Department of Health and Human Services
OFFICE OF 
    
IN  SPECTOR GENERAL 
 
 
 
 
 
 
 
 
E P D
FFECT OF THE  ART   
 
C   G M
OVERAGE  AP ON  EDICARE 
 
B W
EN EFICIARIES  ITHOUT 
 
F A 2006
INANCIAL  SSISTANCE IN 
 
 
 
 
 
Daniel R. Levinson  
Inspector General 
 
March 2009 
OEI-05-07-00610   
Office of Inspector General 
http://oig.hhs.gov 
 
The mission of the Office of Inspector General (OIG), as mandated by Public Law 95-452, as 
amended, is to protect the integrity ofthe Department of Health and Human Services (HHS) 
programs, as well as the health and welfare of beneficiaries served by those programs.  This 
statutory mission is carried out through a nationwide network of audits, investigations, and 
inspections conducted by the following operating components: 
Office of Audit Services 
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audits with its own audit resources or by overseeing audit work done by others.  Audits examine 
the performance of HHS programs and/or its grantees and contractors in carrying out their 
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Office of Evaluation and Inspections 
The Office of Evaluation and Inspections (OEI) conducts national evaluations to provide 
HHS, Congress, and the public with timely, useful, and reliable information on significant 
issues.  These evaluations focus on preventing fraud, waste, or abuse and promoting 
economy, efficiency, and effectiveness in departmental programs.  To promote impact, OEI 
reports also present practical recommendations for improving program operations.  
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The Office of Investigations (OI) conducts criminal, civil, and administrative investigations 
of fraud and misconduct related to HHS programs, operations, and beneficiaries.  With 
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law enforcement authorities.  The investigative efforts of OI often lead to criminal 
convictions, administrative sanctions, or civil monetary penalties. 
Office of Counsel to the Inspector General 
The Office of Counsel to the Inspector General (OCIG) provides general legal services to 
OIG, rendering advice and opinions on HHS programs and operations and providing all 
legal support for OIGs internal operations.  OCIG represents OIG in all civil and 
administrative fraud and abuse cases involving HHS programs, including False Claims Act, 
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also negotiates and monitors corporate integrity agreements.  OCIG renders advisory 
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guidance to the health care industry concerning the anti-kickback statute and other OIG 
enforcement authorities.   
 E X E C U T I V E   S U M M A R Y  
OBJECTIVES
 
1.  To determine the number of Medicare beneficiaries who did not 
receive financial assistance with prescription drugs during the   
Part D coverage gap in 2006. 
2.  To determine changes in prescription drug purchases and payments 
by these beneficiaries. 
BACKGROUND 
Medicare Part D provides an optional drug benefit to Medicare 
beneficiaries.  The Centers for Medicare & Medicaid Services (CMS) 
contracts with private insurance companies, known as plan sponsors, to 
provide prescription drug coverage for beneficiaries who choose to enroll 
in the program.     
During the coverage year, the financial responsibilities of beneficiaries, 
plan sponsors, and CMS vary during each of four distinct coverage 
phases for the standard benefit:  annual deductible, initial coverage, 
coverage gap, and catastrophic coverage.  The coverage phase 
determines a beneficiarys share of the drug cost at the point of sale.  
After reaching the initial coverage limit, beneficiaries enter the 
coverage gap phase and are responsible for 100 percent of drug costs.  
Beneficiaries may receive financial assistance for drug costs during the 
coverage gap phase from their plans; from low-income subsidies; or from 
other approved third-party payers, such as State Pharmacy Assistance 
Programs. 
We used Medicare Part D prescription drug data to determine the 
number of Medicare beneficiaries who did not receive financial 
assistance with prescription drug costs during the coverage gap in 2006.  
We also assessed beneficiary changes in drug purchasing behavior and 
payments during the coverage gap.  Finally, we conducted a national 
beneficiary survey to further enhance our analysis of beneficiary 
changes in drug purchasing and use behaviors during the coverage gap. 
FINDINGS 
Seven percent of Part D beneficiaries entered the coverage gap and 
did not receive financial assistance with prescription drug costs.  Of 
the more than 22 million Part D beneficiaries who filled at least one 
prescription in 2006, 1.5 million beneficiaries had gross covered drug 
    E X E C U T I V E   S U M M A R Y  
costs exceeding the initial coverage limit of $2,250 and did not receive any 
financial assistance in paying for drugs during the coverage gap.   
During the coverage gap, drug purchasing behavior changed for 
almost all beneficiaries who did not receive financial assistance.  
Of the beneficiaries who did not receive financial assistance during the 
2006 coverage gap, 98 percent made some changes in their drug 
purchasing behavior.  Sixty-nine percent of beneficiaries decreased the 
average number of drugs purchased during the coverage gap.  This 
decrease could have represented a strategy that beneficiaries used to 
reduce their financial burden during the coverage gap, or it could have 
represented appropriate reductions due to changes in their health 
status. 
The greater the average number of drugs per month that beneficiaries 
purchased before entering the coverage gap, the more they reduced the 
average number of drugs per month that they purchased during the 
coverage gap.  Beneficiaries who purchased an average of at least nine 
drugs per month had the largest decrease at 18 percent.   
When a sample of beneficiaries similar to those included in the above 
analysis was surveyed, they identified specific types of changes in drug 
purchasing behavior and use.  Thirty-eight percent of beneficiaries 
reported seeking at least one less-costly alternative to purchasing drugs.  
On the other hand, 20 percent of the beneficiaries surveyed may have been 
eligible for but not enrolled in a low-income subsidy that could have 
assisted them with purchasing drugs during the coverage gap.  
Additionally, one-third of the beneficiaries surveyed appeared to have 
compromised their drug regimens with changes in use.  
RECOMMENDATIONS 
CMS should support outreach and education activities targeted at 
beneficiaries who make more prescription drug purchases before 
entering the coverage gap.  CMS could encourage plan sponsors to 
augment their outreach and education efforts by using drug utilization 
data to target beneficiaries who purchased nine or more drugs per month 
during the initial coverage phase.  CMS could also supplement plan 
sponsors outreach and education efforts by working directly with these 
beneficiaries to explore cost-saving strategies for prescription drugs and 
the tools available for choosing different benefit packages (in which they 
could enroll during the next open season). 
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CMS should target low-income subsidy outreach to 
beneficiaries who entered the coverage gap without financial 
assistance.  Targeting the population of beneficiaries who entered the 
coverage gap without financial assistance in previous years might be 
one way to identify eligible beneficiaries for enrollment in the 
low-income subsidy program.  In addition, beneficiaries who enter the 
coverage gap without financial assistance for prescription drug costs 
might benefit from more education about applying for the low-income 
subsidy that can assist them throughout the rest of the benefit year, 
including during the coverage gap. 
AGENCY COMMENTS AND OFFICE OF INSPECTOR GENERAL 
RESPONSE 
CMS generally agreed with our findings and stated that it appreciated 
the additional information provided through the beneficiary survey.  
CMS noted that our findings were similar to the results of CMSs 
analysis presented at the Medicare Drug Benefit Symposium, held in        
October 2008.  However, CMS indicated a concern about the lack of a 
control group with which to compare our results.  As a result, CMS 
pointed out that this evaluation does not provide a true causal analysis.  
This is accurate, as the report does not present a true causal analysis.  
Rather, it presents data about drug purchases with a number of 
plausible explanations of those data, including the possibility that the 
decrease in drug purchases was the result of the coverage gap.  
CMS did not concur with our first recommendation.  CMS stated that it 
believed its current outreach to all beneficiaries is sufficient.  However, 
we found that beneficiaries who made more prescription drug purchases 
before entering the coverage gap had the largest drop in the number of 
drugs purchased during the coverage gap.  Because these beneficiaries 
take more prescription drugs, they are likely in poorer health and are 
the most vulnerable to negative health consequences from 
nonadherence to drug regimens.  Therefore, additional outreach and 
education about efficient and effective drug purchasing options targeted 
at this group of beneficiaries could have far-reaching health benefits. 
CMS concurred with our second recommendation.  However, the actions 
CMS stated it would take do not address our recommendation to use 
drug utilization data to identify potential beneficiaries for the subsidy. 
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E X E C U T I V E   S U M M A R Y  
 T A B L E   O F   C O N T E N T S  
 
