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Figure 1.
Sources of Supplemental Prescription Drug Coverage Among Medicare Beneficiaries With Glaucoma by Participant Characteristics
Sources of Supplemental Prescription Drug Coverage Among Medicare Beneficiaries With Glaucoma by Participant Characteristics

Proportions of beneficiaries are shown on the y-axis.

Figure 2.
Risk-Adjusted Out-of-Pocket Payments per Prescription by Prescription Drug Coverage and Annual Income
Risk-Adjusted Out-of-Pocket Payments per Prescription by Prescription Drug Coverage and Annual Income

The 2015 US dollars are in thousands.

Table 1.  
Characteristics of Medicare Beneficiaries Who Filled at Least 1 Glaucoma Medication During the Survey Yearsa
Characteristics of Medicare Beneficiaries Who Filled at Least 1 Glaucoma Medication During the Survey Yearsa
Table 2.  
Highest Form of Prescription Drug Coverage for the Total Sample by Annual Income Stratuma
Highest Form of Prescription Drug Coverage for the Total Sample by Annual Income Stratuma
Table 3.  
Regression Results for Calculating Predictors of Out-of-Pocket Prescription Drug Costs
Regression Results for Calculating Predictors of Out-of-Pocket Prescription Drug Costs
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Agency for Healthcare Research and Quality. 2014 National healthcare quality and disparities report.http://www.ahrq.gov/research/findings/nhqrdr/nhqdr14/index.html. Updated June 2015. Accessed July 1, 2015.
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Frieden  TR; Centers for Disease Control and Prevention (CDC).  Foreword: CDC health disparities and inequalities report: United States, 2011. MMWR Surveill Summ. 2011;60(suppl):1-2. PubMed
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Lillie-Blanton  M, Hoffman  C.  The role of health insurance coverage in reducing racial/ethnic disparities in health care. Health Aff (Millwood). 2005;24(2):398-408.PubMedArticle
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Blumberg  DM, Prager  AJ, Liebmann  JM, Cioffi  GA, De Moraes  CG.  Cost-related medication nonadherence and cost-saving behaviors among patients with glaucoma before and after the implementation of Medicare Part D. JAMA Ophthalmol. 2015;133(9):985-996.PubMedArticle
5.
Gellad  WF, Haas  JS, Safran  DG.  Race/ethnicity and nonadherence to prescription medications among seniors: results of a national study. J Gen Intern Med. 2007;22(11):1572-1578.PubMedArticle
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Sleath  B, Robin  AL, Covert  D, Byrd  JE, Tudor  G, Svarstad  B.  Patient-reported behavior and problems in using glaucoma medications. Ophthalmology. 2006;113(3):431-436.PubMedArticle
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Briesacher  BA, Zhao  Y, Madden  JM,  et al.  Medicare Part D and changes in prescription drug use and cost burden: national estimates for the Medicare population, 2000 to 2007. Med Care. 2011;49(9):834-841.PubMedArticle
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Centers for Medicare & Medicaid Services. Medicare Current Beneficiary Survey (MCBS).https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/index.html?redirect=/MCBS/. Updated March 26, 2015. Accessed June 22, 2015.
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Regan  JF, Petroski  CA.  Prescription drug coverage among Medicare beneficiaries. Health Care Financ Rev. 2007;29(1):119-125.PubMed
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Centers for Medicare & Medicaid Services. CMS CY 2014 out-of-pocket cost model methodology.http://www.medicare.gov/Publications/Pubs/pdf/oopc_specs.pdf. Updated December 2013. Accessed June 22, 2015.
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Lawton  MP, Brody  EM.  Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179-186.PubMedArticle
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US Department of Health and Human Services. 2015 Poverty guidelines.http://aspe.hhs.gov/poverty/15poverty.cfm#thresholds. Updated September 3, 2015. Accessed June 4, 2015.
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2015 Federal poverty level. Obamacare website. https://obamacare.net/2015-federal-poverty-level/. Updated November 15, 2015. Accessed June 25, 2015.
14.
The Henry J. Kaiser Family Foundation. Examining sources of coverage among Medicare beneficiaries: supplemental insurance, Medicare Advantage, and prescription drug coverage: findings from the Medicare Current Beneficiary Survey, 2006.https://kaiserfamilyfoundation.files.wordpress.com/2013/01/7801.pdf. Published August 2008. Accessed June 4, 2015.
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Goldman  DP, Joyce  GF, Zheng  Y.  Prescription drug cost sharing: associations with medication and medical utilization and spending and health. JAMA. 2007;298(1):61-69.PubMedArticle
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Ashenfelter  O, Card  D.  Using the longitudinal structure of earnings to estimate the effects of training programs. Rev Econ Stat. 1985;67(4):648-660.Article
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The Henry J. Kaiser Family Foundation. Income and assets of Medicare beneficiaries, 2013-2030.https://kaiserfamilyfoundation.files.wordpress.com/2014/01/8540-income-and-assets-of-medicare-beneficiaries-2013-e28093-20301.pdf. Published January 9, 2014. Accessed July 5, 2015.
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Advisory Council on Employee Welfare and Pension Benefit Plans, United States Department of Labor. Disparities for women and minorities in retirement savings.http://www.dol.gov/ebsa/publications/2010ACreport3.html. Accessed July 5, 2015.
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Clark  RL, Ghent  LS, Headen  AE Jr.  Retiree health insurance and pension coverage: variations by firm characteristics. J Gerontol. 1994;49(2):S53-S61.Article
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The Dartmouth Atlas of Healthcare. Racial disparities. http://www.dartmouthatlas.org/keyissues/issue.aspx?con=2942. Accessed July 8, 2015.
21.
Eapen  ZJ, Hammill  BG, Setoguchi  S,  et al.  Who enrolls in the Medicare Part D prescription drug benefit program? medication use among patients with heart failure. J Am Heart Assoc. 2013;2(5):e000242. doi:10.1161/JAHA.113.000242.PubMedArticle
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Corrieri  S, Heider  D, Matschinger  H, Lehnert  T, Raum  E, König  HH.  Income-, education- and gender-related inequalities in out-of-pocket health-care payments for 65+ patients: a systematic review. Int J Equity Health. 2010;9:20.PubMedArticle
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Social Security Administration. Actuarial life table.http://www.ssa.gov/oact/STATS/table4c6.html. Accessed July 5, 2015.
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Outreville  JF.  Risk aversion, risk behavior, and demand for insurance: a survey. J Insur Issues. 2014;37(2):158-186.
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Original Investigation
Journal Club
February 2016

