. | GAO-15-390

Note: Totals do not add up due to rounding.

Beneficiaries may have a justifiable reason for receiving prescriptions

from multiple medical practitioners. For example, a beneficiary may 

legitimately receive prescriptions from different prescribers within the 

same practice. Also if a beneficiary moves multiple times over the course 

of the year, he or she may still require the same prescriptions, which will 

necessitate visits to additional prescribers. There may be other legitimate 

medical reasons for receiving prescriptions for the same drug from 

multiple prescribers, such as visiting multiple specialists.

Analysis of prescribing and dispensing patterns can also help identify 

indicators of potential fraud, waste, and abuse. Excessive patterns of 

prescribing or dispensing, relative to peers, can indicate potential fraud. 

For example, we examined and identified prescribers and pharmacies 

 35We cannot determine from data analysis alone which cases represent actual doctor 

shoppers and which cases represent instances in which the beneficiary had a legitimate 

reason for visiting multiple prescribing physicians. However, certain cases have stronger 

fraud indicators than others, such as those cases in which more than one pharmacy is 

involved.

Questionable Prescribing and 

Dispensing Patterns
Page 17 GAO-15-390 Medicaid Pharmacy Fraud

with an unusually high proportion of activity for brand-name drugs.36

• Prescribers and pharmacies associated with high numbers of 

brand-name drugs. In our discussions with officials that had 

investigated or researched prescription-drug fraud, we found that 

brand-name drugs can be at greater risk of diversion due to their 

relatively high expense. In more egregious examples, an unusually 

high proportion of brand-name drugs could represent a kickback 

scheme benefitting the prescriber or indicate a substitution of generic 

drugs scheme where the pharmacy dispenses generics but bills for 

more-expensive brand-name drugs.

In 

addition, analysis of pharmacy adjustments on claims can indicate 

whether pharmacies are properly billing Medicaid. In our analysis of 

prescription claims for questionable prescribing and dispensing patterns, 

we found the following:

37 Our analysis identified 119 out 

of about 28,000 prescribers associated with at least 500 claims for 

which at least 75 percent of the prescriptions were written for brandname drugs. Among the 8,800 pharmacies we reviewed with at least 

500 claims, we found about 300 pharmacies for which over half of the 

prescriptions filled were for brand-name drugs. We also found 37 

pharmacies with at least 500 claims that only dispensed brand-name 

drugs.38

 36Other possible patterns such as number of drugs prescribed per beneficiary or number 

of pharmacies filling their prescriptions can provide indications of prescribers that are 

more susceptible to fraud, waste, and abuse. In addition, pharmacies being billed 

extremely high numbers of drugs per beneficiary or per prescriber, extremely high cost per 

beneficiary or claim, or extremely high numbers of refills and adjustments relative to other 

pharmacies can also indicate potential fraud.

37Michigan Medicaid officials noted that Michigan state law prohibits Medicaid from 

requiring prescription-medication preauthorizations for brand-name medications for 

specific protected conditions, including HIV and transplant recipients. Arizona Medicaid 

officials stated that some states continue to require specific brand name medication 

coverage because it is more costly to the state to purchase the generic product.

38We identified about 27,800 prescribers and 8,800 pharmacies with at least 500 claims. 

For each prescriber with at least 500 claims, we measured the proportion of all 

prescriptions written that were brand-name drugs. The average proportion was 16.5 

percent (median = 19.9 percent). For each pharmacy with at least 500 claims, we 

measured the proportion of all prescription dispensed that were brand-name drugs. The 

average proportion was 19.3 percent (median = 21.7 percent). Our analysis did not control 

for medications where there was not a generic version available. Additionally, Arizona 

Medicaid officials stated that some specific specialty pharmacies may be expected to have 

a high percentage of branded medications.
Page 18 GAO-15-390 Medicaid Pharmacy Fraud

• Pharmacies without adjustments. When a change to a prescription 

is made or when a beneficiary fails to pick up the prescribed drugs, 

the pharmacy must adjust the claim transaction. According to officials 

in New Jersey, instances of pharmacies with too many or too few 

adjustments may be red flags for concern. We identified about 70 out 

of approximately 4,000 pharmacies that filed over 5,000 claims 

without a single adjustment. These pharmacies received at least $23 

million from Medicaid during fiscal year 2011. In contrast, among 

pharmacies that filled over 5,000 claims, the median pharmacy 

adjusted about 2 percent of its claims and the mean pharmacy 

adjusted about 5 percent of its claims. As we stated previously, 

adjustments may reflect changes to claims for medications that are 

not picked up by beneficiaries. While there may be legitimate reasons 

for a pharmacy to have low percentages of adjustments to claims, 

such pharmacies may warrant follow-up review by state oversight 

officials. For example, Michigan officials stated that there are some 

long-term nursing care facilities that only bill for the medications 

consumed by patients at the end of the month. These facilities would 

not have adjustments in their claims because the bill at the end of the 

month reflects the accurate amount of medication used by the patient.
Page 19 GAO-15-390 Medicaid Pharmacy Fraud

We identified beneficiaries in our four selected states who received 

prescription drugs only used to treat HIV and medications primarily used 

to treat diabetes but who had no additional (beyond receiving the HIV or 

diabetes medications) indicators of HIV or diabetes in their outpatient 

Medicaid activity from fiscal year 2011.39 The absence of such evidence 

does not prove that the beneficiary did not have HIV or diabetes or that 

there was inappropriate off-label use:40 the claims files we used were for 

a limited period and did not reflect the beneficiary’s entire medical history, 

and our search may not have included every possible diagnosis or 

service code related to HIV and diabetes.41

The HHS OIG reported in August 2014 that antiretroviral drugs that treat 

HIV are a target for fraud, waste, and abuse because they can be very 

expensive and can have psychoactive effects.42

Medicaid paid about $3.7 million in claims for HIV medications for 

beneficiaries with no other indications in their fiscal year 2011 outpatient 

Our analysis showed that 

the majority (94 percent) of the approximately 13,000 beneficiaries who 

received prescriptions for one of five HIV drug treatments had an HIVrelated diagnosis indicator documented in their fiscal year 2011 Medicaid 

outpatient claims. In contrast, more than 750 of the 13,000 beneficiaries 

received HIV medications despite having no apparent indicator of having 

HIV in their fiscal year 2011 Medicaid outpatient claims. These 

beneficiaries received the HIV medications Atripla, Combivir, Norvir, 

Reyataz, and Truvada, which according to Food and Drug Administration 

indications and usage labeling are used to treat HIV-positive patients.

 39We used the MSIS “other services” file to examine each beneficiary’s Medicaid activity. 

We excluded beneficiaries who did not have any activity whatsoever in the MSIS other 

services file from this analysis. The MSIS other services file covers all Medicaid or 

Children’s Health Insurance Program claims that are not included in the MSIS inpatient, 

long-term, or prescription-drug claims files. This includes payments for provider claims for 

all noninstitutional Medicaid services.

40Off-label use refers to the prescription of a medication for uses other than what the Food 

and Drug Administration has approved. Our review did not include all drugs that may be 

used to treat HIV or diabetes. See appendix I for additional details about our drug 

selection criteria.

41The results of this analysis may also be caused by off-label use, record-keeping, or 

data-coding issues. In addition, one state suggested that timing differences in its priorauthorization process could explain some of these observations.

42HHS OIG, OEI-02-11-00170.

