Potential Savings from Greater
Use of $4 Generic Drugs
Presenter: Yuting Zhang
Assistant Professor
University of Pittsburgh
Coauthors: Lei Zhou a, Walid Gellad
a
a, b
University of Pittsburgh; b VA Pittsburgh and RAND
Background
 Suboptimal
use of more cost-effective
generics
 Availability of the $4 generic programs
 No data on how $4 programs are used
and potential savings from broader use of
them
Objectives
How were prescriptions filled for the drugs
commonly available at a $4 program?
 What factors affect the likelihood of use of a $4
program?
 What are potential savings from the broad use of
$4 programs?

Data Sources
2007 Medical Expenditure Panel Survey
 List of $4 drugs available at major national
pharmacy chains


Wal-Mart, Sam’s Club, Target
Study Population
30,964 (US 301,309,149)
 13,908 (50%) adults (age ≥18) used ≥1 Rx
 7,769 (51%) used ≥1 drugs that are commonly
available at a $4 program (80,561 prescriptions
by generic name, dosage form, and strength)

How were Prescriptions Filled?
No. of
Prescriptions
No. of No. of Weighted US
Adults*
Population
Total Prescriptions
80,561
7,769
81,503,409
Generic drugs
67,045
6,974
72,505,952
Current using $4
1,898
491
4,936,383
Not using
$4, could save
27,682
4,365
47,115,346
13,516
2,195
24,144,384
7,119
1,333
14,973,791
Brand-name drugs
Not using
$4, could save
Current
users
Potential
savers
Potential
savers
Note: * Numbers don’t sum up because individuals could overlap across groups
Objectives
How were prescriptions filled for the drugs
commonly available at a $4 program?
 What factors affect the likelihood of use of a $4
program?
 What are potential savings from the broad use of
$4 programs?

Characteristics of Study Population
CurrentUsers
(N=491)
PotentialSavers
(N=4,795)
P-value
62.8
58.3
.36
40-64 yr
46
50.5
.034
≥65 yr
39
32.2
.018
Black
10.1
9.7
0.80
Hispanic
9.1
8.5
0.27
College
38.4
40
0.33
Post College
11
0.08
Poor (<100%)
7.8
10.9
8.6
.097
Near poor (100%-125%)
5.2
4.4
.018
Low income (125%-200%)
17.5
12.4
.054
High income (≥400%)
35.6
43.6
<0.0001
Variable
Female, %
Age, %
Race,%
Education,%
Income, %
Characteristics of Study Population (cont.)
CurrentUsers
PotentialSavers
P-value
Any private
62.4
74.1
<0.0001
Public only
24.7
18.6
0.001
Uninsured
13
7.3
0.0001
Northeast
12.3
18
0.006
South
44.1
37.8
0.001
West
17.7
21
0.024
=0
20.2
44.3
17.4
50.5
0.030
.059
≥3
10.5
5.8
<0.0001
Fair and poor
26.7
22.8
0.047
Excellent
10.6
14.5
0.048
Very Good
25.6
30
0.018
Variable
Insurance, %
Region, %
Rural, %
Chronics, %
Health Status,
%
Determinants of Using $4 Programs:
Multivariate Logistic Regression
Variables
Odds Ratios
95% CI
Uninsured vs. Private
1.85
1.36-2.50
Public vs. Private
1.32
1.02-1.71
Chronic
≥3
1.75
1.21-2.53
Region
Northeast vs. South
0.6
0.43-0.83
West vs. South
0.7
0.54-0.92
Insurance
Other variables in the multivariate logistic regression include age,
gender, race, education, income, insurance, region, rural vs
metropolitan, and health status.
Objectives
How were prescriptions filled for the drugs
commonly available at a $4 program?
 What factors affect the likelihood of use of a $4
program?
 What are potential savings from the broad use of
$4 programs?

Potential Overall Savings in 2007
No. of
Prescriptions
No. of
Adults*
Savings from
Switching to
Regular
Generics
Brand-name
7,119
1,333
$233,977
$362,353
Regular
generics
27,682
4,365
0
$346,556
$4 generics
1,898
491
0
0
5,286
233,977
708,909
Total
Savings from
Switching to
$4 Generics
Note: * Numbers don’t sum up because individuals could overlap across groups
Potential Annual Savings Per Person
Total Savings
Patient
Savings
Brand-name to $4
generics
$259
($237-$282)
$130
($118-$142)
Regular generic to
$4 generics
$80
($74-$86)
$43
($39-$46)
$138
($129-$147)
$72
($66-$77)
Total saving by
switching to $4
generics
This translates to…

$7.6 billion in total annual savings in the US in 2007
 $4.2 billion by patients
 $2.2 billion by private insurance
 $1.4 billion by Medicare

Limitations
Summary
6% adults used a $4 program to obtain these
drugs in 2007
 Users of $4 programs are more likely to have
no insurance, have ≥3 chronic conditions, and
live in the south
 7.2 billion could be saved with broad use of $4
programs in 2007

Acknowledgements

The RAND University of Pittsburgh Health
Institute (RUPHI) and the Clinical and
Translational Science Institute (CTSI):
Translating Research into Practice (TRIP)
program