 
EXECUTIVE SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i 
 
I N T RO DUC T IO N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 
 
F I N D IN G S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 
Seven percent of Part D beneficiaries entered the coverage gap 
without financial assistance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 
During the coverage gap, drug purchasing behavior changed . . . 12 
 
R E C O MMEN D A T ION S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 
Agency Comments and Office of Inspector General Response . . . 20 
 
APPENDIXES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 
  A:  Detailed methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 
  B:  Beneficiary survey responses . . . . . . . . . . . . . . . . . . . . . . . . . . 27 
  C:  Nonresponse analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 
    D:  Estimates and confidence intervals . . . . . . . . . . . . . . . . . . . . . 34 
    E:  Agency Comments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 
 
A C K NO WL E D G M E N T S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 
     
 
 I N T R O D U C T I O N  
OBJECTIVES 
1.  To determine the number of Medicare beneficiaries who did not 
receive financial assistance with prescription drugs during the    
Part D coverage gap in 2006. 
2.  To determine changes in prescription drug purchases and payments 
by these beneficiaries. 
BACKGROUND 
Research suggests that the Medicare Part D coverage gap may affect 
beneficiaries prescription drug use behaviors.  A 2006 national survey 
of noninstitutionalized Medicare beneficiaries found that rates of 
nonadherence to a drug regimen because of costs were greater for 
Part D beneficiaries than for seniors with the Veterans Administration 
or an employer-sponsored prescription drug plan.1  The study suggested 
that beneficiaries who entered the Medicare Part D coverage gap may 
have changed their prescription drug use behaviors because they were 
responsible for 100 percent of their drug costs during the coverage gap.2  
Additional research suggests that Medicare beneficiaries whose benefits 
were capped use fewer prescription drugs overall and fewer drugs for 
treatment of chronic diseases.3   
The Medicare Part D Prescription Drug Benefit 
Medicare Part D provides an optional outpatient prescription drug 
benefit to Medicare beneficiaries.4  The Centers for Medicare & 
Medicaid Services (CMS) contracts with private entities, known as plan 
sponsors, to provide prescription drug coverage for beneficiaries who 
choose to enroll in the program.  These plan sponsors may offer a 
stand-alone prescription drug plan or they may offer prescription drug 
coverage as part of a managed care plan, known as a Medicare 
Advantage prescription drug plan (hereinafter referred to collectively as 
plans).   
 
1 Patricia Neuman, et al., Medicare Prescription Drug Benefit Progress Report:  
Findings From a 2006 National Survey of Seniors.  Health Affairs, vol. 26, no. 5, 
August 21, 2007. 
2 Ibid. 
3 John Hsu, et al., Unintended Consequences of Caps on Medicare Drug Benefits.  The 
New England Journal of Medicine, vol. 354, no. 22, June 1, 2006. 
4 The Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA), 
P.L. No. 108-173  101, Social Security Act,  1860D, 42 U.S.C.  1395w-101(a). 
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Part D Coverage 
During the coverage year, the financial responsibilities of beneficiaries, 
plan sponsors, and CMS vary during each of four distinct coverage 
phases for the standard benefit:  annual deductible, initial coverage, 
coverage gap, and catastrophic coverage.5  The coverage phase 
determines a beneficiarys cost.6  In general, beneficiaries are 
responsible for a monthly premium; a deductible; and cost-sharing at 
the point of sale, which can be either percentage-based coinsurance or a 
fixed copayment.  
To determine the coverage phase, plan sponsors must track prescription 
drug costs and payments every time a beneficiary fills a prescription 
under Part D.  Cost data include the cost of the drug, dispensing fee, 
and sales tax.  Payment data include all payments made by plan 
sponsors; beneficiaries; and other approved third-party payers, such as 
State Pharmacy Assistance Programs (SPAP).7  
Part D Coverage Types 
The MMA permits plan sponsors to offer plans with either standard 
prescription drug coverage or alternative prescription drug coverage.8  
Alternative prescription drug coverage may be either actuarially 
equivalent to standard prescription drug coverage or enhanced.9  Plan 
benefits, including formularies, premiums, deductibles, and beneficiary 
cost-sharing requirements, vary according to coverage type. 10 
Standard coverage.  In 2006, standard plans had an initial deductible of 
$250.11  In all standard plans, after paying the deductible, beneficiaries 
enter the initial coverage phase.  During initial coverage, beneficiaries 
pay a 25-percent coinsurance toward Part D drug costs.  Initial coverage 
continues until gross covered drug costs reach the initial coverage limit 
 
5 CMS, 2007 Prescription Drug Event Data Training Participant Guide, Module 4  
Calculating and Reporting the Basic Benefit, p. 4-3, 2007.   
6 Ibid. 
7 Other approved third-party payers include health savings accounts, flexible spending 
accounts, medical savings accounts, and certain charities. 
8 MMA, P.L. No. 108-173  101, Social Security Act,  1860D, 42 U.S.C.  1395w-102(a). 
9 42 CFR  423.104(e) and (f). 
10 MMA, P.L. No. 108-173  101, Social Security Act,  1860D, 42 U.S.C.  1395w-102(b) 
and (c). 
11 42 CFR  423.104(d)(1). 
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I N T R O D U C T I O N  
established by law.12  Gross covered drug costs are the total cost of 
drugs (including dispensing fee and sales tax) regardless of payer. 
After reaching the initial coverage limit, beneficiaries in most plans 
enter the coverage gap phase and are responsible for 100 percent of 
drug costs.  The coverage gap continues until beneficiaries true 
out-of-pocket (TrOOP) spending reaches the annual TrOOP threshold.13  
Generally, TrOOP spending includes all beneficiary payments 
(excluding monthly premiums) and any payments made by approved 
third-party payers.14 
After reaching the TrOOP threshold, beneficiaries enter the 
catastrophic coverage phase.  During catastrophic coverage, 
beneficiaries pay approximately 5 percent in coinsurance toward Part D 
drug costs,15 plans pay approximately 15 percent, and CMS pays plans 
the remaining 80 percent. 
The maximum amount that beneficiaries pay out of pocket for the 
deductible and during the initial coverage and coverage gap phases are 
adjusted yearly.16  The 2006 standard coverage thresholds are shown in 
Table 1.   
 
Table 1:  2006 Standard Coverage Cost-Sharing Thresholds by Benefit Phase 
     Cost-Sharing 
Beneficiary   Plan  CMS 
Maximum  Percentage   Maximum  Percentage 
Maximum  Percentage  Total  of Drug  Total  of Drug 
Benefit Phase  Gross Drug Costs  Total Cost*  of Drug Cost  Cost  Cost  Cost  Cost 
Deductible  $250  $250  100%  $0  0%  $0  0% 
Initial coverage   > $250 to $2,250  $500  25%  $1,500  75%  $0  0% 
Coverage gap  > $2,250 to $5,100  $2,850  100%  $0  0%  $0  0% 
 approximately 
Catastrophic coverage  generally > $5,100  **  5%  **  15%  **  80% 
* The beneficiarys maximum total cost does not include monthly premiums. 
** The amount paid depends on the amount of drugs purchased during catastrophic coverage. 
Source:  CMS 2007 Prescription Drug Event Data Training Participant Guide, 2007. 
 