Variation in Prescription Drug Coverage Enrollment Among Vulnerable Beneficiaries With Glaucoma Before and After the Implementation of Medicare Part D

Journal Club PowerPoint Slide Download
Author Affiliations
  • 1Bernard and Shirlee Brown Glaucoma Research Laboratory, Department of Ophthalmology, Edward S. Harkness Eye Institute, Columbia University Medical Center, New York, New York
  • 2Department of Ophthalmology, Columbia University Medical Center, College of Physicians and Surgeons, New York, New York
JAMA Ophthalmol. 2016;134(2):212-220. doi:10.1001/jamaophthalmol.2015.5090
Abstract

Importance  It is important to understand in more detail how patients with glaucoma were affected by the implementation of Medicare Part D, which was designed to provide beneficiaries with near-universal prescription drug coverage.

Objectives  To determine changes in prescription drug coverage and out-of-pocket spending after the implementation of Medicare Part D across income strata and to identify characteristics of beneficiaries associated with prescription status.

Design, Setting, and Participants  Longitudinal observational study in the general community using the Medicare Current Beneficiary Survey (pooled 2004, 2005, 2007, and 2008 data). Participants were noninstitutionalized Medicare beneficiaries who filled at least 1 glaucoma prescription during the survey years. The dates of this analysis were January 2004 to December 2009.

Main Outcomes and Measures  Effect of the implementation of the Medicare Part D drug benefit, including prescription drug coverage and risk-adjusted out-of-pocket spending related to glaucoma medications.

