Discounted generic medication programs ($4 per 30-day-supply or $10 per 90-day-supply) are available at pharmacies of many retail stores, such as Wal-Mart and Target.1, 2 While most prescription drug coverage requires patients to pay $10–$11 per 30-day supply for generics and $25–$27 for preferred branded drugs between 2006 and 2009,3 anyone regardless of insurance pays only $4 for qualifying generics through these programs. Use of $4 programs could potentially save patients and society billions of dollars. Our study is the first to evaluate who may be using $4 programs and potential national savings from broad use of these programs.
Methods
We examined a nationally-representative sample of 30,964 individuals in the 2007 Medical Expenditure Panel Survey (MEPS).4 Our study population consists of individuals older than 18 years of age who used any generic medications, or their brand-name counterparts, available in $4 programs any time in 2007. We limited our analysis to pills, tablets, or capsules. To identify prescriptions for these medications filled through $4 programs in MEPS, we used the following criteria: 1) the drug is available through a $4 program at $4 for a 30-day quantity; 2) patients paid $4 out-of-pocket for the same 30-day quantity; and 3) no other payers contributed to the payment (i.e., patients bear the total medication cost). We defined those who did not use $4 programs and could save if they filled their drugs (both generic or brand) at $4 programs as “potential users” and calculated potential savings as the difference between MEPS actual prescription payments and potential costs if one were to buy the drugs from $4 programs. Because not every potential user would switch to a $4 program, we conducted sensitivity analyses. We ranked the potential out-of-pocket savings among potential users from highest to lowest, and then calculated potential savings assuming only the top 80, 50, and 30 percent of potential users would switch.
Results
Among 30,964 individuals sampled in the 2007 MEPS, 13,908 adults filled at least one prescription in 2007, accounting for 50% of the US population. Approximately 55% of the 13,908 (or 7,690) used any drug (either generic or brand-name) whose generic formulation is commonly available in the $4 programs, corresponding to 80,567,861 US adults. Among these 7,690 adults, only 5.9% (450) used a $4 program in 2007; and 60.2% (4,628) could potentially have filled their prescription in a $4 program. This corresponds to 4,429,793 current-users and 50,188,290 potential-users among US adults.
The Table presents the potential savings from switching from brand-name and regular generics to $4 generics using 2007 MEPS data. The average total savings per person over one year for both generic and brand-name drugs would be $115 (95% CI 107–124) and the average out-of-pocket savings per person would be $64 (95% CI 59–69). The total societal savings based on the weighted US population would be $5.78 billion, of which $3.23 billion is attributed to patient out-of-pocket savings and $1.07 billion to Medicare.
Table.
No. of Adults |
No. of Weighted Users |
Total Savings Per Person* |
Total Societal Savings† |
Out-of-pocket Savings Per Person* |
Total Savings to Patients† |
Total Savings to Medicare† |
||||
---|---|---|---|---|---|---|---|---|---|---|
2007 $ |
95% CI | 2007 $ | 2007 $ | 95% CI | 2007 $ | 2007 $ | ||||
All switched | Branded | 1,047 | 11,701,128 | 216 | (194–238) | 2,529,052,573 | 125 | (113–138) | 1,467,669,167 | 442,970,165 |
Generics | 4,042 | 43,676,443 | 74 | (69–80) | 3,252,518,957 | 40 | (37–44) | 1,761,463,956 | 626,582,594 | |
Total | 4,628 | 50,188,290 | 115 | (107–124) | 5,781,571,531 | 64 | (59–69) | 3,229,133,122 | 1,069,552,759 | |
Top 80% switched | Branded | 958 | 10,728,057 | 231 | (208–254) | 2,477,381,456 | 137 | (123–150) | 1,465,834,780 | 435,423,813 |
Generics | 3,199 | 34,323,534 | 92 | (85–99) | 3,163,901,619 | 51 | (47–55) | 1,738,475,939 | 605,471,857 | |
Total | 3,702 | 39,921,744 | 141 | (131–151) | 5,641,283,075 | 80 | (74–86) | 3,204,310,718 | 1,040,895,670 | |
Top 50% switched | Branded | 811 | 9,001,487 | 262 | (236–287) | 2,354,752,998 | 161 | (145–176) | 1,445,988,387 | 415,959,412 |
Generics | 1,914 | 20,457,160 | 131 | (120–142) | 2,676,650,960 | 77 | (71–84) | 1,579,556,244 | 485,712,268 | |
Total | 2,314 | 24,889,392 | 202 | (187–217) | 5,031,403,958 | 122 | (112–131) | 3,025,544,631 | 901,671,680 | |
Top 30% switched | Branded | 607 | 6,747,286 | 324 | (294–353) | 2,183,990,629 | 204 | (185–223) | 1,378,153,731 | 363,155,303 |
Generics | 1,103 | 11,508,520 | 176 | (161–191) | 2,028,496,166 | 112 | (106–118) | 1,290,853,911 | 339,736,655 | |
Total | 1,388 | 14,717,599 | 286 | (266–307) | 4,212,486,795 | 181 | (170–193) | 2,669,007,642 | 702,891,958 |
These numbers are weighted numbers that reflect the survey design, sampling frame, and adjustments for household non-response and planned over-sampling. The weighted results therefore represent estimates for the non-institutionalized US population.