 
12 MMA, P.L. No. 108-173  101, Social Security Act,  1860D, 
42 U.S.C.  1395w-102(b)(3)(A). 
13 42 CFR  423.104(d)(5)(iii). 
14 CMS, Prescription Drug Benefit Manual, ch. 5  30. 
15 42 CFR  423.104(d)(5)(B). 
16 42 CFR  423.104(d)(1)(5). 
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Actuarially equivalent coverage.  Actuarially equivalent plans offer 
coverage that is at least equal to the value of standard coverage.17  
Actuarially equivalent plans may contain a coverage gap phase.  
However, they may increase the initial coverage limit, which could 
make the entry point into the coverage gap different from the entry 
point under standard coverage.  Actuarially equivalent plans can also 
offer lower or no deductibles and copayments instead of coinsurance at 
the point of sale. 
Enhanced coverage.  Enhanced plans must provide supplemental 
benefits in addition to providing standard prescription drug coverage.18  
As part of their supplemental benefits package, enhanced plans must 
offer coverage of drugs that are specifically excluded as Part D drugs or 
at least one feature that increases the value above the actuarial value of 
standard coverage.19  Features that can be used to increase the 
actuarial value of benefits include lower deductibles, an increase in the 
initial coverage limit, or reductions in cost sharing at the point of sale.  
Although enhanced plans may provide lower beneficiary cost-sharing 
obligations or full coverage during the coverage gap, most enhanced 
plans did not in 2006. 
Part D Enrollment 
In 2006, 22.5 million Medicare beneficiaries were enrolled in Part D 
plans.20  Enrollment varied among coverage types:  17 percent of Part D 
beneficiaries were enrolled in standard coverage plans, 52 percent in 
actuarially equivalent coverage plans, and 30 percent in enhanced 
coverage plans.21 22   
 
 
 
 
17 MMA, P.L. No. 108-173  101, Social Security Act,  1860D, 
42 U.S.C.  1395w-102(c)(1)(A). 
18 42 CFR  423.104(f). 
19 42 CFR  423.104(f)(1)(ii). 
20 The Henry J. Kaiser Foundation, Medicare Data Update:  Prescription Drug Coverage 
Among Medicare Beneficiaries, June 2006.  Available online at 
http://www.kff.org/medicare/upload/7453.pdf.  Accessed on August 1, 2008. 
21 Juliette Cubanski, Patricia Neuman, Status Report on Medicare Part D Enrollment 
in 2006:  Analysis of Plan-Specific Market Share and Coverage, Health Affairs, 26, p. w6, 
2007.   
22 Percentages do not add to 100 percent because of rounding.  
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Part D Drugs 
Covered Part D drugs are the subset of Part D drugs that are included 
on a Part D plans formulary.23  Part D excludes drugs for which 
payment is available under Medicare Parts A or B and drugs that may 
be excluded from coverage or otherwise restricted under Medicaid, 
except for smoking cessation agents. 
Subject to a plans formulary, Part D covers both generic and         
brand-name drugs.  A generic drug is chemically identical to its     
brand-name counterpart, with the same therapeutic effect and          
risk-benefit profile.  Generally, generic drugs are cheaper than       
brand-name drugs.  According to the National Association of Chain 
Drug Stores, in 2006 the average brand-name prescription drug cost 
$107.48, while the average generic prescription drug cost $31.39a     
71-percent difference.24  Although the use of generic drugs may help 
reduce costs, this reduction is possible only when a physician prescribes 
a generic drug or a pharmacist substitutes a generic drug if one is 
available for the prescribed brand-name drug. 
Part D Low-Income Subsidy 
To be eligible for a low-income subsidy, a beneficiary must meet an 
income and asset test.  A beneficiarys annual income must be less than 
150 percent of the Federal poverty level (FPL) ($14,700 for an individual 
and $19,800 for a married couple living together in 2006).  The value of 
assets, including bank accounts, stocks, bonds, and real estate other 
than the beneficiarys primary residence, must be below $10,000 for 
individuals and $20,000 for married couples.   
Beneficiaries with such limited income and assets are eligible to receive 
assistance to pay the out-of-pocket costs associated with their 
prescription drug coverage.  The fewer financial resources an eligible 
beneficiary has, the lower his or her out-of pocket costs will be in all 
coverage phases, including the coverage gap.  Some beneficiaries receive 
drug coverage with no monthly premium, no annual deductible, and no 
copayments at the point of sale.  Other beneficiaries pay copayments 
ranging from $1 to $5 but do not pay monthly premiums or annual 
 
23 Covered Part D drugs also include those that are on a Part D plans formulary as a 
result of a coverage determination or appeal. 
24 National Association of Chain Drug Stores, Industry Facts at a Glance:  
Pharmaceutical Pricing.  Available online at 
http://www.nacds.org/wmspage.cfm?parm1=507.  Accessed on June 6, 2008. 
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deductibles.  Still other beneficiaries have a sliding-scale monthly 
premium, a $50 deductible, and a coinsurance of 15 percent at the point 
of sale.  Beneficiaries who receive the low-income subsidy are not 
subject to the coverage gap. 
Previous Office of Inspector General Work 
The Office of Inspector General (OIG) has conducted many studies 
related to Part D, including generic drug utilization in Part D,25 
identifying beneficiaries for the low-income subsidy,26 CMSs tracking of 
beneficiaries TrOOP costs,27 and dual eligibles transition from 
Medicaid to Medicare.28   
METHODOLOGY 
Scope   
This study explores the effect of the coverage gap on beneficiaries drug 
purchases during 2006 by focusing on beneficiaries without financial 
assistance (i.e., from plans; low-income subsidies; or other approved 
third-party payers, such as SPAP).  During the coverage gap, 
beneficiaries with financial assistance did not face the same financial 
burden related to purchasing prescription drugs as beneficiaries without 
financial assistance.  Thus, our analysis excludes beneficiaries who had 
financial assistance during the coverage gap.  In addition, this study 
included only Part D-covered drugs in our analysis, as only those 
purchases count toward the initial coverage limit and beneficiaries 
TrOOP costs.   
Data Sources 
We used 2006 Prescription Drug Event (PDE) data to conduct this 
study.  CMS requires plans providing prescription drug coverage to 
submit PDE data for payment purposes.  Each drug event included in 
these data represents the dispensing of a drug or medical supply for the 
injection of insulin.   
 
25 OIG, Generic Drug Utilization in the Medicare Part D Program, OEI-05-07-00130, 
November 2007. 
26 OIG, Identifying Beneficiaries Eligible for the Medicare Part D Low-Income Subsidy,     
OEI-03-06-00120, November 2006. 
27 OIG, Tracking Beneficiaries True Out-of-Pocket Costs for the Part D Prescription 
Drug Benefit, OEI-03-06-00360, December 2007. 
28 OIG, Dual Eligibles Transition:  Part D Formularies Inclusion of Commonly Used 
Drugs, OEI-05-06-00090, January 2006. 
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We used two drug data compendia to supplement the PDE data.  For 
each claim, these compendia indicated whether the prescribed drug was 
a brand-name or generic drug and whether the drug was typically 
prescribed to treat a chronic or an acute condition. 
In addition, we conducted a national survey of beneficiaries.  Using 
the PDE data, we selected a simple random sample of                      
300 beneficiaries who had gross covered drug costs greater than the 
initial coverage limit of $2,250.  We excluded all beneficiaries with 
low-income subsidies or those who were enrolled in enhanced plans 
from our sample to remove beneficiaries who might have received 
assistance during the coverage gap.  The survey was distributed by 
mail in February 2008 and data collection lasted through March 2008.   
Upon receiving the surveys, we removed beneficiaries who appeared 
to have received financial assistance during the coverage gap.  We 
used 2006 PDE data to determine which beneficiaries did not pay           
100 percent of their drug costs during the coverage gap.  After 
removing any beneficiary who did not pay 100 percent of drug costs, 
we had a sample of 176 beneficiaries.  Of these 176 beneficiaries,     
142 responded to our survey, for an 81-percent response rate. 
Because the survey was conducted in 2008, beneficiaries may have 
also been in the coverage gap in 2007.  Therefore, we asked 
beneficiaries about their general experiences while in the coverage 
gap and did not ask them to tie their experiences to a specific year.  
The survey asked beneficiaries to identify, from predetermined lists of 
options, changes they made in how they used and purchased 
prescription drugs after entering the coverage gap.  It also requested 
information such as marital status and income range. 
For a complete list of the data sources and other aspects of the 
methodology, see Appendix A.  For a copy of the beneficiary survey 
and for the total responses, see Appendix B. 
Data Analysis 
Determining the number of beneficiaries in the coverage gap.  To establish 
how many beneficiaries entered the coverage gap and did not have 
financial assistance, we summed the appropriate cost and payment 
fields in the PDE data for Part D-covered drugs to determine which 
beneficiaries had gross covered drug costs exceeding the initial coverage 
limit.  After identifying this population of beneficiaries, we selected all 
of their 2006 PDE claims for Part D-covered drugs (hereinafter referred 
to as drugs).  Using the date when each beneficiary entered the coverage 
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I N T R O D U C T I O N  
gap and the date each became eligible for catastrophic coverage (if 
applicable), each claim was assigned to the proper coverage phase for 
that beneficiary:  initial coverage (including deductible phase), coverage 
gap, and catastrophic coverage.29  We then excluded beneficiaries who 
did not pay 100 percent of their drug costs during the coverage gap to 
remove beneficiaries who had financial assistance in the coverage gap.   
Using these claims data, we calculated a number of descriptive 
measures.  We determined the average number of days it took 
beneficiaries to enter the coverage gap, how long they remained in the 
coverage gap, and when they left the coverage gap for catastrophic 
coverage. 
Analyzing changes in beneficiary drug purchases.  To measure 
prescription drug purchasing in each coverage phase, we calculated 
three measures:  (1) average number of prescription drugs purchased 
per month, (2) percentage of prescription drugs purchased to treat 
chronic and acute conditions, and (3) generic drug utilization rate. 
To calculate the average number of prescription drugs purchased per 
month by coverage phase, we calculated the unique number of drugs by 
beneficiary by month.  Then, for each coverage phase, we divided the 
total number of unique drugs by beneficiary by the total number of 
months. 
For purposes of this analysis, in all prescription data, we normalized the 
data by the number of days that the prescription covered.  We 
considered PDE data with a supply of less than or equal to 44 days as 
one prescription; greater than 44 days but less than or equal to 74 days 
as two prescriptions; and greater than 74 days as three prescriptions. 
Analyzing changes in beneficiary drug payments.  To analyze payment in 
each coverage phase, we computed the average and median beneficiary 
payment per phase and the average beneficiary payment per month.  To 
determine the average and median beneficiary payment per phase, we 
used the PDE data field patient pay amount for each beneficiary.  
Patient pay amount is the amount that the beneficiary paid for each 
drug.  We calculated the average beneficiary payment per month by 
 