Beneficiaries in Four 

Selected States Receiving 

Drugs for Conditions Not 

Identified in Their Fiscal 

Year 2011 Medicaid 

Outpatient Claims Indicate 

Potential Improper 

Payments

HIV Medications Prescribed to 

Beneficiaries without Indicators 

of HIV in Their Fiscal Year 

2011 Medicaid Outpatient 

Claims
Page 20 GAO-15-390 Medicaid Pharmacy Fraud

claims of having HIV. For example, 60 beneficiaries each received 

Truvada at least 12 times despite not having a HIV diagnosis code or 

other indicator for HIV, costing Medicaid at least $523,000. About 30 

beneficiaries with no HIV indicators each received the HIV medication 

Atripla at least 12 times at a cost to Medicaid of at least $418,000. One 

such beneficiary had 52 claims for multiple different HIV medications at a 

cost to Medicaid of over $50,000. Our analysis found that about 20 

pharmacies dispensed HIV medications to at least 10 different 

beneficiaries who had no HIV indicators according to their fiscal year 

2011 Medicaid claims. Table 2 summarizes the costs associated with 

each drug under review received by beneficiaries who did not have a 

Medicaid HIV indicator in the fiscal year 2011 outpatient claims file, 

broken out by beneficiaries with 1 to 11 claims and beneficiaries with 12 

or more claims.

Table 2: Estimated Costs Associated with Beneficiaries in Four Selected States in Fiscal Year 2011 Who Received Human 

Immunodeficiency Virus (HIV) Medications but Did Not Have Outpatient Claims in Fiscal Year 2011 Indicating HIV

Beneficiaries with 1 to 11 claims Beneficiaries with 12 or more claims

HIV drug

Number of 

beneficiaries

Medicaid paid amount 

(dollars in thousands) 

Number of 

beneficiaries

Medicaid paid amount 

(dollars in thousands)

Atripla 190 $728 30 $418

Combivir 80 114 20 85

Norvir 280 283 60 155

Reyataz 140 348 40 215

Truvada 310 853 60 523

Total 640 $2,326 140 $1,397

Source: GAO analysis of Arizona, Florida, Michigan, and New Jersey data. | GAO-15-390

Note: Totals do not add up because beneficiaries may receive multiple medications. The claims files 

we used were for a limited period and did not reflect the beneficiary’s entire medical history. 

Therefore, we cannot determine from data analysis alone which cases represent inappropriate 

prescriptions and which are permissible prescribing patterns.

We cannot determine from data analysis alone which cases represent 

inappropriate prescriptions and which permissible prescribing patterns 

are. Such determinations would require additional review of the facts and 

circumstances of each individual case by state oversight officials.

Our analysis showed that the majority (96 percent) of the approximately 

57,000 beneficiaries who received prescriptions for one of four diabetes 

treatments had diabetes-related indicators elsewhere in their fiscal year 

2011 Medicaid outpatient claims. However, we identified about 2,300 

beneficiaries who received diabetes medications, including Actos, 

Humalog, Lantus, and Novolog, without other indicators for the disease in 

Diabetes Medications 

Prescribed to Beneficiaries 

without Indicators of Diabetes 

in Their Fiscal Year 2011 

Medicaid Outpatient Claims
Page 21 GAO-15-390 Medicaid Pharmacy Fraud

their Medicaid outpatient claims. The costs for providing these 

medications amounted to at least $680,000. For example, about 100 

beneficiaries each received 12 or more prescriptions for Actos at a total 

cost to Medicaid of at least $96,000. Another 72 beneficiaries each 

received 12 or more prescriptions for Lantus costing Medicaid at least 

$46,000. Table 3 summarizes the costs associated with each drug under 

review received by beneficiaries who did not have a diabetes-related 

indicator in the fiscal year 2011 outpatient claims file, broken out by 

beneficiaries with 1 to 11 claims and beneficiaries with 12 or more claims.

Table 3: Estimated Costs Associated with Beneficiaries in Four Selected States in Fiscal Year 2011 Who Received Certain 

Diabetes Medications but Did Not Have Outpatient Claims in Fiscal Year 2011 Related to the Disease

Beneficiaries with 1 to 11 claims Beneficiaries with 12 or more claims

Diabetes drug

Number of 

beneficiaries

Medicaid paid amount 

(dollars in thousands) 

Number of

beneficiaries

Medicaid paid amount 

(dollars in thousands)

Actos 600 $191 100 $96

Humalog 520 149 20 32

Lantus 1,210 161 70 46

Novolog 410 13 10 0

Total 2,160 $514 190 $174

Source: GAO analysis of Arizona, Florida, Michigan, and New Jersey data. | GAO-15-390

Note: Totals do not add up because beneficiaries may receive multiple medications. The claims files 

we used were for a limited period and did not reflect the beneficiary’s entire medical history. 

Therefore, we cannot determine from data analysis alone which cases represent inappropriate 

prescriptions and which are permissible prescribing patterns.

We cannot determine from data analysis alone which cases represent 

inappropriate prescriptions and which represent permissible prescribing 

patterns or anomalies within the data. Again, such determinations would 

require additional review of the facts and circumstances of each individual 

case by oversight officials.

Of the 5.4 million beneficiaries in the four states we examined, we found 

hundreds of cases from the fiscal year 2011 data that showed potential 

indicators of improper payments, which may include fraudulent activity 

(e.g., prescriptions written by apparently deceased prescribers), due to 

concerns about the beneficiary, prescriber, or pharmacy. Figure 1 

summarizes the results of our matching data to external sources to 

identify indicators of potential improper payments or fraud. Additional 

investigation would be required to definitively determine whether improper 

payment or fraud occurred.

Indicators of Potential 

Improper Payments 

Identified Using Data 

Matching
Page 22 GAO-15-390 Medicaid Pharmacy Fraud

Figure 1: Potential Improper-Payment Indicators Related to Medicaid Claims for Prescription Medication for Four Selected 

States during Fiscal Year 2011

Note: Data are from the Medicaid Statistical Information System (MSIS), Excluded Parties List 

System, List of Excluded Individuals and Entities, Social Security Administration (SSA) death data, 

and state prison records.
Page 23 GAO-15-390 Medicaid Pharmacy Fraud

• Deceased prescribers. The identities of 290 deceased prescribers in 

the four states we examined were used to prescribe drugs to 

individuals who received Medicaid benefits. The cost of the drugs 

totaled at least $77,000 for fiscal year 2011.43

• Deceased beneficiaries. The identities of about 170 deceased 

beneficiaries in the four states we examined were used to obtain 

prescriptions that were subsequently filled and paid for by Medicaid. 

The cost of the drugs totaled at least $32,000 for fiscal year 2011.44

• Incarcerated beneficiaries and prescribers. Federal law prohibits 

states from obtaining federal Medicaid matching funds for health-care 

services provided to inmates, with the exception of inmates who are 

patients in medical institutions. The intent of the federal prohibition is 

to ensure that federal Medicaid funds are not used to finance care that 

is the responsibility of state and local authorities. For the four states 

that we examined, however, about 200 Medicaid beneficiaries 

received prescription-drug benefits while incarcerated in state prisons 

at some point in fiscal year 2011. According to the MSIS data, 

Medicaid approved at least $41,000 in benefits for these incarcerated 

individuals. This suggests possible identity theft or phantom billing 

since the beneficiary’s incarceration would have physically prevented 

him or her from receiving prescriptions.45

• Excluded prescribers. The federal government can exclude healthcare providers from participating in the Medicaid program for a variety 

of program-integrity reasons, such as criminal convictions or major 

problems related to health care (e.g., patient abuse or neglect). 

Excluded providers can be placed on one or both of the following lists, 

We also found one 

prescriber who appears to have written one prescription while 

incarcerated in a state prison.

 43Michigan Medicaid officials stated that there are instances in which a dead prescriber 

may appear to be billing after the day of death. In their program, they stated that this is 

usually because another member of the physician’s practice writes the prescription and 

the pharmacy does not update the physician information. Michigan officials have identified 

this clerical data error in their own review of deceased prescribers. 

44These results only include claims where the prescribed date occurred after death. 

