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Original Research |

Effect of the Medicare Part D Coverage Gap on Medication Use Among Patients With Hypertension and Hyperlipidemia

Pengxiang Li, PhD; Sean McElligott, MS; Henry Bergquist, BS; J. Sanford Schwartz, MD; and Jalpa A. Doshi, PhD
[+] Article and Author Information

From the University of Pennsylvania, Philadelphia, Pennsylvania.

Disclaimer: Drs. Li and Doshi had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Grant Support: By investigator-initiated grants from the Penn–Pfizer Alliance and the American Heart Association.

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M11-2255.

Reproducible Research Statement:Statistical code: Available from Dr. Li (e-mail, penli@mail.med.upenn.edu). Study protocol and data set: Not available.

Requests for Single Reprints: Jalpa A. Doshi, PhD, Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Blockley Hall, Room 1222, Philadelphia, PA 19104-6021; e-mail, jdoshi@mail.med.upenn.edu.

Current Author Addresses: Dr. Li: Blockley Hall, Room 1215, Philadelphia, PA 19104-6021.

Mr. McElligott: Blockley Hall, Room 1208, Philadelphia, PA 19104-6021.

Mr. Bergquist: 3641 Locust Walk, Philadelphia, PA 19014-6218.

Dr. Schwartz: Blockley Hall #1101, 423 Guardian Drive, Philadelphia, PA 19104-6021.

Dr. Doshi: Blockley Hall, Room 1222, Philadelphia, PA 19104-6021.

Author Contributions: Conception and Design: P. Li, S. McElligott, J.S. Schwartz, J.A. Doshi.

Analysis and interpretation of the data: P. Li, S. McElligott, H. Bergquist, J.S. Schwartz, J.A. Doshi.

Drafting of the article: P. Li, S. McElligott, H. Bergquist, J.S. Schwartz, J.A. Doshi.

Critical revision of the article for important intellectual content: P. Li, S. McElligott, J.S. Schwartz, J.A. Doshi.

Final approval of the article: P. Li, S. McElligott, J.S. Schwartz, J.A. Doshi.

Provision of study materials or patients: J.A. Doshi.

Statistical expertise: P. Li, S. McElligott, J.S. Schwartz, J.A. Doshi.

Obtaining of funding: J.S. Schwartz, J.A. Doshi.

Administrative, technical, or logistic support: P. Li, S. McElligott, H. Bergquist, J.A. Doshi.

Collection and assembly of data: P. Li, S. McElligott, J.A. Doshi.


Ann Intern Med. 2012;156(11):776-784. doi:10.7326/0003-4819-156-11-201206050-00004
Text Size: A A A

Background: Prior studies of the Medicare Part D coverage gap are limited in generalizability and scope.

Objective: To determine the effect of the coverage gap on drugs used for asymptomatic (antihypertensive and lipid-lowering drugs) and symptomatic (pain relievers, acid suppressants, and antidepressants) conditions in elderly patients with hypertension and hyperlipidemia.

Design: Quasi-experimental study using pre–post design and contemporaneous control group.

Setting: Medicare claims files from 2005 and 2006 for 5% random sample of Medicare beneficiaries.

Patients: Part D plan enrollees with hypertension or hyperlipidemia aged 65 years or older who had no coverage, generic-only coverage, or both brand-name and generic coverage during the gap in 2006. Patients who were fully eligible for the low-income subsidy served as the control group.

Measurements: Monthly 30-day supply prescriptions available, medication adherence, and continuous medication gaps of 30 days or more for antihypertensive or lipid-lowering drugs; monthly 30-day supply prescriptions available for pain relievers, acid suppressants, or antidepressants before and after coverage gap entry.

Results: Patients with no gap coverage had a decrease in monthly antihypertensive and lipid-lowering drug prescriptions during the coverage gap. Nonadherence also increased in this group (antihypertensives: odds ratio [OR], 1.60 [95% CI, 1.50 to 1.71]; lipid-lowering drugs: OR, 1.59 [CI, 1.50 to 1.68]). The proportion of patients with no gap coverage who had continuous medication gaps in lipid-lowering medication use and antihypertensive use increased by an absolute 7.3% (OR, 1.38 [CI, 1.29 to 1.46]) and 3.2% (OR, 1.35 [CI, 1.25 to 1.45]), respectively, because of the coverage gap. Decreases in use were smaller for pain relievers and antidepressants and larger for acid suppressants in patients with no gap coverage. Patients with generic-only coverage had decreased use of cardiovascular medications but no change in use of drugs for symptomatic conditions. No measures changed in the brand-name and generic coverage groups. Results of sensitivity analyses were consistent with the main findings.