29 For purposes of this analysis, the deductible and initial coverage phases were 
combined. 
 
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I N T R O D U C T I O N  
dividing the total beneficiary payment by the total number of months in 
that phase. 
Analyzing beneficiary survey responses.  To analyze beneficiary survey 
responses, we calculated basic frequencies on the key questions related 
to beneficiaries changes in drug purchases and use during the coverage 
gap.  We conducted a nonresponse analysis to see how our survey 
estimates might be affected by potential nonresponse bias and found no 
evidence of bias.  Appendix C provides details of the nonresponse 
analysis. 
We projected all survey statistics to beneficiaries who entered the 
coverage gap, were not enrolled in enhanced plans, did not receive 
low-income subsidies, and paid 100 percent of drug costs during the 
coverage gap based on their 2006 PDE claims.  See Appendix D for a 
list of 95-percent confidence intervals for all statistical projections. 
Data Limitations 
Our analysis of PDE data covered only prescription drugs purchased 
through Part D.  Because PDE data do not capture prescription drug 
purchases outside Part D, we could not capture the full extent of 
beneficiaries prescription drug purchases.  In addition, SPAP 
assistance with prescription drug costs would only have been visible in 
the PDE data if the SPAP coordinated with Part D.  However, our 
survey analysis asked beneficiaries about the use of free medication 
samples and purchases made outside their Part D plans in an attempt 
to gather this information. 
Because we chose to base our analysis of the PDE data on the number of 
months in which beneficiaries filled a prescription, not enrollment 
months, our results are not comparable to standard industry 
per-member-per-month measures, which are based on enrollment 
months.  For example, our analysis of the average number of drugs per 
month may be higher than industry averages.  However, this analytic 
choice does not change the relative decrease in the average number of 
drugs purchased per month after entering the coverage gap. 
The population to which we project our survey sample is different from 
the population used to conduct the PDE analysis.  Both populations 
excluded beneficiaries who received financial assistance during the 
coverage gap.  The survey population, however, excluded all 
beneficiaries enrolled in enhanced plans, some of whom may not have 
received assistance during the coverage gap.  In other words, the survey 
population, because of the means used to target beneficiaries, may not 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE   9   
 
I N T R O D U C T I O N  
represent all beneficiaries who did not receive assistance during the 
coverage gap.  
Standards 
This study was conducted in accordance with the Quality Standards for 
Inspections issued by the Presidents Council on Integrity and 
Efficiency and the Executive Council on Integrity and Efficiency.
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  10   
 
IFF NII NNNT RDDD OIII NNND GGGU SSSC    T I O N  
 F I N D I N G S  
  
Seven percent of Part D beneficiaries entered  OOff  tthhee  2222  mmiilllliioonn  PPaarrtt  DD  
the coverage gap and did not receive financial  bbeenneeffiicciiaarriieess  wwhhoo  ffiilllleedd  aatt  lleeaasstt  oonnee  
assistance with their prescription drug costs  pprreessccrriippttiioonn  iinn  22000066,,  77  ppeerrcceenntt  hhaadd  
ggrroossss  ccoovveerreedd  ddrruugg  ccoossttss  eexxcceeeeddiinngg  
tthhee  iinniittiiaall  ccoovveerraaggee  lliimmiitt  ooff  $$22,,225500  aanndd  ddiidd  nnoott  rreecceeiivvee  aannyy  ffiinnaanncciiaall  
aassssiissttaannccee  dduurriinngg  tthhee  ccoovveerraaggee  ggaapp..    TThhiiss  rreepprreesseennttss  aapppprrooxxiimmaatteellyy        
11..55  mmiilllliioonn  bbeenneeffiicciiaarriieess..    IInn  ccoonnttrraasstt,,  2266  ppeerrcceenntt,,  oorr  aapppprrooxxiimmaatteellyy          
55..66  mmiilllliioonn  bbeenneeffiicciiaarriieess,,  hhaadd  ggrroossss  ccoovveerreedd  ddrruugg  ccoossttss  eexxcceeeeddiinngg  tthhee  
iinniittiiaall  ccoovveerraaggee  lliimmiitt  bbuutt  hhaadd  ssoommee  aassssiissttaannccee  dduurriinngg  tthhee  ccoovveerraaggee  ggaapp..    
TThhiiss  aassssiissttaannccee  ccoouulldd  hhaavvee  ccoommee  ffrroomm  tthheeiirr  ppllaannss;;  llooww--iinnccoommee  ssuubbssiiddiieess;;  
oorr  ootthheerr  aapppprroovveedd  tthhiirrdd--ppaarrttyy  ppaayyeerrss,,  ssuucchh  aass  SSPPAAPP..    IInn  ttoottaall,,                              
3333  ppeerrcceenntt  ooff  bbeenneeffiicciiaarriieess  hhaadd  ggrroossss  ccoovveerreedd  ddrruugg  ccoossttss  eexxcceeeeddiinngg  tthhee  
iinniittiiaall  ccoovveerraaggee  lliimmiitt  iinn  22000066..        
TTiimmee  ssppeenntt  bbeeffoorree  tthhee  ccoovveerraaggee  ggaapp.  Beneficiaries who did not have 
financial assistance during the coverage gap took an average of              
7 months to enter the coverage gap.  In fact, 36 percent entered the 
coverage gap in the third quarter of the year, and 45 percent entered 
the coverage gap in the fourth quarter.  Thirteen percent of beneficiaries 
who did not have assistance during the coverage gap entered the 
coverage gap in December.  
Time spent in the coverage gap.  Most beneficiaries who did not have 
financial assistance (83 percent) spent less than 6 months in the 
coverage gap.  Approximately 17 percent spent 6 to 8 months in the 
coverage gap, and less than 1 percent spent 9 to 12 months. 
Money spent during the coverage gap.  While in the coverage gap, 
beneficiaries who did not have financial assistance spent an average 
total of $979, with a median total of $675.  On average, these 
beneficiaries spent $108 per month before entering the coverage gap 
and $290 per month during the coverage gap. 
Beneficiaries who left the coverage gap.  Twelve percent (178,717) of 
beneficiaries without financial assistance during the coverage gap left it 
and entered catastrophic coverage.  Beneficiaries who entered 
catastrophic coverage spent an average of 4.5 months in the coverage 
gap and 2.7 months in catastrophic coverage.  Overall, 59 percent of 
beneficiaries who entered catastrophic coverage did so in the last 
quarter of 2006.  
 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  11   
 