45Identity theft is stealing identifying information from providers and patients and using it 

for nefarious purposes. Phantom billing is billing for prescription drugs (or other services) 

that were not provided to the beneficiary.
Page 24 GAO-15-390 Medicaid Pharmacy Fraud

which Medicaid officials must check before paying for a prescription 

claim: the List of Excluded Individuals and Entities, managed by HHS, 

and the System for Award Management, managed by GSA.46 The 

primary effect of these exclusions is that no payment will be provided 

for any items or services furnished, ordered, or prescribed by an 

excluded individual or entity. This includes Medicare, Medicaid, and 

all other federal plans and programs that provide health benefits 

funded directly or indirectly by the United States. We found about 200 

excluded prescribers who wrote prescriptions that were then used to 

obtain prescription drugs that were paid for by Medicaid. The selected 

states approved and paid the claims at a cost of over $1 million.47

• Beneficiaries concurrently receiving benefits in two or more 

states. Beneficiaries are entitled to Medicaid prescription-drug 

benefits in the states in which they currently reside but are not eligible 

to receive Medicaid benefits in more than one state concurrently.48

We identified about 618 beneficiaries that received prescription drugs 

from Medicaid in two or more of our selected states concurrently. The 

costs associated with these drugs were at least $186,000.

 4642 C.F.R. § 455.436(c)(2) requires states to check the List of Excluded Individuals and 

Entities and the Excluded Parties List System. However, GSA discontinued the Excluded 

Parties List System in 2012 and moved its content to the System for Award Management. 

In August 2012, CMS officials instructed states to use the System for Award Management 

instead of the Excluded Parties List System to fulfill their regulatory responsibilities.

47We also looked for pharmacies in the four states that had been excluded from federal 

health-care programs including Medicaid, but did not find any that billed Medicaid for 

prescription drugs dispensed during fiscal year 2011.

48Our analysis may have included Medicaid beneficiaries who moved back and forth 

between two of the selected states who appropriately terminated their Medicaid benefits 

after each move. For example, officials in Florida suggested individuals who move in and 

out of the area may have accounted for a portion of this analysis. 
Page 25 GAO-15-390 Medicaid Pharmacy Fraud

CMS monitors state Medicaid programs’ efforts to prevent and detect 

instances of prescription-drug fraud in Medicaid, but we identified areas 

that may require additional guidance for oversight. Required by federal 

law, the Medicaid Drug Utilization Review (DUR) program is one process 

states use to promote patient safety and monitor prescription-drug activity 

for fraud, waste, and abuse.49 In the first phase (prospective DUR) the 

states use tools such as point-of-sale edits, preferred-drug lists, and 

eligibility screening to promote patient safety and avoid abuse. The 

second phase (retrospective DUR) involves ongoing and periodic 

examination of claims data to identify patterns of fraud, abuse, gross 

overuse, or medically unnecessary care and implements corrective action 

when needed. For example, these measures can include postpayment 

reviews, lock-in programs, and pharmacy automatic refill restrictions.50 An 

effective DUR can reduce states’ exposure to potential fraud schemes, 

such as those described earlier in this report.51 Federal statute and 

regulation require that states report on their DUR activities as well as cost 

savings generated from their DUR programs.52

CMS also collects information from states about DUR program 

operations, cost savings from DUR programs, and innovative DUR 

practices by means of the Medicaid Drug Utilization Review Annual 

Report Survey. CMS compiles this information into an annual summary 

report that is publicly available, and may be used to highlight innovative 

practices that state Medicaid programs have implemented. According to 

the fiscal year 2013 Medicaid Drug Utilization Review State Comparison 

Annual Report (2013 CMS DUR Summary), DUR activities saved an 

average of about 18 percent on drug costs, adding up to about $3.9 billion 

in savings. CMS does not collect information about lock-in programs for 

 4942 U.S.C. § 1396r-8(g). 

50Lock-in programs are one DUR tool that can address doctor shopping by locking 

beneficiaries who have abused the Medicaid program in to one prescriber, one pharmacy, 

or both for receiving prescriptions.

51For the purposes of this section, we examined CMS’s oversight role of the entire 

Medicaid program (as opposed to just in the selected states). Observations presented in 

this section are derived from a review of key documents such as the 2013 Medicaid Drug 

Utilization Review State Comparison Annual Report, state DUR plans, and interviews with 

Medicaid officials from Arizona, Florida, Michigan, and New Jersey. Due to the scope of 

our review, we focused on DUR measures related to the prevention and detection of 

fraud, waste, and abuse. 

5242 U.S.C. § 1396r-8(g)(3)(D) and 42 C.F.R. § 456.712.

Drug Utilization 

Reviews Help States 

Detect and Prevent 

Unnecessary 

Prescriptions, and 

Additional Reporting 

Would Help CMS 

Determine Whether 

More Guidance on 

Controls Is Needed
Page 26 GAO-15-390 Medicaid Pharmacy Fraud

noncontrolled substances or automatic refill prohibitions, despite the 

concerns detailed below.

Prospective DUR screens prescription-drug claims to identify possible 

safety and overuse indicators before the drugs are dispensed. Key 

prospective DUR controls include the following:

• Point-of-sale edits. Point-of-sale edits are alerts that occur at the 

pharmacy point of sale and promote patient safety and program 

integrity by sending alerts to pharmacies during the process of filling 

the prescription to determine whether certain criteria are met. 

Effective point-of-sale edits can address issues such as the potentially 

excessive and unnecessary prescriptions described earlier in this 

report. Alerts, such as drug–drug interactions or therapeutic 

duplication, appear when there is a drug interaction risk or when a 

patient is to be dispensed a drug that is in the same therapeutic class 

as another recently dispensed drug, respectively.53

• Preferred-drug list. DUR often include a preferred-drug list, which is 

designed to help keep health-care costs down by encouraging use of 

preferred, generic and over-the-counter drugs. The preferred-drug list 

drives a market shift to generic drugs when the generic drug pricing is 

less than the brand-name drug pricing (net of CMS and supplemental 

rebates), although prescribers can override the preferred-drug list 

These alerts also 

work to promote patient safety as well as program integrity. A DUR 

can also include alerts such as a gender-specific alert that occurs 

when a drug is dispensed that is not recommended for use by the 

gender indicated on the recipient’s eligibility file. Other alerts such as 

early-refill warnings are routine edits that may signal that the patient is 

not taking the drug according to the directions or may be misusing the 

medication. Early-refill alerts also help to prevent Medicaid from 

paying for excessive amounts of medication above and beyond what 

is necessary. According to the 2013 CMS DUR Summary, all states 

set early-refill thresholds as a way of preventing prescriptions from 

being refilled too soon, which is categorized as a point-of-sale edit.

 53A therapeutic duplication DUR alert identifies instances of prescribing multiple 

medications for the same medical symptom or indication without a clear distinction of 

when one agent should be administered over another. The drug-disease contraindication 

DUR alert is activated when a drug is prescribed for an individual who has a disease for 

which the drug may be harmful. 

Prospective DUR
Page 27 GAO-15-390 Medicaid Pharmacy Fraud

using a prior-authorization request. Use of the preferred-drug list may 

limit or prevent wasteful spending.

• Eligibility screening. As described earlier in this report, states are to 

screen for the eligibility of beneficiaries, prescribers, pharmacies, and 

other entities to ensure that they have coverage under or participate in 

a health-insurance program. States are to use federal death sources 

such as SSA’s Death Master File as well as local sources such as the 

state’s vital statistics office and prisoner files to check for the death 

and incarcerations of beneficiaries. Per CMS regulations, states are 

also required to use tools such as the List of Excluded Individuals and 

Entities, managed by HHS, and the System for Award Management, 

managed by GSA, to screen prescribing providers or pharmacies for 

federal exclusions and debarments.54

Retrospective DUR involves ongoing and periodic examination of claims 

data to identify potentially problematic patterns. Key retrospective DUR 

fraud controls include postpayment reviews, lock-in programs, and 

automatic refill prohibitions.