These numbers are savings per person multiplied by the number of weighted users.
If we assumed only the top 80 percent of potential users would switch, the potential total societal savings would be $5.64 billion, with $3.20 billion savings to patients and $1.04 billion to Medicare. The average total saving per person would be $141 (95% CI 131–151) and the average out-of-pocket savings per person would be $80 (95% CI 74–86). If only the top 30 percent of potential users would switch, the total societal savings would be $4.21 billion (see Table). Examining the distribution of savings shows that 50 percent of potential users would save less than $22 a year out-of-pocket, and only 5 percent of all potential users could save more than $269 and approximately 1 percent could save more than $718 annually out-of-pocket.
Comment
We found that among patients taking drugs available in $4 programs and their brand-name counterparts, only 5.9% actually paid $4 in 2007. The societal savings would be $5.8 billion in 2007 if all potential users switched to $4 program; however, only 50% of potential users would save more than $22 a year out-of-pocket.
While the policy change to encourage these cost savings is not obvious, the ramifications of such a change are important to consider. A potential savings of $6 billion represents approximately 2.5% of total health expenditures on prescription drugs in 2007, which is not inconsequential.11 Additionally, our savings calculations only assume direct substitution and do not incorporate the possibility of therapeutic substitution, and our analysis excludes children. It remains to be seen what the uptake of these programs has been since 2007.
We are not attempting to promote Wal-Mart or any other specific pharmacy as the place for patients to fill their prescriptions. It appears, however, that the majority of savings comes from a small proportion of individuals, and if policy makers and clinicians can direct these individuals to low-cost generic programs, patients, payers, and taxpayers could save enormously.
Acknowledgements
This project was supported in part by the RAND-University of Pittsburgh Health Institute (RUPHI), a formal collaboration between the RAND Corporation, RAND Health, and the University of Pittsburgh School of the Health Sciences. For more information about RUPHI, please visit our website at: http://www.ruphi.pitt.edu.
This publication was made possible by Grant Number UL1 RR024153 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the http://www.ncrr.nih.gov/. Information on Re-engineering the Clinical Research Enterprise can be obtained from http://nihroadmpa.nih.gov/clinicalresearch/overview-translational.asp.
Primary funding source: The RAND University of Pittsburgh Health Institute (RUPHI) and the Clinical and Translational Science Institute (CTSI): Translating Research into Practice (TRIP) Program
Footnotes
Presentation: Dr. Zhang gave a podium presentation of this paper at the AcademyHealth annual meeting in Boston on June 27 2010.
Disclosure of potential conflicts of interests: none
Author contributions:
Conception and design: Y. Zhang, W. Gellad
Analysis and interpretation of the data: Y. Zhang, W. Gellad, L. Zhou
Drafting of the article: Y. Zhang, W. Gellad
Critical revision of the article for important intellectual content: Y. Zhang, W. Gellad
Final approval of the article: Y. Zhang, W. Gellad, L. Zhou
Statistical expertise: Y. Zhang, L. Zhou
Obtaining of funding: Y. Zhang, W. Gellad
Administrative, technical or logistic support: Y. Zhang, W. Gellad, L. Zhou
Collection and assembly of data: Y. Zhang, L. Zhou
References
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