F I N D I N G S  
 
During the coverage gap, drug purchasing  Of the beneficiaries who did 
behavior changed for almost all beneficiaries who  not receive financial 
assistance during the 2006 
did not receive financial assistance  
coverage gap, 98 percent 
made some changes in their drug purchasing behavior.  During the 
coverage gap, 69 percent of beneficiaries decreased the average number 
of drugs purchased, while 29 percent increased the average number of 
drugs purchased. 
For those beneficiaries who decreased the average number of drugs they 
purchased during the coverage gap, the number dropped from an 
average of 4.5 drugs per month to 3.8 drugs per month.  This decrease 
could represent a strategy that beneficiaries used to reduce their 
financial burden during the coverage gap, when they were responsible 
for 100 percent of drug costs.  This explanation is consistent with 
research suggesting that beneficiaries decrease prescription drug use 
when they encounter a gap in coverage.  The decrease could also reflect 
nonadherence to prescribed drug regimens.  On the other hand, the 
reduction could be the result of medically appropriate changes in 
beneficiaries drug regimens due to changes in health status.   
For those beneficiaries who increased the average number of drugs they 
purchased, the number rose from an average of 4.3 drugs per month to 
5.6 drugs per month during the coverage gap.  This increase is most 
likely explained by changes in the beneficiaries drug regimens due to 
changes in health status.  
Overall, changes in drug purchasing behavior did not alter the type of 
drugs purchased as measured by chronic versus acute drugs.  
Beneficiaries used chronic and acute drugs in the same proportions 
before and during the coverage gap, at a rate of approximately            
80-percent chronic and 20-percent acute drugs.  The high percentage of 
drugs that beneficiaries purchased to treat chronic conditions indicates 
that beneficiaries prescription drug needs remain mostly stable over 
time, regardless of purchasing patterns.  Because the percentage of 
acute drugs did not decrease during the coverage gap, the decrease in 
the average number of drugs is likely not explained by the cessation of 
acute medical conditions. 
In addition, beneficiaries increased their utilization rate of generic 
drugs by 8 percent during the coverage gap, from 49 to 53 percent.  
Although the generic utilization rate increased during the coverage gap, 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  12   
 
FF II NN DD II NN GG SS   
it remained lower than the 2006 Part D national generic utilization rate 
of 56 percent.30 
Beneficiaries with more drug purchases before entering the coverage gap 
made greater changes in their drug purchasing behavior during the 
coverage gap 
The greater the average number of drugs per month that beneficiaries 
purchased before entering the coverage gap, the more they reduced the 
average number of drugs per month that they purchased during the 
coverage gap.  Beneficiaries who purchased an average of 1 to 4.9 drugs 
per month had a 9-percent decrease in the average number of drugs 
purchased per month, while beneficiaries who purchased an average of 
5 to 8.9 drugs had a 10-percent decrease.  Beneficiaries who purchased 
an average of at least nine drugs per month had the largest decrease, at 
18 percent.  See Table 2 for the changes in average monthly drug 
purchasing for all beneficiaries. 
 
Table 2:  Average Number of Drugs Purchased per Beneficiary per Month  
Average Monthly 
Beneficiaries by Average  Number of Drugs  Average Monthly 
Drugs Purchased per  Purchased Before  Number of Drugs 
Month Before Entering  Number of  Entering the  Purchased During 
the Coverage Gap  Beneficiaries  Coverage Gap  the Coverage Gap  Percent Change 
Beneficiaries purchasing 
14.9 drugs  959,075  3.5  3.2   -9% 
Beneficiaries purchasing 
58.9 drugs  527,738  6.2  5.6   -10% 
Beneficiaries purchasing 
9 or more drugs  43,975  10.1  8.3   -18% 
Source:  OIG analysis of 2006 PDE data, 2008. 
 
The greater the average number of drugs per month that beneficiaries 
purchased before entering the coverage gap, the greater their average 
monthly payments both before and during the coverage gap.  However, 
beneficiaries who purchased an average of nine or more drugs per 
month before entering the coverage gap had a smaller percentage 
increase in their average monthly payments when comparing costs 
before and after entering the coverage gap than beneficiaries who 
purchased, on average, fewer drugs per month.  See Table 3 for the 
changes in average monthly payments for all beneficiaries. 
 
30 OIG, Generic Drug Utilization in the Medicare Part D Program, OEI-05-07-00130, 
November 2007. 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  13   
 
F I N D I N G S  
 
Table 3:  Average Payment per Beneficiary per Month  
Beneficiaries by Average  Average Monthly  Average Monthly 
Drugs Purchased per  Payment Before  Payment During 
Month Before Entering  Number of  Entering the  the Coverage 
the Coverage Gap  Beneficiaries  Coverage Gap  Gap  Percent Change 
Beneficiaries purchasing 
14.9 drugs  959,075  $100  $258  158% 
Beneficiaries purchasing 
58.9 drugs  527,738  $120  $319   166% 
Beneficiaries purchasing 
9 or more drugs  43,975  $181  $432   139% 
Source:  OIG analysis of 2006 PDE data, 2008. 
 
Beneficiaries who purchased an average of nine or more drugs per 
month saw a 139-percent increase in average monthly payments 
compared to more than 150 percent for other beneficiaries.  This smaller 
percentage increase is likely explained by the fact that this group of 
beneficiaries most dramatically reduced the average number of drugs 
purchased during the coverage gap, thereby mitigating the full financial 
burden of the coverage gap. 
The smaller percentage increase is not explained by a change in generic 
drug utilization.  In fact, the more drugs beneficiaries purchased on 
average before the coverage gap, the less likely that they were to 
increase their utilization of generic drugs during the coverage gap.  
Beneficiaries purchasing an average of 1 to 4.9 drugs per month 
increased their generic utilization rate from 44 percent before entering 
the coverage gap to 49 percent during the coverage gap.  However, 
beneficiaries who purchased an average of five or more drugs per month 
before entering the coverage gap did not change their generic utilization 
rates.  See Table 4 for rates of generic utilization before and during the 
coverage gap. 
 
 
 
 
 
 
 
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F I N D I N G S  
Table 4:  Rates of Generic Utilization  
Beneficiaries by Average  Generic Utilization  Generic 
Drugs Purchased per  Rate Before  Utilization Rate 
Month Before Entering the  Number of  Entering the  During the 
Coverage Gap  Beneficiaries  Coverage Gap  Coverage Gap  Percent Change 
Beneficiaries purchasing   
14.9 drugs  959,075  44%  49%  11% 
Beneficiaries purchasing   
58.9 drugs  527,738  55%  55%  0% 
Beneficiaries purchasing 9 
or more drugs  43,975  59%  59%  0% 
Source:  OIG analysis of 2006 PDE data, 2008. 
 
For the beneficiaries who purchased an average of five or more drugs 
per month before the coverage gap, increasing generic utilization rates 
may not have been an option.  Their generic utilization rates before they 
entered the coverage gap were already higher than those of other 
beneficiaries.  Further, their generic utilization rate was at or above the 
Part D national generic utilization rate.31 
Although decreasing the average number of drugs that beneficiaries 
purchased during the coverage gap may have helped them reduce their 
financial burden, it may have kept them in the coverage gap longer.  For 
example, beneficiaries who purchased an average of nine or more drugs 
per month before the coverage gap spent an average of 4.5 months in 
the coverage gap, compared to 4 months or less for other beneficiaries.  
See Table 5 for the average amount of time before beneficiaries entered 
the coverage gap and the average amount of time beneficiaries spent in 
the coverage gap. 
 
    Table 5:  Average Time in the Coverage Gap in Months 
Beneficiaries by Average Drugs  Average Amount of  Average Amount 
Purchased per Month Before  Number of  Time To Enter the  of Time in the 
Entering the Coverage Gap  Beneficiaries  Coverage Gap  Coverage Gap 
Beneficiaries purchasing          
14.9 drugs  959,075  7.9  3.0 
Beneficiaries purchasing          
58.9 drugs  527,738  6.8  4.0 
Beneficiaries purchasing 9 or 
more drugs  43,975  4.5  4.5 
Source:  OIG analysis of 2006 PDE data, 2008. 
 