• Postpayment reviews. Postpayment reviews involve reviewing 

claims and other documents after payment to ensure compliance with 

payment rules, and to determine whether the prescription was 

medically necessary. These reviews permit states to suspend 

payments and obtain and review medical records. Specific tactics 

states may choose to employ to find fraud in these payments include 

examining claims by amount paid, average costs, number of claims, 

adjustment rates, or percentage of claims for brand-name or Drug 

Enforcement Administration Schedule II drugs.55

 5442 C.F.R. § 455.436(c)(2). 

States can vary the 

55States have other requirements they must meet, such as timely payment that would be 

examined in a postpayment review. Drugs, substances, and certain chemicals used to 

make drugs are classified into five distinct categories or schedules depending upon the 

drug’s acceptable medical use and the drug’s abuse or dependency potential. The abuse 

rate is a determinate factor in the scheduling of the drug. Schedule II drugs, substances, 

or chemicals are defined as drugs that have a high potential for abuse, a currently 

accepted medical use in treatment in the United States or a currently accepted medical 

use with severe restrictions, and abuse may lead to severe psychological or physical 

dependence. These drugs are also considered dangerous. Some examples of Schedule II 

drugs are: combination products with less than 15 milligrams of hydrocodone per dosage 

unit (Vicodin), cocaine, methamphetamine, methadone, hydromorphone (Dilaudid), 

meperidine (Demerol), oxycodone (OxyContin), fentanyl, Dexedrine, Adderall, and Ritalin.

Retrospective DUR
Page 28 GAO-15-390 Medicaid Pharmacy Fraud

period of review depending on available data and may monitor overall 

activity as well as activity within subsections of the population. For 

example, states can look for top beneficiary recipients of a certain 

drug or therapeutic class, prescribers who most frequently prescribe 

controlled substances, or pharmacies that dispense certain drugs at 

an average cost that is significantly higher than that of their peers. 

There are numerous ways the data can be analyzed and checks can 

be combined to strengthen detection of indicators of potential fraud. 

Effective strategies can then be repeated. While it is likely not 

possible to determine from data analysis alone whether any given 

prescription was appropriate, such analysis can detect anomalies that 

might warrant additional audit and investigation outside the DUR 

process. For example, as we discussed previously in this report, a 

pharmacy may dispense an unusually high proportion of brand-name 

medications. States can use pharmacy audits to ensure dispensary 

compliance with program rules and regulations while looking for fraud 

and abuse.

• Lock-In Programs (also known as Restricted Recipient 

Programs). As noted earlier in this report, we identified about 16,000 

individuals whose visits to multiple prescribers for antipsychotics and 

respiratory medications raise questions.56

Lock-ins are typically triggered by abuse of controlled substances. 

Officials in Arizona and New Jersey stated that their lock-in program 

has historically focused on lock-in for controlled substances, although 

lock-ins for other drugs were permitted. Officials in Florida stated that 

their program does not use lock-in for noncontrolled substances and 

has trended towards using point-of-sale edits to restrict doctorshopping activities related to controlled substances. Michigan officials 

stated that the state Medicaid program has two categories of lock-ins: 

Lock-in programs are one 

DUR tool that can address doctor shopping by locking beneficiaries 

who have abused the Medicaid program in to one prescriber, one 

pharmacy, or both for receiving prescriptions. Lock-in allows both 

prescribers and pharmacies to develop a more-complete picture of the 

beneficiary’s drug-utilization history. Lock-in programs historically 

have applied to those beneficiaries in an FFS arrangement, although 

MCOs may employ similar measures to “lock-in” enrollees when such 

actions are warranted.

 56As noted earlier, we recognize that in some cases legitimate reasons exist to visit 

multiple prescribers.
Page 29 GAO-15-390 Medicaid Pharmacy Fraud

beneficiaries may be locked in to a specific prescriber for controlled 

substances, or beneficiaries may be locked in to specific prescribers 

and pharmacies for all medications. Michigan officials indicated that 

they apply specific criteria to determine the lock-in category a 

beneficiary is assigned.

According to CMS officials, CMS does not have specific guidance for 

the state Medicaid programs on lock-ins. They said that states decide 

the requirement for placing a beneficiary in a lock-in program. Given 

that we found more than 16,000 beneficiaries who received 

prescriptions for relatively high-value medications from at least five 

prescribers in 1 fiscal year, there is a risk that Medicaid is wasting 

funds on prescriptions that are medically not necessary, and 

potentially fraudulently diverted. Although there is no federal 

requirement for states to implement a lock-in program, according to 

the 2013 CMS DUR Summary all but one of the states has a lock-in 

program for controlled substances. However, the report does not 

contain information on lock-in programs for noncontrolled substances.

• Pharmacy Automatic Refill. Pharmacies may automatically refill 

prescriptions for certain medications without any customer action. 

Automatic refill services can be employed at both retail and mailservice pharmacies. In retail settings, medications that are not picked 

up by the patient within a finite period must be returned to stock. 

However, mail-service pharmacies are unable to return the medication 

to stock once the prescription is delivered. Concerns with pharmacy 

automatic refill include the potential for stockpiling, continued fill of 

discontinued medications, and an increase in the cost and waste of 

prescription medications. In 2013, CMS banned pharmacy automatic 

refills in the Medicare Part D program because these practices were 

potentially generating significant waste and unnecessary additional 

costs for the Medicare Part D program overall.

Unlike Medicare Part D, CMS currently does not have specific 

guidance on pharmacy automatic refills for the Medicaid program.57

 57CMS administers the Medicare program as well as oversees the design and operation of 

state Medicaid programs. To receive federal matching funds for services provided to 

Medicaid beneficiaries, each state must submit a state Medicaid plan for approval by 

CMS. The state Medicaid plan defines how the state will operate its Medicaid program, 

including which populations and services are covered. States must operate their Medicaid 

programs within broad federal parameters. While complying with these federal 

requirements, however, states have the flexibility to tailor their Medicaid programs. 
Page 30 GAO-15-390 Medicaid Pharmacy Fraud

CMS officials stated that policy on pharmacy automatic refills is a 

state-specific decision and states may have information in their billing 

instructions to pharmacies on their policy regarding automatic refills. 

In addition, CMS officials said that each state’s Board of Pharmacy 

may have a policy on this subject and that these boards may audit 

pharmacies regarding their compliance with state regulations. 

Currently, Florida and Arizona are the states in our review that do not 

allow automatic refills. When asked why such prohibitions were in 

place, officials in Arizona noted that its Medicaid population was 

transient, and automatic refills could lead to prescriptions mailed to 

old addresses where the beneficiary no longer lived, at the state’s 

expense. Officials in Florida cited concerns about beneficiaries 

stockpiling medications and not wanting to pay for prescriptions that 

were no longer needed.

Federal regulations define abuse as 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.

Automatic refill programs may result in Medicaid beneficiaries 

obtaining medications far in excess of what was utilized or needed, 

resulting in wasted Medicaid resources. In fact, officials in New Jersey 

stated that automatic refills pose a problem for both fraud and waste 

of government funds, but at the time of our review did not have a 

policy preventing this practice.