Results  Respondents included 12 079 participants in the 2004 survey, 11 089 participants in the 2005 survey, 11 995 participants in the 2007 survey, and 11 723 participants in the 2008 survey. The sample included 19 045 glaucoma prescriptions, and 2519 Medicare beneficiaries filled at least 1 glaucoma prescription during the study years. Overall 574 (22.8%) beneficiaries reported living below the poverty level, and 795 (31.6%) had incomes consistent with near-poor status. The implementation of Medicare Part D resulted in increased rates of prescription drug coverage across all economic strata, with reductions in beneficiaries without coverage from 22.8% to 4.0%, 29.1% to 7.3%, and 19.9% to 3.7% among poor, near-poor, and higher-income beneficiaries, respectively. Despite these gains, near-poor status remained a risk factor for lack of prescription drug coverage after the implementation of Medicare Part D (odds ratio, 2.46; 95% CI, 1.26-4.55; P = .04). No differences were identified in adjusted out-of-pocket prescriptions drug costs between the near poor and those with higher income, although out-of-pocket costs were 37% (95% CI, 26%-49%; P < .001) lower among the poor relative to those with higher income.

Conclusions and Relevance  Medicare Part D enrolled most beneficiaries with glaucoma who previously lacked prescription drug coverage. The results of this study suggest that coverage gains lagged among the near poor. While these data evaluated changes in coverage among cohorts of beneficiaries and not from longitudinal follow-up of patients, targeted efforts to improve prescription drug coverage among vulnerable beneficiaries would likely improve access to prescribed ocular hypotensive medications.

Introduction

Despite efforts to reduce or eliminate health disparities in the United States, significant inequalities exist regarding access to care, morbidity, and mortality.1 Studies find that Americans living in poverty are much more likely to be in fair or poor health and to have disabling conditions or chronic illnesses that are more severe2 and are less likely to be engaged in the health care system.3 The financial burden for prescription drug costs may be particularly challenging for those who are underinsured or uninsured because they are largely or wholly responsible for the cost of medication. Even among those who have prescription drug coverage, the acquisition of medication generally requires some type of cost sharing, such as a copayment or coinsurance, which may be a deterrent to prescription refills or may result in spending less for basic needs to save for medications.4 This dilemma can be particularly problematic for minority communities because higher percentages of blacks and Hispanics have reported nonadherence to medication regimens because of cost.5

The cost of glaucoma medications is a significant barrier to adherence to topical therapy.6 Before 2006, there was no uniform prescription drug coverage for Medicare beneficiaries, and only 65% to 80% of overall Medicare beneficiaries had prescription drug coverage.7 In 2006, the Medicare Modernization Act implemented the Part D prescription drug benefit, which allowed adults covered under Medicare to purchase insurance for prescription drugs. While the purpose of the Part D program was to increase the availability of prescription medications to Medicare beneficiaries, little is known about how recent policy changes have affected the ability of patients with glaucoma in the United States to acquire their medications and, in particular, how such policy changes affect vulnerable subpopulations, such as the economically disadvantaged and minorities.

In this study, changes in prescription drug coverage and trends in out-of-pocket drug spending among a nationally representative sample of Medicare beneficiaries with glaucoma were assessed before and after the implementation of Medicare Part D. We were particularly interested in evaluating whether there were income-based, racial/ethnic, or regional variations in prescription drug coverage before and after implementation of the drug benefit and in assessing how prescription drug coverage affected out-of-pocket costs among beneficiaries.

Box Section Ref ID

At a Glance

  • Understanding variation in prescription drug coverage enrollment among vulnerable beneficiaries with glaucoma before and after the implementation of Medicare Part D is desirable.

  • Part D was found to reduce the percentage of beneficiaries with glaucoma who are without coverage from 23.6% to 4.9% across all economic strata, but inequalities continue to exist.