31 OIG, Generic Drug Utilization in the Medicare Part D Program, OEI-05-07-00130, 
November 2007. 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  15   
 
FFFF IIII NNNN DDDD IIII NNNN GGGG SSSS     
 
Beneficiaries who purchased an average of nine or more drugs per 
month were possibly in the coverage gap longer, on average, than other 
beneficiaries.  Because these beneficiaries purchased a greater average 
number of drugs per month, they entered the coverage gap earlier than 
other beneficiaries.  It took this group of beneficiaries approximately            
4.5 months to enter the coverage gap, compared to over 6.5 months for 
other beneficiaries.  Thus, they had a longer time to spend in the 
coverage gap.  Beneficiaries who entered the coverage gap later in the 
coverage year may have had their time in the coverage gap cut short by 
the end of the benefit year.   
Surveyed beneficiaries identified specific types of changes in drug 
purchasing behavior and use 
Changes in drug purchasing.  When we surveyed a sample of 
beneficiaries similar to those included in the analysis above,32              
38 percent of the beneficiaries reported seeking at least one less-costly 
alternative to purchasing drugs, including free medication samples, 
comparison shopping, and switching to mail-order pharmacies.  Table 6 
lists changes that beneficiaries reported making in drug purchasing 
behavior during the coverage gap. 
 
Table 6:  Beneficiaries Reported Changes in Drug Purchasing During 
the Coverage Gap 
Changes in Purchasing Prescription Drugs   Percentage of Beneficiaries* 
Used free medication samples  25% 
Shopped around and compared prices  23% 
Switched to a mail-order pharmacy  11% 
Purchased drugs outside their plan  8% 
*Choices are not mutually exclusive    
Source:  OIG analysis of beneficiary survey responses, 2008. 
 
In addition to seeking less-costly alternatives to purchasing prescription 
drugs, beneficiaries sought help from informal sources to help pay for 
drug purchases.  Fifteen percent of beneficiaries who reported entering 
the coverage gap reported receiving help to pay for their prescription 
 
32 For a discussion of the sampling methodology used to select this sample of 
beneficiaries, please see the methodology, p. 7. 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  16   
 
F I N D I N G S  
drug purchases during the coverage gap; 2 percent reported more than 
one type of help.  Table 7 lists sources that beneficiaries reported 
receiving help from during the coverage gap. 
 
Table 7:  Beneficiaries Reported Sources of Financial Help During the 
Coverage Gap 
Sources of Financial 
Assistance   Percentage of Beneficiaries 
Family member or friend  8% 
SPAP*  4% 
Private pharmaceutical 
company  4% 
Charitable organization  1% 
*We removed all beneficiaries who received financial assistance during the 2006 coverage 
gap based on 2006 PDE data.  This would include assistance from SPAPs.  Beneficiaries may 
be referring to help from SPAPs in the 2007 coverage gap or may be confusing premium 
assistance with help paying for drugs at the point of sale. 
Source:  OIG analysis of beneficiary survey responses, 2008. 
 
Twenty percent of the beneficiaries surveyed may have been eligible 
for but not enrolled in a low-income subsidy that could have assisted 
them with purchasing prescription drugs during the coverage gap.  
These beneficiaries reported annual incomes below 150 percent of the 
FPL and therefore met the income eligibility requirements for a 
low-income subsidy; whether they would have passed the asset test as 
well is unknown. 
Changes in drug use.  Surveyed beneficiaries also identified changes in 
the ways in which they used prescription drugs.  One-third appeared to 
have compromised their drug regimens, indicating that they used 
medications less often, stopped taking medications, or did not start new 
medications.  In addition, 20 percent reported not consulting a medical 
professional before making changes to their drug regimens.  Table 8 
lists changes that beneficiaries reported making in the way they used 
prescription drugs during the coverage gap. 
 
 
 
 
 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  17   
 
F I N D I N G S  
Table 8:  Beneficiaries Reported Changes in Drug Use During the 
Coverage Gap 
Changes in Prescription Drug Use  Percentage of Beneficiaries* 
Used a medication less often than prescribed  21% 
Switched to a different prescription drug  18% 
Stopped taking one or more medications  16% 
Did not start a new medication  14% 
Switched to an over-the-counter drug  4% 
*Choices are not mutually exclusive    
Source:  OIG analysis of beneficiary survey responses, 2008. 
 
 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  18   
 
R E C O M M E N D A T I O N  
 R E C O M M E N D A T I O N S  
Seven percent of beneficiaries entered the coverage gap without 
financial assistance.  Almost all of these beneficiaries made changes in 
their drug purchasing behavior during the coverage gap.  In particular, 
69 percent decreased the number of drugs that they purchased.  In 
addition, the more drugs per month that beneficiaries purchased before 
entering the coverage gap, the more they reduced the number of drugs 
per month that they purchased during the coverage gap.  
When surveyed, beneficiaries identified specific changes in the ways 
they purchased or used drugs during the coverage gap.  Thirty-eight 
percent reported seeking at least one less-costly alternative to 
purchasing drugs, and one-third appeared to have compromised their 
drug regimens, potentially compromising their health.  
Given that some beneficiaries appeared to decrease the number of drugs 
that they purchased during the coverage gap and the potential health 
consequences of those actions, we make the following recommendations 
to CMS:  
CMS Should Support Outreach and Education Activities Targeted at 
Beneficiaries Who Make More Prescription Drug Purchases Before Entering 
the Coverage Gap 
CMS could accomplish this by encouraging plan sponsors to augment 
their current outreach and beneficiary education efforts.  CMS could 
encourage sponsors to use drug utilization data to target beneficiaries 
who purchase more drugs per month during initial coverage for more 
education about efficient and effective drug purchasing options. 
Medication Therapy Management programs (MTMP) could be expanded 
to discuss drug purchasing options and strategies.  
CMS could also supplement plans outreach and education efforts by 
working directly with beneficiaries who historically have purchased 
more drugs per month during initial coverage.  These beneficiaries could 
be targeted using the previous years PDE data.  CMS could start by 
targeting beneficiaries who purchased nine or more drugs per month 
during initial coverage; our analysis shows that they had the most 
dramatic drop in the number of drugs purchased monthly during the 
coverage gap.    
CMS could educate beneficiaries who purchased more drugs during 
initial coverage about cost-saving strategies for purchasing prescription 
drugs.  This could include such strategies as talking to a doctor about 
switching to lower-cost, therapeutically equivalent drugs or comparison 
shopping to get the lowest prices on current drugs.  
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  19   
 
R E C O M M E N D A T I O N S  
In addition, CMS could provide targeted education to these beneficiaries 
about the various tools available for choosing the most cost-effective 
prescription drug plan for the next year.  Given that beneficiaries who 
purchased more drugs during initial coverage had a high rate of generic 
utilization, changing beneficiary purchasing behaviors within the same 
plan, in some cases, may not be enough to reduce the financial burden 
during the coverage gap.   
CMS Should Target Low-Income Subsidy Outreach to Beneficiaries Who 
Entered the Coverage Gap Without Financial Assistance  
Targeting the population of beneficiaries who entered the coverage gap 
without financial assistance in previous years might be one way to 
identify eligible beneficiaries for enrollment in the low-income subsidy 
program; 20 percent of the beneficiaries surveyed may have been 
eligible.  As a 2006 OIG report demonstrates, there is no effective way to 
identify the pool of beneficiaries who may be eligible for the subsidy.33  
That report concluded that legislation is needed to allow CMS and the 
Social Security Administration to more effectively identify beneficiaries 
who are potentially eligible for the subsidy.  We continue to support this 
conclusion. 
In addition, CMS should continue targeting beneficiaries to promote the 
low-income subsidy and assist eligible beneficiaries.  Beneficiaries who 
enter the coverage gap without financial assistance for prescription 
drug costs might benefit from more education about the low-income 
subsidy that can assist them throughout the rest of the benefit year. 
AGENCY COMMENTS AND OFFICE OF INSPECTOR GENERAL 
RESPONSE 
CMS generally agreed with our findings and stated that it appreciated 
the additional information provided through the beneficiary survey.  
CMS noted that our findings were similar to the results of CMSs 
analysis presented at the Medicare Drug Benefit Symposium, held in        
October 2008.  For example, we found that 7 percent of beneficiaries 
entered the coverage gap and did not receive financial assistance with 
their prescription drug costs.  CMS found that almost 10 percent of 
beneficiaries who did not have a low-income subsidy and were not in a 
plan with gap coverage reached their plans specific initial coverage 
 
33 OIG, Identifying Individuals Eligible for the Medicare Part D Low-Income Subsidy,     
OEI-03-06-00120, November 2006. 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  20   
 