According to the Standards for Internal Control in the Federal 

Government, internal controls should generally be designed to ensure 

that ongoing monitoring occurs in the course of normal operations, and 

that it is performed continually and ingrained in the agency’s operations.58

 58

Our review of CMS monitoring activities found that CMS surveys states 

on a variety of different measures for fraud and waste prevention as well 

as cost-savings measures. Our discussions with officials in the selected 

states and CMS indicated that lock-in programs for noncontrolled 

substances and automatic refill prohibitions may warrant additional 

review. As discussed previously, state Medicaid programs varied in the 

type of medications that are included in lock-in programs. Additionally, we 

found more than 16,000 beneficiaries who received prescriptions for 

GAO/AIMD-00-21.3.1.
Page 31 GAO-15-390 Medicaid Pharmacy Fraud

relatively high-value medications from at least five prescribers in 1 fiscal 

year, indicating that there is a risk that Medicaid is wasting funds on 

prescriptions that are medically not necessary, and potentially 

fraudulently diverted. The Medicare Part D program, as well as Florida 

and Arizona Medicaid programs, prohibit automatic refills, citing both 

patient safety and unnecessary costs as concerns for implementing these 

practices. However, CMS does not collect this information in the DUR 

survey or other collection methods. As a result, CMS does not know the 

number of state Medicaid programs that prohibit automatic refills or have 

lock-in programs for noncontrolled substances. Additional information 

would allow CMS to determine whether additional guidance for locking in 

recipients of noncontrolled substances and prohibiting automatic refills in 

Medicaid could prevent some of the problems we identified in our analysis 

and lead to cost savings.

Our review of fiscal year 2011 prescription-drug claims data from four 

states uncovered indicators of potential fraud, waste, and abuse 

throughout the Medicaid prescription-drug program in those states, 

including potential doctor shopping of noncontrolled substances. In 

addition, interviews with officials from these four states highlighted 

Medicaid practices that were prone to waste and abuse, such as 

pharmacy automatic refills. Ensuring that cost-effective controls are in 

place and working properly requires additional improvements from the 

MCOs, states, and CMS responsible for administering Medicaid. While 

CMS oversees the administration of state Medicaid programs, CMS does 

not currently identify whether states have implemented lock-in programs 

for noncontrolled substances or automatic refill prohibitions. Lock-in 

programs are an important tool that can be used to address doctor 

shopping by locking beneficiaries who have abused the Medicaid 

program in to one prescriber, one pharmacy, or both for receiving 

prescriptions. Automatic refill prohibitions may help limit waste and 

unnecessary program expenditures. Expanding monitoring efforts to 

examine these matters in greater depth would provide CMS with morecomplete information to help determine whether there is a need to issue 

guidance to address these potential problems more consistently to help 

ensure greater program integrity and additional cost savings.

To enhance monitoring of potentially wasteful or abusive practices in the 

Medicaid program, we recommend that the Acting Administrator of CMS 

require states to report to CMS whether their state has lock-in programs 

for abusers of noncontrolled substances and prohibitions on pharmacy 

Conclusions

Recommendation for 

Executive Action
Page 32 GAO-15-390 Medicaid Pharmacy Fraud

automatic refills, and examine the results to determine whether additional 

guidance is appropriate.

We provided a draft copy of this report to HHS, SSA, and state Medicaid 

program offices for Arizona, Florida, Michigan, and New Jersey. Written 

comments from HHS; SSA; the Arizona Health Care Cost Containment 

System (AHCCCS); the Florida Agency for Health Care Administration 

(AHCA); and the State of New Jersey, Department of Human Services, 

Division of Medical Assistance and Health Services (DMAHS) are 

summarized below and reprinted in appendixes II–VI. HHS concurred 

with our recommendation. The letter from SSA stated the agency had no 

comments on our report. AHCCCS disagreed with our methodology and 

provided detailed comments on our findings, as described below. AHCA 

did not comment on the report’s findings but stated that the state 

Medicaid program already prohibits pharmacy automatic refills and will 

work with CMS to implement a lock-in program for noncontrolled 

substance abusers. DMAHS did not comment on the report’s findings but 

outlined several steps the state has taken that could address the types of 

issues raised in our report, which are summarized below. In an e-mail 

received on May 28, 2015, officials from the Michigan Department of 

Community Health did not comment on the report’s findings but provided 

technical comments, which we incorporated as appropriate. In addition, 

we provided excerpts of this draft report related to the reliability issues of 

Medicaid data to state Medicaid program offices for California, Illinois, 

Maryland, New York, Ohio, Pennsylvania, and Texas for technical 

comment. In an e-mail received on May 19, 2015, the Deputy Director, 

Division of Program Development and Management of the New York 

Department of Health, provided suggestions regarding CMS’s 

implementation of T-MSIS, which was outside the scope of our review, so 

we did not incorporate these comments in our draft report. Officials from 

California, Illinois, Maryland, New York, Ohio, Pennsylvania, and Texas 

did not provide technical comments.

In its written comments, HHS concurred with our recommendation and 

stated that it will consider requiring states to report on lock-in programs 

for abusers of noncontrolled substances and pharmacy automatic refill 

policies. HHS also outlined the steps the agency has taken to improve 

data collection in Medicaid and address prescription-medication fraud 

since the fiscal year 2011 data used in our study. We incorporated these 

comments in our report as appropriate. 

Agency Comments 

and Our Evaluation
Page 33 GAO-15-390 Medicaid Pharmacy Fraud

In its written comments, AHCCCS said that it takes exception to being 

included in a series of findings that offer no state-specific detail. As we 

noted in our meetings with all state agencies included in our study, we did 

not provide state-level detail for two primary reasons. First, because CMS 

was the audited agency for our work, conducting analysis at the statelevel would be outside the scope of our work and would put the focus on 

a comparison between the states, rather than on CMS oversight. In 

addition, due to the age and limitations of the data, as noted in the report, 

we would not be referring specific cases for follow-up. Moreover, 

AHCCCS noted that the findings of our study represent less than onetenth of Medicaid spending for the four states used in our study. As we 

stated previously in this report, all of the states in our study had MCO 

arrangements in place during our study period. As a result, the Medicaid 

paid amounts associated with managed care may not be reflected in the 

state claims that were submitted to CMS for medical services, and hence 

our estimate is likely understated.

AHCCCS also commented on specific sections of our analysis. First, 

AHCCCS stated that our report did not identify state practices that are 

able to leverage more-accurate data sources on a real-time basis. As 

mentioned above, the focus of our work was CMS oversight of the 

Medicaid program rather than an in-depth discussion of current, specific 

practices employed by the states. Second, AHCCCS incorrectly stated 

that we used the federal incarceration file in our analysis. As we note in 

appendix I, we used each state’s department of corrections prisoner 

databases for individuals incarcerated for any period during fiscal year 

2011. Specifically, for our work, we used the same Arizona Department of 

Corrections file to perform matches that AHCCCS outlined in its response 

letter. Third, AHCCCS provided an overview of the additional checks the 

state performs to identify incarcerated beneficiaries, as well as deceased 

providers and beneficiaries. This overview does not refute the findings in 

our report, and we did not incorporate these details in the report. 

Regarding our analysis of prescription-drug medication claims data, 

AHCCCS stated that our report should have used more than a single year 

of claims data to identify diagnosis information. We acknowledge this 

limitation, and updated our report with the appropriate caveats. 

Specifically, we state that we identified beneficiaries who did not have 

indicators of HIV or diabetes in their outpatient Medicaid activity from 

fiscal 2011, and that the absence of such evidence does not prove that 

the beneficiary does not have HIV or diabetes or that there was 

inappropriate off-label use. Further we stated that the results of this 

analysis may also be caused by off-label use, record-keeping, or data-
Page 34 GAO-15-390 Medicaid Pharmacy Fraud

coding issues. In addition, we noted that timing differences in the priorauthorization process could explain some of these observations. We also 

note that we cannot determine from data analysis alone which cases 

represent inappropriate prescriptions and which are permissible 

prescribing patterns.

Regarding our analysis of brand-name medications, AHCCCS stated that 

our findings represent 0.425 percent of prescribing clinicians. In the draft 

report provided to AHCCCS, we provided the number of individuals we 

found and the total study population to provide the appropriate context. 