  • While these data evaluated changes in coverage among cohorts of beneficiaries and not from longitudinal follow-up of patients, targeted efforts to improve prescription drug coverage among vulnerable populations likely would improve access to needed ocular hypotensive medications.

Methods
Medicare Current Beneficiary Survey

This study was conducted using the Medicare Current Beneficiary Survey (MCBS) data set. The Columbia University Medical Center determined this study was exempt from institutional review board approval and participant informed consent. The MCBS is a nationally representative panel survey of institutionalized and noninstitutionalized Medicare beneficiaries and has been previously described elsewhere.8 In short, interview data are linked with Medicare claims and detailed use data. The MCBS cohort was drawn from an enrollment list of all persons eligible for Medicare coverage and includes a national sample of approximately 12 000 to 16 000 participants each year. Respondents provide information on filled prescriptions during in-depth, face-to-face interviews at 4-month intervals, during which they are asked to bring and review pill bottles and other medication containers. Prescription drug information is then verified by invoices, receipts, explanation-of-benefits forms, and empty prescription containers and supplemented by Medicare claims data, which has helped to ensure the reliability of the information.9 Monthly out-of-pocket costs to the beneficiary are calculated by the Centers for Medicare & Medicaid Services.10

Inclusion Criteria

Our study included MCBS respondents who filled at least 1 glaucoma prescription during the survey years as identified by drug claims and survey results. Participants were selected from the survey years 2004, 2005, 2007, and 2008. Because the Part D drug benefit was implemented in 2006, it was considered a transition year and was not included in our sample.

Baseline Demographics, Health Factors, and Ocular Hypotensive Medication

For all beneficiaries, demographic characteristics were described using annual survey responses, including age, sex, self-reported race/ethnicity, geographic region, education, current employment status, and urban vs rural residence. The 9 US census divisions were consolidated into the 4 regions of Northeast, Midwest, South, West, and Puerto Rico. Baseline health factors included self-reported poor vision, functional independence in activities of daily living (as measured by the Lawton Index11), and the Charlson Comorbidity Index, which is derived from International Classification of Diseases, Ninth Revision codes and is used to measure health status. In analyses for which glaucoma medications were included, all ocular hypotensive medications except for β-adrenergic antagonists and miotics were considered in branded form because most generics were not available during the study period.

Income and Socioeconomic Variables

Income was self-reported and represented the sum of pension, Social Security, and retirement benefits. When beneficiaries reported household income, individual income was calculated by dividing the household income in the numerator with the number of individuals in the household in the denominator. Those whose total annual income was less than $15 000 or less than 125% of the poverty level were designated as having a low income.12 Those whose total income was $15 000 to $30 000 or 125% to 250% of the poverty level were designated as being near poor. Those whose total income exceeded $30 000 were designated as having higher income. Low income was categorized based on approximate qualifications for Medicaid eligibility in all 50 states in 2015, and near-poor status was based on beneficiaries’ eligibility in 2015 for cost-sharing reduction in subsidies.13 Additional indicators of income included self-reported education and current employment status because working past the age of retirement may reflect an effort to maintain or afford a standard of living.

Insurance Status

Prescription drug coverage was coded in a mutually exclusive, hierarchical fashion using MCBS insurance coverage variables following the classification by The Henry J. Kaiser Family Foundation.14 The prescription drug coverage hierarchy is as follows: (1) Part D stand-alone prescription drug plan; (2) Medicare Advantage; (3) employer; (4) self-purchased only; (5) other public or private coverage, including dual-eligible Medicare and Medicaid plans, Veterans Affairs insurance, Department of Defense coverage, and state-funded programs; and (6) no prescription drug coverage. Beneficiaries with multiple drug plans were assigned to the highest level of prescription drug coverage. Before the implementation of Part D, dual-eligible beneficiaries with Medicare and Medicaid coverage were able to receive drug benefits through Medicaid prescription drug coverage, whereas after the Medicare Modernization Act went into effect, drugs became covered by the Part D prescription drug benefit.