R E C O M M E N D A T I O N S  
limit.  The difference in results can be explained by different analytic 
approaches, as CMS correctly noted.   
Although CMS generally agreed with our findings, it indicated a 
concern about the lack of a control group with which to compare our 
results.  As a result, CMS pointed out that this evaluation does not 
provide a true causal analysis.  This is accurate, as the report does not 
present a true causal analysis.  Rather, it presents data about drug 
purchases with a number of plausible explanations of those data, 
including the possibility that the decrease in drug purchases was the 
result of the coverage gap.  This explanation is consistent with research 
described in the body of the report suggesting that beneficiaries 
decrease prescription drug use when they encounter a gap in coverage.   
In addition, CMS questioned whether the decrease in drug purchases 
could be attributed to the coverage gap.  CMS stated that it had 
conducted a similar analysis using beneficiaries who received a 
low-income subsidy as a comparison group.  CMS found that the 
comparison group decreased the number of drugs purchased per month 
despite the fact that they did not face a coverage gap.  However, it is 
unclear whether the extent of the decrease was as sharp for this group 
as it was for beneficiaries without financial assistance during the 
coverage gap.     
In response to our recommendation that CMS support outreach and 
education activities targeted at beneficiaries who make more 
prescription drug purchases before entering the coverage gap, CMS 
stated that it believed its current outreach to all beneficiaries is 
sufficient.  CMS stated that the annual open-enrollment campaign 
encourages all beneficiaries to make informed decisions based on cost.  
In addition, CMS indicated that the Medicare Prescription Drug Plan 
Finder tool selects generic alternatives as the default and can substitute 
lower-cost therapeutic alternatives.  Thus, beneficiaries can use this tool 
to explore cost-saving options.  Lastly, CMS highlighted the additional 
outreach done through Part D sponsors and their MTMPs.  
However, we found that beneficiaries who made more prescription drug 
purchases before entering the coverage gap had the largest drop in the 
number of drugs purchased during the coverage gap.  Because these 
beneficiaries take more prescription drugs, they are likely in poorer 
health and are the most vulnerable to negative health consequences 
from nonadherence to drug regimens.  Therefore, additional outreach 
and education about efficient and effective drug purchasing options 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  21   
 
R E C O M M E N D A T I O N S  
targeted at this group of beneficiaries could have far-reaching health 
benefits.  Current CMS outreach and plan sponsor MTMPs do not target 
this group, nor are MTMPs required to assist with financial decisions or 
provide cost-saving strategies. 
CMS concurred with our second recommendation that CMS target 
low-income subsidy outreach to beneficiaries who entered the coverage 
gap without financial assistance.  CMS indicated that it would continue 
to emphasize the financial value of the low-income subsidy to attract 
beneficiaries with significant drug utilization who might benefit from 
the subsidy.  However, this action does not address our 
recommendation, which is to use drug utilization data to identify 
potential beneficiaries for the subsidy.  Given the recognized difficulty 
in identifying beneficiaries who may be eligible for the subsidy, we 
offered this as an additional approach. 
CMS also offered a few technical comments.  They offered the same 
comments when asked to informally comment on the draft report.  We 
did not alter our draft report in response to these comments because 
they primarily pointed out how our analysis is different from other 
approaches.  Given that we clearly stated our approach, this did not 
seem necessary.  For this final version of the report, we have sought to 
make these differences explicit.  For the full text of CMSs comments, 
see Appendix E.  
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  22   
 
 A P P E N D I X   ~   A  
 
Detailed Methodology 
This study explores the effect of the coverage gap on beneficiaries drug 
purchasing behavior by focusing on those beneficiaries without 
assistance during the coverage gap in 2006.  We examined changes in 
drug purchasing behavior and costs for these beneficiaries as they 
moved from initial coverage into the coverage gap.   
Data Sources 
We used 2006 Prescription Drug Event (PDE) data to conduct this 
study.  The Centers for Medicare & Medicaid Services (CMS) requires 
plans providing prescription drug coverage to submit PDE data for 
payment purposes.  Each drug event included in the PDE data 
represents the dispensing of a drug or medical supply for the injection of 
insulin.  These data contain the beneficiarys identification number; the 
Food and Drug Administrations National Drug Code (NDC) ;34 the date 
of service; the number of days for which the drug is supplied; and 
payments at point of sale made by plan sponsors, beneficiaries (or on 
behalf of beneficiaries), and other approved third-party payers.  Our 
analysis included final action PDE claims submitted by all plans for 
2006 as of July 2007.35 
We used two drug data compendia to supplement the PDE data:          
(1) August 2007 First DataBank drug product information data and    
(2) first quarter 2007 Redbook drug product data.  The 2007 First 
DataBank and Redbook data contained information on all drugs covered 
by Part D in 2006 but with more up-to-date drug information than 
earlier versions of First DataBank and Redbook.  First DataBank is a 
database containing drug product information, such as drug name and 
therapeutic class, for each NDC.  Redbook is a database that provides 
pricing and descriptive information for prescription and                    
over-the-counter drugs.   
 
34 An NDC is a three-part universal identifier that specifies the manufacturer, product, 
and package size. 
35 Final action claims are those that CMS uses to reconcile payments to plans.  A PDE 
record is submitted each time a beneficiary fills a prescription covered under Part D.  The 
PDE records may be amended or deleted up to 6 months after the end of the payment year.  
After that point, CMS considers them to be final action claims. 
  OEI-05-07-00610  EFFECTS OF MEDICARE PART D COVERAGE GAP ON BENEFICIARIES WITHOUT FINANCIAL ASSISTANCE  23   
 
AAA PPP PPP EEE NNN DDD III XXX     ~~~     AAA    
In addition, we conducted a national survey of a random sample of 
beneficiaries.  We used the Medicare enrollment database to obtain 
addresses for our sample and public directories to find phone numbers.   
To ensure the construct validity of our cover letter and survey 
instrument, we conducted two focus group meetings at senior centers.  
We asked beneficiaries to read the cover letter and complete the survey.  
After they completed the survey, we conducted brief cognitive 
interviews to determine whether the cover letter and survey were clear 
and understandable.  Most beneficiaries interpreted the survey 
questions as we intended.  Where necessary, we altered the survey 
based on the feedback we received from the focus groups to make it 
more understandable.  
We conducted the survey primarily by mail.  For beneficiaries with valid 
phone numbers, we made three attempts by mail and two attempts by 
phone to obtain their responses.  For beneficiaries without valid phone 
numbers, we made five mail attempts.   
We allowed proxy respondents.  We asked that the person who made 
health care decisions on behalf of the beneficiary complete the survey. 
Approximately 23 percent of the surveys were completed by someone 
other than the beneficiary.   
Data Analysis 
Determining the number of beneficiaries in the coverage gap.  The 
complete final action 2006 PDE data contained nearly 817 million 
claims for over 22 million beneficiaries.  To obtain our population of 
beneficiaries who had gross covered drug costs exceeding the initial 
coverage limit and did not have financial assistance, we completed a 
series of steps. 
First, we removed some claims: 
1.  We excluded all claims for noncovered Part D drugs because these 
claims do not count toward true out-of-pocket expenses.  This 
removed 5,889,021 claims from the PDE data, representing less 
than 1 percent of the total claims. 
2.  We removed claims without corresponding drug-identifying 
information.  We merged beneficiary claims with First DataBank 
and Redbook data.  This removed 166,405 claims because the 
drugs were not listed in at least one of those data sources.    
 