AHCCCS also noted that our report did not take into consideration that 

states may continue to require brand-name coverage because it may be 

more costly to the state to purchase the generic product. As a result, we 

incorporated discussion of this limitation in our report. Similarly, AHCCCS 

stated that our report does not differentiate between retail pharmacies 

and specialty pharmacies, and that some specific specialty pharmacies 

are expected to have a high percentage of branded medications. We 

noted that we did not control for medications where there was not a 

generic version available. However, to address the specific concern of 

AHCCCS, we incorporated this caveat into our report. Again, as noted 

several times in our report, the results of our analysis are indicators of 

potential fraudulent or improper payments. 

AHCCCS further stated that Arizona protocols already apply the 

recommendations in our report. In our report, we note that Arizona has a 

lock-in program that can incorporate noncontrolled medications and 

prohibits automatic refills in the Medicaid program. As noted in our report, 

the recommendation is addressed to CMS, and not the states used in our 

study. Specifically, we recommended that CMS collect information on 

what other states’ practices are related to lock-ins of noncontrolled 

medications and prohibitions of automatic refills, and examine the results 

to determine whether additional guidance is appropriate.

Finally, AHCCCS stated that our report reaches sweeping conclusions 

without validating findings based on state-specific data. Again, as 

mentioned earlier, the focus of our report is CMS oversight of the 

Medicaid program. Our report provides the appropriate context for our 

findings, including limitations of our analysis to ensure that the results of 

our analysis were not taken in an inappropriate context. 

In response to our draft report, the Florida Agency for Health Care 

Administration (AHCA) stated that the Florida Medicaid program currently 

does not allow pharmacy automatic refills. Further AHCA stated that it will 
Page 35 GAO-15-390 Medicaid Pharmacy Fraud

work with CMS’s guidance and recommendations for the implementation 

of a lock-in program for abusers of noncontrolled substances

In its response to our draft report, the New Jersey Department of Human 

Services, Division of Medical Assistance and Health Services (DMAHS),

stated that automatic prescription refills are a major concern for the State 

of New Jersey. According to DMAHS, although characterized by retail 

pharmacies as a “patient-friendly” service designed to improve the quality 

of prescription services, automatic prescription refills pose several 

concerns, such as the potential for stockpiling medications; continued 

filling of discontinued medications; unrecognized changes in drug 

therapies; and increases in fraud, waste, and abuse of prescription drugs. 

DMAHS stated that it looked forward to better understanding the audit 

practices used by CMS and certain states to audit this practice.

In addition, DMAHS outlined steps the New Jersey Medicaid program has 

taken to strengthen prescription-drug internal controls, including requiring 

MCO programs to implement a pharmacy lock-in program. DMAHS also 

provided comments to address additional actions the state has taken that 

would address the findings we outlined in our report, including a qualitymanagement and utilization-review program that focuses on medical 

encounters and a quarterly doctor-shopper report that identifies recipients 

who may be engaged in fraudulent activities. While we did not make any 

specific recommendations to the states, we believe that such actions 

should enhance their oversight of prescription-drug controls. 

Additionally, DMAHS provided comments on timely submission of MSIS 

data and stated that timely submission of MSIS data is related to the time 

required for CMS to validate New Jersey claims file submissions. We 

incorporated its comments in our report, as appropriate.

As agreed with your offices, unless you publicly announce the contents of 

this report earlier, we plan no further distribution until 30 days from the 

report date. At that time, we will send copies of this report to the

Secretary of Health and Human Services, the Commissioner of Social 

Security, relevant state agencies, and interested congressional 

committees. In addition, the report is available at no charge on the GAO 

website at http://www.gao.gov.
Page 36 GAO-15-390 Medicaid Pharmacy Fraud

If you or your staff have any questions about this report, please contact 

me at (202) 512-6722 or bagdoyans@gao.gov. Contact points for our 

Offices of Congressional Relations and Public Affairs may be found on 

the last page of this report. GAO staff that made key contributions to this 

report are listed in appendix VII.

Seto J. Bagdoyan

Director, Audit Services

Forensic Audits and Investigative Service
Page 37 GAO-15-390 Medicaid Pharmacy Fraud

List of Requesters

The Honorable Ron Johnson

Chairman

The Honorable Thomas R. Carper

Ranking Member

Committee on Homeland Security and Governmental Affairs

United States Senate

The Honorable Claire McCaskill

Ranking Member

Permanent Subcommittee on Investigations

Committee on Homeland Security and Governmental Affairs

United States Senate

The Honorable Sheldon Whitehouse

Ranking Member

Subcommittee on Crime and Terrorism

Committee on the Judiciary

United States Senate
Appendix I: Objectives, Scope, and 

Methodology

Page 38 GAO-15-390 Medicaid Pharmacy Fraud

In this report, we (1) evaluated the reliability of Medicaid data from the 

Centers for Medicare & Medicaid (CMS) and selected states for the 

purpose of identifying indicators of potential fraud or abuse; (2) identified 

and analyzed indicators, if any, of potentially fraudulent or abusive 

activities related to prescription drugs in Medicaid; and (3) examined the 

extent to which federal and selected state oversight policies, controls, and 

processes are designed to prevent and detect indicators of prescriptiondrug fraud in Medicaid.

To evaluate the reliability of Medicaid data from CMS for our selected 

states that could be used to identify indicators of potential fraud or abuse, 

we took several steps. We vetted 11 states for possible inclusion in our 

study.1 We selected states based on high Medicaid beneficiary 

enrollment, geographic diversity, and availability of data. In the selection 

process, we also considered whether drugs were paid under fee-forservice (FFS) or managed care, by including states that included these 

program types in our review. We performed electronic testing to 

determine the validity of specific data elements in the federal and 

selected state databases that we used to perform our work. We also 

reviewed related documentation, including data layouts and agency 

reports. Specifically, we used a January 2013 Mathematica Policy 

Research report that details Medicaid Statistical Information System 

(MSIS) state data characteristics and anomalies to further vet states 

selected for our audit work.2 We also used published GAO and 

Department of Health and Human Services (HHS) Office of the Inspector 

General (OIG) reports that detailed the limitations of the MSIS data we 

used for our study.3

 1

The states vetted were: Arizona, California, Florida, Illinois, Maryland, Michigan, New 

Jersey, New York, Ohio, Pennsylvania, and Texas.

Additionally, we interviewed officials responsible for 

their respective databases to discuss data-reliability considerations, and 

reviewed prior work related to the quality of the MSIS data used for our 

2

Mathematica Policy Research, Inc., MSIS State Data Characteristics/Anomalies Report

(Jan. 7, 2013).

3

Department of Health and Human Services, Office of Inspector General, Early 

Assessment of Review of Medicaid Integrity Contractors, OEI-05-10-00200 (Washington, 

D.C.: February 2012); GAO, National Medicaid Audit Program: CMS Should Improve 

Reporting and Focus on Audit Collaboration with States, GAO-12-627 (Washington, D.C.: 

June 14, 2012); and Medicaid: Data Sets Provide Inconsistent Picture of Expenditures, 

GAO-13-47 (Washington, D.C.: Nov. 29, 2012).

Appendix I: Objectives, Scope, and 

Methodology
Appendix I: Objectives, Scope, and 

Methodology

Page 39 GAO-15-390 Medicaid Pharmacy Fraud

study.4

To identify indicators of potentially fraudulent or abusive activities related 

to prescription drugs in Medicaid, we obtained and analyzed Medicaid 

claims paid in fiscal year 2011, the most-recent period from which we 

could draw reliable data, for four states: Arizona, Florida, Michigan and 

New Jersey. These states accounted for about 13 percent of the federal 

share of fiscal year 2011 Medicaid expenditures. These states were 

selected primarily because they had consistently comparable and reliable 

data and were among the states with the highest Medicaid expenditures. 