Costs

All costs were converted to 2015 US dollars using the Consumer Price Index. Because out-of-pocket payment costs will affect medication use, beneficiaries with a greater degree of cost sharing may delay or avoid refilling their medications.15 Because patients were included in our analyses only if they successfully filled at least 1 glaucoma prescription medication, we calculated the median out-of-pocket cost for 1 prescription refill based on the number of refills obtained during the survey years.

Statistical Analysis

Baseline demographic, clinical, socioeconomic, and insurance characteristics of Medicare beneficiaries with glaucoma surveyed during the study period were determined by year, as were the proportions of beneficiaries in each prescription drug coverage plan. For all analyses, an independent 2-group t test was performed for continuous variables, and a χ2 test was used for categorical variables.

Multivariable stepwise logistic regression with robust standard errors was used to evaluate baseline demographic, clinical, and socioeconomic patient characteristics associated with prescription drug coverage. The main outcome variables were (1) prescription drug coverage status and (2) source of coverage before and after the implementation of Medicare Part D. Baseline covariates considered in the models included age, sex, annual income, race/ethnicity, geographic region, education, current employment status, urban vs rural residence, Charlson Comorbidity Index and functional independence indexes, and self-reported poor vision.

Out-of-pocket spending was modeled using a generalized linear model with a gamma distribution as its probability distribution and log link as its link function. Gamma generalized linear models are commonly used to account for distributions in highly skewed data, such as expenditure data.16 To verify the family of distributions, a modified Park test was performed to confirm that the gamma distribution was the best fit for our data. The main outcome variable in the model was the median out-of-pocket expenditures per prescription. Because patient characteristics and financial resources may influence enrollment in a prescription drug coverage plan, assessing the association between prescription drug coverage and costs may be prone to selection bias. For this reason, we calculated a risk-adjusted predictive method that included all baseline demographic, clinical, and socioeconomic factors, in addition to insurance prescription drug coverage and class of medication. Bootstrap resampling was used for model validation.

Results

Respondents included 12 079 participants in the 2004 survey, 11 089 participants in the 2005 survey, 11 995 participants in the 2007 survey, and 11 723 participants in the 2008 survey. Our sample included 19 045 glaucoma prescriptions filled by Medicare beneficiaries during 2004-2005 (before the implementation of Medicare Part D) and 2007-2008 (after the implementation of Medicare Part D). In total, 2519 Medicare beneficiaries filled at least 1 glaucoma prescription during these years. When examined by year, there were 578 beneficiaries in 2004, 629 beneficiaries in 2005, 658 beneficiaries in 2007, and 654 beneficiaries in 2008. Overall, 574 (22.8%) beneficiaries reported living below the poverty level, and 795 (31.6%) had incomes consistent with near-poor status, which is similar to national Medicare beneficiary data.17

No differences were identified before and after the implementation of Medicare Part D in participants’ sex, age, mean annual income or income strata, race/ethnicity, geographic region, urban vs rural residence, self-reported poor vision, or International Classification of Diseases, Ninth Revision glaucoma diagnosis. After the implementation of Part D, patients reported slightly higher levels of education compared with before the implementation of Part D (Table 1) (odds ratio [OR], 1.22; 95% CI, 1.04-1.43; P = .03 for reporting some college education).

Characteristics Associated With Prescription Drug Coverage Status

Of the 1207 respondents from the years before the implementation of Part D, 23.6% were without prescription drug coverage. Of the 1312 respondents from the years after the implementation of Part D, 4.9% remained without prescription drug coverage (difference, 18.7%; 95% CI, 16.1%-21.4%; P < .001) (Table 2). The implementation of Medicare Part D was found to reduce the percentage of beneficiaries without coverage across all income strata, with reductions in those without coverage from 22.8% to 4.0% (difference, 18.7%; 95% CI, 13.4%-24.2%) among poor beneficiaries, from 29.1% to 7.3% (difference, 20.9%; 95% CI, 16.3%-25.7%) among near-poor beneficiaries, and from 19.9% to 3.7% (difference, 16.2%; 95% CI, 12.4%-19.9%) among higher-income beneficiaries (P < .001 for all). Figure 1 shows the source of prescription drug coverage by patient characteristics before and after the implementation of Medicare Part D. The eTable in the Supplement lists the source of prescription drug coverage among Medicare beneficiaries with glaucoma by insurance type.