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Then, we determined our population: 
1.   We removed all beneficiaries who did not have gross covered      
drug costs greater than the initial coverage limit of $2,250.  To do 
this, we calculated cumulative and total spending for each 
beneficiary using these PDE data fields:  ingredient cost, 
dispensing fee, and sales tax.  This removed                     
14,783,703 beneficiaries, representing 66.7 percent of all 
beneficiaries. 
2.   We then removed all beneficiaries who received assistance from a 
low-income subsidy.  To complete this step, we used the PDE data 
field that records the amount of a beneficiarys low-income 
subsidy, if any.  If this field was greater than zero, we removed the 
beneficiary.  This removed 4,257,527 beneficiaries, representing 
19.2 percent of all beneficiaries. 
3.  Finally, we removed all beneficiaries who did not pay 100 percent 
of the drugs ingredient cost, dispensing fee, and sales tax for all 
claims during the coverage gap.  To do this, we separated the 
claims into three phases:  (1) before the coverage gap, which 
included both the deductible and initial coverage; (2) during the 
coverage gap; and (3) catastrophic coverage (after the coverage 
gap).  We then determined which beneficiaries had claims during 
the coverage gap for which they did not pay 100 percent of the 
drug cost.  This removed 1,411,446 beneficiaries, representing 
6.4 percent of all beneficiaries.   
We assumed the standard 2006 initial coverage limit of $2,250 as the 
threshold for entry into the coverage gap.  While we did not use the 
initial coverage limit specific to each beneficiarys plan, we did exclude 
all forms of assistance in the coverage gap, which includes additional 
assistance from plans with extended initial coverage limits. 
Finally, we removed additional beneficiaries because of data anomalies 
that made their claims history implausible: 
1.  We removed any beneficiary whose entry into catastrophic 
coverage preceded his or her entry into the coverage gap.  To do 
this, we calculated the date when each beneficiary entered the 
coverage gap and catastrophic coverage.  An additional          
16,808 beneficiaries were removed in this step, representing less 
than 1 percent of all beneficiaries. 
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A P P E N D I X   ~   A  
2.  We removed any beneficiary who had a claim before the coverage 
gap but not during it or who had a claim during the coverage gap 
but not before.  This removed an additional 166,017 beneficiaries, 
representing less than 1 percent of all beneficiaries. 
As a result, our population consisted of 1,530,788 beneficiaries with 
81,922,129 claims.  We assigned beneficiaries to one of three groups, 
based on the average number of drugs purchased per month during 
initial coverage:  1 to 4.9 drugs, 5 to 8.9, and 9 or more.  This allowed 
us to analyze changes in drug purchasing and payment across groups, 
based on the average number of drugs purchased.   
Analyzing changes in beneficiary drug purchases.  To measure drug 
purchasing in each coverage phase, we calculated three measures:        
(1) average number of different drugs per month, (2) percentage of 
drugs purchased to treat chronic and acute conditions, and (3) generic 
drug utilization rate. 
We based our count of drugs per beneficiary on the Ingredient List 
Identifier for each drug.  This represents a unique combination of active 
ingredients, regardless of manufacturer, package size, dosage form, 
route of administration, or strength.  As such, it incorporates multiple 
NDCs. 
Where we refer to months in our calculations, we calculated months 
based on the whether or not a beneficiary filled a prescription.  If a 
beneficiary had a claim during a given month, we counted that calendar 
month towards his or her total months.   
To identify the percentage of chronic and acute drugs purchased per 
phase, we used a data field from the Redbook that indicated, at the NDC 
level, whether a drug was considered to be a maintenance drug.  
Maintenance drugs are used to treat chronic conditions.  In each 
coverage phase, we counted the total number of maintenance and 
nonmaintenance drugs prescribed and divided that by the total number 
of drugs purchased.     
To identify the generic drug utilization rate per phase, we used a data 
field from First DataBank that indicates, at the NDC level, whether a 
drug is a brand-name or generic drug.  We then identified the number of 
prescriptions labeled as generic for each beneficiary.   
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Nonresponse analysis 
We analyzed how nonresponse to our survey may have affected our 
survey estimates.  We examined potential nonresponse bias effects on 
24 key survey questions.  Our nonresponse analysis provided no 
evidence that our survey results were biased because of nonresponse.   
Our basic approach was to impute answers for nonrespondents and 
determine whether the survey estimate calculated with the imputed 
values differed significantly from the survey estimate based solely on 
the respondents answers.  If no statistical difference was found between 
the two estimates, we considered our survey estimates to be unaffected 
by potential nonresponse bias. 
Variables for both respondent and nonrespondent beneficiaries were 
age, sex, race, drug benefit type, and plan type.  We determined 
whether respondents and nonrespondents differed based on these 
variables.  They did not differ based on sex, race, and drug benefit type.  
However, they differed based on plan type and age.   
Because nonrespondents were different by plan type and age, we 
imputed nonrespondents answers based on the response frequencies of 
late responders who shared the same plan type and age characteristics.  
To do this, we classified response time as either early or late 
depending on how many attempts it took to obtain a response.  Late 
responders were those who responded to the survey after our third 
contact attempt.  Finally, we conducted statistical tests of significance 
to determine whether the estimates based on both respondents answers 
and nonrespondents imputed values differed from the estimates based 
only on respondents answers.   
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Estimates and Confidence Intervals 
Table D-1:  Estimates of Survey Results:  Coping Strategies Related to Prescription Drug Purchasing and 
Use During the Coverage Gap by Beneficiaries Who Reported Entering the Coverage Gap 
Sample  95-Percent 
Estimate Description  Size Point Estimate  Confidence Interval
Percentage of beneficiaries who reported entering the coverage gap 
after enrolling in a Part D plan  142 80.3%  73.7%86.9%
Percentage of beneficiaries who reported seeking less costly 
alternatives to purchasing drugs (i.e., used a medication less often, 
stopped taking a medication, or did not start a new medication)  114 37.7%  28.7%46.8%
Percentage of beneficiaries who reported using free prescription 
drug samples   114 25.4%  17.3%33.6%
Percentage of beneficiaries who reported shopping around and 
comparing prices   114 22.8%  15.0%30.6%
Percentage of beneficiaries who reported switching to a mail-order 
pharmacy   114 11.4%  5.5%17.3%
Percentage of beneficiaries who reported purchasing drugs outside 
their plan   114 7.9%  2.9%12.9%
Percentage of beneficiaries who reported receiving at least one type 
of help in purchasing their prescription drugs   114 14.9%  8.3%21.6%
Percentage of beneficiaries who reported receiving more than one 
source of help in purchasing their prescription drugs   114 1.8%  0.2%6.2%*
Percentage of beneficiaries who reported receiving help from a 
family member or friend   114 7.9%  2.9%12.9%
Percentage of beneficiaries who reported receiving help from a 
State Pharmacy Assistance Program   114 4.4%  0.6%8.2%
Percentage of beneficiaries who reported receiving help from a 
private pharmaceutical company   114 3.5%  0.1%6.9%
Percentage of beneficiaries who reported receiving help from a 
charitable organization   114 0.9%  0.02%4.8%*
Percentage of beneficiaries who reported compromising their drug 
regimens (i.e., used a medication less often, stopped taking a 
medication, or did not start a new medication)  114 33.3%  24.5%42.1%
Percentage of beneficiaries who reported using a drug less often 
than prescribed   114 21.1%  13.5%28.7%
Percentage of beneficiaries who reported that they stopped taking a 
medication   114 15.8%  9.0%22.6%
Percentage of beneficiaries who reported not starting a new 
medication  114 14.0%  7.6%20.5%
* Confidence interval calculated with an exact method based on the binomial distribution. 
Source:  Office of Inspector General (OIG) analysis of beneficiary survey responses, 2008. 
 
 
 
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Table D-1:  Estimates of Survey Results:  Coping Strategies Related to Prescription Drug Purchasing and 
Use During the Coverage Gap by Beneficiaries Who Reported Entering the Coverage Gap, continued  
Sample  95-Percent 
Estimate Description  Size Point Estimate  Confidence Interval
Percentage of beneficiaries who reported not talking to a doctor, 
nurse, or pharmacist before changing their drug use  110 20.0%  12.4%27.6%
Percentage of beneficiaries who reported switching to a different 
prescription drug   114 18.4%  11.2%25.6%
Percentage of beneficiaries who reported switching to an over-the-
counter drug   114 4.4%  0.6%8.2%
Source:  OIG analysis of beneficiary survey responses, 2008. 
 
 
Table D-2:  Estimates of Survey Results:  Beneficiaries Reported Annual Incomes   
Sample  Point  95-Percent 
Estimate Description  Size Estimate  Confidence Interval
Percentage of all beneficiaries who reported that their annual 
household income was below 150% of the Federal poverty level  176 19.9%  13.9%25.8%
Source:  OIG analysis of beneficiary survey responses, 2008. 
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Agency Comments 
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This report was prepared under the direction of Ann Maxwell, Regional 
Inspector General for Evaluation and Inspections in the Chicago 
regional office, and Thomas Komaniecki, Deputy Regional Inspector 
General. 
Nicole Hrycyk served as the team leader for this study.  Other principal 
Office of Evaluation and Inspections staff from the Chicago regional 
office who contributed to the report include Meghan Kearns, Elizabeth 
Kopko, Tamara Perry, Margarita Rodriguez, and Mara Werner; other 
central office staff who contributed include Kevin Farber, Doris 
Jackson, Kevin Manley, and Matthew McMullen. 
 
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