Limitation: Because this study was nonrandomized, unobserved differences may still exist between study groups.

Conclusion: The Part D coverage gap was associated with decreased use of medications for hypertension and hyperlipidemia in patients with no gap coverage and generic-only gap coverage. The proposed phasing out of the gap by 2020 will benefit such patients; however, use of low-value medications may also increase.

Primary Funding Source: Penn–Pfizer Alliance and American Heart Association.

Figures

Grahic Jump Location
Appendix Figure 1.

Study flow diagram.

LIS = low-income subsidy.

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Grahic Jump Location
Appendix Figure 2.

Average out-of-pocket cost per 30-day supply prescription filled for all antihypertensive and lipid-lowering drugs before and during the coverage gap.

Error bars indicate 95% CIs. LIS = low-income subsidy.

Grahic Jump Location
Grahic Jump Location
Figure 1.

Adjusted changes in number of 30-day supply antihypertensive and lipid-lowering prescriptions available by beneficiaries in months before and during the coverage gap, compared with the control group of low-income subsidy patients.

Month 0 represents the calendar month of entry into the coverage gap. The figures are based on mean differences in adjusted 30-day supply prescriptions available per month for each study group relative to the control group of fully eligible low-income subsidy patients. The adjusted 30-day supply prescriptions used per month were estimated with segmented regression models using generalized estimating equations with first-order, autoregressive correlation structure; variables for study groups, coverage gap status, months, and months after entering coverage gap; and interaction terms between group indicators and time-related variables. Data were adjusted for age, sex, race and ethnicity, Medicare entitlement status, metropolitan status (urban or rural), census region of residence, area-level characteristics (per capita income, unemployment rate, and education level) in beneficiary's county of residence, and prescription drug hierarchical condition category risk score. Error bars indicate 95% CIs obtained with 500 bootstrapped replicates.

Grahic Jump Location
Grahic Jump Location
Appendix Figure 3.

Adjusted changes in adherence rates of antihypertensive and lipid-lowering prescriptions used by beneficiaries in months before and during the coverage gap, compared with the control group of low-income subsidy patients.

Month 0 represents the calendar month of entry into the coverage gap. The figures are based on mean differences in adjusted monthly adherence rates for each study group relative to the control group of fully eligible low-income subsidy patients. The adjusted monthly adherence rates were estimated with segmented regression models using generalized estimating equations with first-order, autoregressive correlation structure; variables for study groups, coverage gap status, months, and months after entering coverage gap; and interaction terms between group indicators and time-related variables. Data were adjusted for age, sex, race and ethnicity, Medicare entitlement status, metropolitan status (urban or rural), census region of residence, area-level characteristics (per capita income, unemployment rate, and education level) in beneficiary's county of residence, and prescription drug hierarchical condition category risk score. Error bars indicate 95% CIs obtained with 500 bootstrapped replicates.

Grahic Jump Location
Grahic Jump Location
Figure 2.

Adjusted changes in number of 30-day supply acid suppressant, pain reliever, and antidepressant prescriptions available by beneficiaries in months before and during the coverage gap, compared with the control group of low-income subsidy patients.

Month 0 represents the calendar month of entry into the coverage gap. The figures are based on mean differences in adjusted 30-day supply prescriptions available per month for each study group relative to the control group of fully eligible low-income subsidy patients. The adjusted 30-day supply prescriptions used per month were estimated with segmented regression models using generalized estimating equations with first-order, autoregressive correlation structure; variables for study groups, coverage gap status, months, and months after entering coverage gap; and interaction terms between group indicators and time-related variables. Data were adjusted for age, sex, race and ethnicity, Medicare entitlement status, metropolitan status (urban or rural), census region of residence, area-level characteristics (per capita income, unemployment rate, and education level) in beneficiary's county of residence, and prescription drug hierarchical condition category risk score. Error bars indicate 95% CIs obtained with 500 bootstrapped replicates.

Grahic Jump Location

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