The results of our analysis of these states are not generalizable to other 

states.

On the basis of our discussions with agency officials and our own 

testing, we concluded that the data elements from the four states—

Arizona, Florida, Michigan and New Jersey—used for this report were 

sufficiently reliable for the purpose of identifying indicators of potential 

fraud or abuse. However, in assessing the reliability of the data, we 

observed reportable shortcomings such as issues with timeliness, 

completeness, and accuracy in the data that may affect Medicaid 

administrators’ ability to effectively oversee their program. We discuss 

these shortcomings in greater detail earlier in this report.

We obtained CMS MSIS beneficiary, provider, prescription-drug, and 

other services claims data, as well as state Medicaid Management 

Information Systems (MMIS) crosswalk data (with personal identifiers) to 

perform our work. The crosswalk data we used contained specific 

identifying information on prescribers, pharmacies, and beneficiaries that 

were not collected in the MSIS data, such as name and address. 

Additionally, managed-care organizations (MCO) receive a monthly 

capitated payment.5

 4

Mathematica Policy Research serves as CMS’s contractor and performs reviews to 

ensure and report on the quality of MSIS data. The organization publishes information on 

unreconciled data in its anomalies report.

As a result, the Medicaid paid amounts associated 

with managed care may not be reflected in the state claims that were 

submitted to CMS for medical services, and hence our estimate is likely 

understated. All of the states included in our review—Arizona, Florida, 

Michigan, and New Jersey—had MCO arrangements in place.

5

Under managed-care arrangements, states contract with MCOs to deliver care through 

networks. States typically pay the MCOs a fixed amount each month, called a capitation 

payment. Approximately 70 percent of Medicaid enrollees are served through managedcare delivery systems, where providers are paid at a monthly capitation payment rate.
Appendix I: Objectives, Scope, and 

Methodology

Page 40 GAO-15-390 Medicaid Pharmacy Fraud

We reviewed literature related to health-care fraud, including reports 

discussing fraud, waste, and abuse related to prescription drugs. We 

interviewed federal, state, and private-sector auditors, program 

administrators, and other relevant officials who had published work that 

investigated or researched prescription-drug fraud. On the basis of this 

research, we identified areas at greater risk of fraud and abuse such as 

drugs at high risk for diversion and types of prescribing patterns that 

warranted additional review. We used this information to develop our 

analytic approach to identify indicators of potential fraud and abuse 

related to prescription drugs in Medicaid. To identify potential overuse, we 

reviewed beneficiaries who received more than a 480-day supply of the 

same medication in a single year based on the national drug code. To 

identify potential doctor-shopping activities, we examined beneficiaries 

who received prescriptions for drugs within one of two therapeutic classes 

of drugs from five or more prescribers. We focused on beneficiaries who 

received prescriptions for antipsychotics or respiratory medications from 

five or more different prescribers over the course of 1 year. We selected 

medications in these therapeutic classes because they had a large 

number of individuals who received drugs from five or more prescribers 

relative to other classes of noncontrolled substances we considered, have 

a known diversion risk, and are relatively expensive.6

 6

Drugs and other substances that are considered controlled substances under the

Controlled Substances Act are divided into five schedules. An updated and complete list 

of the schedules is published annually in 21 C.F.R. §§ 1308.11 – 1308.15. Substances 

are placed in their respective schedules based on whether they have a currently accepted 

medical use in treatment in the United States, their relative abuse potential, and likelihood 

of causing dependence when abused. Drugs that are not considered controlled 

substances are known as noncontrolled substances.

We selected the 

five-or-more prescribers threshold based on our review of drug-diversion 

literature and prior GAO work. Since we did not focus on all noncontrolled 

substances, our analysis understates the number of instances and dollar 

amounts related to potential doctor-shopping activities. We also looked 

for prescribers and pharmacies with a high proportion of prescribing or 

dispensing activities for brand-name drugs (versus generics) compared to 
Appendix I: Objectives, Scope, and 

Methodology

Page 41 GAO-15-390 Medicaid Pharmacy Fraud

the average activity of other prescribers and pharmacies7 and pharmacies 

without any adjusted or voided claims.8

To identify potentially unnecessary prescription-drug activities, we 

reviewed claims paid on behalf of beneficiaries who received human 

immunodeficiency virus (HIV) and diabetes medications despite having 

no HIV or diabetes-related indicators related to such ailments in their 

fiscal year 2011 Medicaid outpatient claims listed in the MSIS “other 

services” file. The absence of such evidence does not prove that the 

beneficiary did not have HIV or diabetes or that there was inappropriate 

off-label use: the claims files we used were for a limited period and did 

not reflect the beneficiary’s entire history, and our search may not have 

included every possible diagnosis or service code related to HIV and 

diabetes. We selected the HIV medications Atripla, Combivir, Norvir, 

Reyataz, and Truvada based on their specific use as a treatment for HIV 

as well as a preliminary examination of the MSIS data. We selected the 

diabetes medications Actos, Humalog, Lantus, and Novolog based on 

their primary use as a treatment for diabetes as well as a similar review of 

the MSIS data. We selected these drugs and drug classes because they 

were received by a relatively large number of beneficiaries and had a high 

expense to Medicaid. In addition, when we examined the Food and Drug 

Administration indications and usage labeling for each drug, we found 

that each drug was only approved for treatment of HIV or diabetes.9 For 

each beneficiary who received one of these drugs, we reviewed the MSIS 

“other services” file to determine whether the beneficiary (1) had an 

International Classification of Diseases diagnosis code related to HIV or 

diabetes, (2) had a Healthcare Common Procedure Coding System 

service code related to HIV or diabetes, or (3) had claims associated with 

the prescribing physician.10

 7

Our analysis did not control for medications where there was not a generic version 

available. 

We removed beneficiaries from our analysis if 

they exhibited one of these characteristics and reported on the remaining 

8

When a change to a prescription is made or when a beneficiary fails to pick up the 

prescribed drugs, the pharmacy must adjust the claim transaction. According to officials in 

New Jersey, instances of pharmacies with too many or too few adjustments may be red 

flags for concern.

9

Our review did not include all drugs that may be used to treat HIV or diabetes.

10This analysis was based on diagnosis codes for HIV or diabetes. We did not account for 

prescribing of these medications for other ailments. 
Appendix I: Objectives, Scope, and 

Methodology

Page 42 GAO-15-390 Medicaid Pharmacy Fraud

population. We restricted our review to only include beneficiaries who 

received at least one prescription written during fiscal year 2011.

We also matched the Medicaid data to other external sources to identify 

potential fraud and improper payments. We compared the beneficiary and 

prescriber identity information shown in the Medicaid claims data to the 

Social Security Administration’s (SSA) complete file of death information 

from October 2012 to determine whether any individuals were reportedly 

deceased before or when they purportedly prescribed, dispensed, or 

received prescription drugs covered by Medicaid. To identify prescriptiondrug claims that might have been improperly processed and paid by the 

Medicaid program because either the prescribers or beneficiaries were 

incarcerated, we matched our selected states’ MMIS data to the states’

departments of corrections prisoner databases. Prisoner data included 

individuals incarcerated for any period during fiscal year 2011. For 

Arizona, Florida, and New Jersey, we identified provider and beneficiary 

records for which the Medicaid Social Security number (SSN) and names 

matched that of a person who was incarcerated in fiscal year 2011 in any 

of the four states. Michigan did not provide SSNs in its incarceration data. 