Multivariable logistic regression was used to determine baseline demographic, clinical, and socioeconomic characteristics associated with prescription drug coverage status. Before the implementation of Part D, white race (OR, 1.82; 95% CI, 1.24-2.95; P = .03) was associated with lack of prescription drug coverage, as was residence in a rural area (OR, 1.88; 95% CI, 1.27-2.30; P = .001), the Midwest (OR, 1.80; 95% CI, 1.22-3.17; P = .01), the South (OR, 1.96; 95% CI, 1.30-2.26; P = .004), or Puerto Rico (OR, 17.58; 95% CI, 4.22-78.22; P < .001). Those with current employment (OR, 1.87; 95% CI, 1.17-3.81; P = .03) and near-poor income status (OR, 1.91; 95% CI, 1.35-2.79; P < .001) were more likely to lack prescription drug coverage, although those living in poverty were not (OR, 1.28; 95% CI, 0.82-2.00; P = .27). After 2006, patients who remained without prescription drug coverage were more likely to be near poor (OR, 2.46; 95% CI, 1.26-4.55; P = .04) or reside in Puerto Rico (OR, 12.65; 95% CI, 1.43- 22.03; P = .05). In addition, men were then more likely to lack prescription drug coverage (OR, 1.98; 95% CI, 1.20-4.90; P = .05).

Before the implementation of Part D, predictors of Medicaid coverage were age 65 years or older (OR, 7.69; 95% CI, 2.90-49.90; P = .001), black race (OR, 6.47; 95% CI, 3.94-13.13; P < .001), Hispanic ethnicity (OR, 7.50; 95% CI, 3.08-15.53; P < .001), residence in the Northeast (OR, 3.33; 95% CI, 1.42-7.69; P = .01 relative to the Midwest), and a lower level of functional independence (OR, 0.08; 95% CI, 0.73-0.99; P = .02 per Lawton Index point). By definition, annual income was the strongest predictor of Medicaid prescription drug coverage (OR, 132; 95% CI, 38-880; P < .001 for poor and OR, 13.70; 95% CI, 3.23-71.72; P = .001 for near poor). After 2006, Medicaid no longer provided drug benefits because dual-eligible beneficiaries were transitioned into Medicare Part D.

Beneficiaries with Part D coverage were more likely to be female (OR, 1.55; 95% CI, 1.15-2.12; P = .01), from an urban area (OR, 1.80; 95% CI, 1.33-2.85; P < .001), near poor (OR, 2.61; 95% CI, 1.50-3.42; P = .001), or poor (OR, 7.36; 95% CI, 4.62-11.80; P < .001). Beneficiaries with employee-based health coverage were more likely to be of white race (OR, 1.49; 95% CI, 1.12-3.22; P < .001), live in an urban area (OR, 1.74; 95% CI, 1.31-2.71; P < .001), have higher income (OR, 16.10; 95% CI, 11.60-47.09; P < .001 relative to poor and OR, 2.85; 95% CI, 2.06-4.23; P < .001 relative to near poor), be retired (OR, 1.53; 95% CI, 1.05-3.01; P = .04), and have more education (OR, 2.25; 95% CI, 1.85-3.79; P < .001 for some college or higher relative to no college). Characteristics of beneficiaries with employee-based health coverage were similar before and after the implementation of Medicare Part D.

Out-of-pocket Spending

Table 3 lists generalized linear model coefficients, standard errors, and P values for per-prescription out-of-pocket expenditures throughout the study period. Adjusted baseline predictors of out-of-pocket cost per prescription included female sex (P = .001), age 65 years or older (P = .01), non-Hispanic ethnicity and white race (P < .001 for both), and geographic region (range, P < .001 to P = .009 relative to the Northeast).