For Michigan, we identified provider and beneficiary records for which the 

Medicaid name and birth day exactly matched that of a person who was 

incarcerated in fiscal year 2011 in any of the four states. We then 

identified Medicaid claims associated with the identified individuals by 

matching to the MSIS data. We compared the beginning service date of 

the claims to the individual’s admittance and release date to identify all 

claims that occurred while the associated beneficiary or provider identity 

was incarcerated. Additionally, we reviewed these claims’ type of service 

to determine that none qualified for federal matching funds.

It is not possible to determine from data matching alone whether these 

matches definitively identify recipients who were deceased or 

incarcerated without reviewing the facts and circumstances of each case. 

For example, it is possible that individuals can be erroneously listed in the 

full Death Master File. Similarly, a provider or beneficiary may have an 

SSN, name, and date of birth similar to an individual in state prison 

records. Alternatively, our matches may also understate the number of 

deceased or incarcerated individuals receiving assistance because 

matching would not detect applicants whose identifying information in the 

Medicaid data differed slightly from their identifying information in other 

databases.

To identify Medicaid beneficiaries who received benefits in two or more 

states concurrently, we identified all beneficiary SSNs that appeared in 
Appendix I: Objectives, Scope, and 

Methodology

Page 43 GAO-15-390 Medicaid Pharmacy Fraud

two or more states’ MMIS data in fiscal year 2011. We then found all 

claims associated with the beneficiary identities. We conducted further 

analysis to determine the states in which each beneficiary identity 

appeared and the service ranges—first and last prescribed date—for 

those states. We defined a concurrent claim as a claim that occurred 

within the service range of a second state for the same beneficiary 

identity. For each claim, we compared its prescription date to the service 

ranges for the beneficiary identity to determine whether it was a 

concurrent claim. It is not possible to definitely say through data matching 

alone that a beneficiary was improperly receiving Medicaid benefits in two 

or more states concurrently without looking into further information for 

each claim and beneficiary. For example, a beneficiary could have been a 

resident in one state and received services, then changed residency to a 

second state and received benefits for a brief period, before finally 

relocating again back to the original state and receiving additional 

services. In this case, the claims could have been identified as a 

concurrent claim even if the beneficiary did not receive any services from 

the original state during his or her relocation period in the second state.

To identify claims that might have been improperly processed and paid by 

the Medicaid program because the federal government had excluded 

these providers from providing services to Medicaid beneficiaries, we 

compared the Medicaid claims to the exclusion and debarment files from 

the Department of Health and Human Services’ (HHS) Office of Inspector 

General (OIG) and the General Services Administration (GSA). 

Specifically, we used the HHS List of Excluded Individuals and Entities 

file from September 2012 and the GSA Excluded Parties List System 

database extract from October 2011 to perform our match. We matched 

MMIS and MSIS Medicaid data using SSN and individual name with both 

the List of Excluded Individuals and Entities and the Excluded Parties List 

System data extracts. We then identified unique individuals who had 

Medicaid claims processed where the date of exclusion occurred before 

the prescribed date in the Medicaid claims file.

To determine the extent to which federal and state oversight policies, 

controls, and processes are designed to prevent and detect instances of 

prescription-drug fraud in Medicaid, we reviewed CMS and state Medicaid 

policies pertinent to program integrity over pharmaceuticals, met with 

CMS officials, and visited state Medicaid offices that perform oversight 

functions for the four states we selected. We used federal standards for
Appendix I: Objectives, Scope, and 

Methodology

Page 44 GAO-15-390 Medicaid Pharmacy Fraud

internal control,11 GAO’s Fraud Prevention Framework,12

To determine the reliability of the data used in our analysis, we performed 

electronic testing to determine the validity of specific data elements in the 

federal and selected state databases that we used to perform our work. 

We also interviewed officials responsible for their respective databases, 

and reviewed documentation related to the databases and literature 

related to the quality of the data. On the basis of our discussions with 

agency officials and our own testing, we concluded that the data elements 

used for this report were sufficiently reliable for our purposes.

and Medicaid 

statutes and regulations addressing the administration of pharmacy 

benefits to evaluate these functions.

We identified criteria for Medicaid fraud controls by examining federal and 

state policies, laws, and guidance, including policy memos and manuals. 

We interviewed officials from CMS and the state governments of Arizona, 

Florida, Michigan, and New Jersey involved in Medicaid program 

administration, auditing, and Medicaid fraud response.

We conducted this performance audit from March 2014 to July 2015 in 

accordance with generally accepted government auditing standards. 

Those standards require that we plan and perform the audit to obtain 

sufficient, appropriate evidence to provide a reasonable basis for our 

audit findings and conclusions based on our audit objectives. We believe 

that the evidence obtained provides a reasonable basis for our findings 

and conclusions based on our audit objectives.

 11GAO, Standards for Internal Control in the Federal Government, GAO/AIMD-00-21.3.1

(Washington, D.C.: November 1999).

12GAO, Individual Disaster Assistance Programs: Framework for Fraud Prevention, 

Detection, and Prosecution, GAO-06-954T (Washington, D.C.: July 12, 2006).
Appendix II: Comments from the Department 

of Health and Human Services

Page 45 GAO-15-390 Medicaid Pharmacy Fraud

Appendix II: Comments from the Department 

of Health and Human Services
Appendix II: Comments from the Department 

of Health and Human Services

Page 46 GAO-15-390 Medicaid Pharmacy Fraud
Appendix II: Comments from the Department 

of Health and Human Services

Page 47 GAO-15-390 Medicaid Pharmacy Fraud
Appendix III: Comments from the Social 

Security Administration

Page 48 GAO-15-390 Medicaid Pharmacy Fraud

Appendix III: Comments from the Social 

Security Administration
Appendix IV: Comments from the Arizona 

Health Care Cost Containment System

Page 49 GAO-15-390 Medicaid Pharmacy Fraud

Appendix IV: Comments from the Arizona 

Health Care Cost Containment System
Appendix IV: Comments from the Arizona 

Health Care Cost Containment System

Page 50 GAO-15-390 Medicaid Pharmacy Fraud
Appendix IV: Comments from the Arizona 

Health Care Cost Containment System

Page 51 GAO-15-390 Medicaid Pharmacy Fraud
Appendix IV: Comments from the Arizona 

Health Care Cost Containment System

Page 52 GAO-15-390 Medicaid Pharmacy Fraud
Appendix V: Comments from the State of 

Florida Agency for Health Care Administration

Page 53 GAO-15-390 Medicaid Pharmacy Fraud

Appendix V: Comments from the State of 

Florida Agency for Health Care 

Administration
Appendix VI: Comments from the New Jersey 

Department of Human Services

Page 54 GAO-15-390 Medicaid Pharmacy Fraud

Appendix VI: Comments from the New 

Jersey Department of Human Services
Appendix VI: Comments from the New Jersey 

Department of Human Services

Page 55 GAO-15-390 Medicaid Pharmacy Fraud
Appendix VI: Comments from the New Jersey 

Department of Human Services

Page 56 GAO-15-390 Medicaid Pharmacy Fraud
Appendix VI: Comments from the New Jersey 

Department of Human Services

Page 57 GAO-15-390 Medicaid Pharmacy Fraud
Appendix VII: GAO Contact and Staff 

Acknowledgments

Page 58 GAO-15-390 Medicaid Pharmacy Fraud

Seto Bagdoyan, (202) 512-6722 or bagdoyans@gao.gov

In addition to the contact named above, Matthew Valenta (Assistant 

Director), John Ahern, Mariana Calderón, Melinda Cordero, Julia DiPonio, 

Lorraine Ettaro, Colin Fallon, Katherine Iritani, Barbara Lewis, Maria 

McMullen, Kevin Metcalfe, Rubén Montes de Oca, James Murphy, 

Christine San, and Paola Tena made key contributions to this report.

Appendix VII: GAO Contact and Staff 

Acknowledgments

GAO Contact

Staff 

Acknowledgments

(192444)
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