Adjusted socioeconomic predictors of out-of-pocket costs included higher income (P < .001 relative to poor) and more education (P = .05). There was no difference in out-of-pocket costs between the near poor and those with higher income (P = .86), although out-of-pocket costs were 37% (95% CI, 26%-49%; P < .001) lower among the poor relative to those with higher income (Figure 2). Patients without prescription drug coverage (P < .001), with Medicare Advantage (P = .02), or with self-purchased coverage (P < .001) had greater costs than those with employee-based health coverage. Conversely, those with other coverage such, as state-sponsored indigent programs or Veterans Affairs coverage, had lower costs than those with employer-sponsored coverage (P < .001 for all).

Discussion

This article provides an in-depth look at the source of prescription drug coverage among beneficiaries with glaucoma before and after the implementation of the Medicare Part D prescription drug benefit and at out-of-pocket costs associated with prescription drug coverage status. We found that the percentage of patients with glaucoma without prescription drug coverage declined over the study period from 23.6% to 4.9%, suggesting that Part D reached most beneficiaries with glaucoma who previously lacked prescription drug coverage.

The implementation of Medicare Part D resulted in increased rates of prescription drug coverage across all economic strata. However, after the implementation, the near poor were more likely to remain without prescription drug coverage. Unlike those living in poverty, the near poor in many circumstances do not qualify for low-income subsidies. In contrast, many beneficiaries living in poverty are dual eligible and had prescription drug coverage through Medicaid drug plans before 2006. After 2006, low-income beneficiaries who were dual eligible or received low-income subsidies were automatically enrolled in Part D and continued to obtain prescription drug coverage though the Part D plan. It appears that beneficiaries with incomes near but above the poverty level have too much income or too many assets to qualify for public programs but remained unable to afford private coverage. As a result, out-of-pocket costs incurred by the near poor were similar to those with higher income and were considerably more than the costs of poor patients.

Race/ethnicity was not a significant predictor of prescription drug coverage, although there were large differences in the source of prescription drug coverage by this variable. The lower levels of employer-sponsored insurance for nonwhite beneficiaries are probably a result of the lower levels of employment in jobs that offered retirement health benefits among minority communities.18 By extension, annual income and employer-sponsored prescription drug coverage are highly correlated because employers who offer retiree prescription drug coverage generally also offer pension benefits.19 Because many patients gained or switched coverage to Part D, race/ethnicity was not a predictor of Part D status despite the significant association with Medicaid coverage before the implementation of Medicare Part D.

While annual income and race/ethnicity appear to be important determinants of prescription drug coverage and type of coverage for beneficiaries with glaucoma, our results suggest that geographic region and urban vs rural residence may be equally important in plan enrollment. Regional differences may be highly correlated with annual income and race/ethnicity because geographic variation in health care spending and use and quality of care has been shown to account for a portion of racial/ethnic disparities in health outcomes.20 Alternatively, local factors, such as public and private sector employment opportunities, Medicaid and low-income subsidy availability, and access or proximity to health care professionals and pharmacies, may contribute to geographic variation in prescription drug coverage.

Throughout the study period, the odds of a woman being enrolled in some form of prescription drug coverage were approximately 50% greater that of a man. Since the implementation of Part D, the odds were 3 times higher for a woman to have prescription drug coverage than a man, and the odds of a woman enrolling in Part D were twice that of a man, as has been reported in the general Medicare population.21 The reasons for this discrepancy are unclear. It has been hypothesized that more women than men qualify for Part D because of higher poverty rates and greater eligibility for public plans among women than men.22 However, because women are known to have a longer life expectancy than men,23 it is possible that women who outlive their spouses subsequently purchase Part D plans. Alternatively, there is a large body of literature confirming that women are more risk averse than men.24 It is possible that such risk aversion may translate to decisions regarding purchasing prescription insurance. Future work in this area is merited.

Although many beneficiaries with glaucoma gained prescription drug coverage through the implementation of Part D, our results indicate that coverage gains lagged among the near-poor relative to the rest of the population. However, our study had at least 4 limitations that should be considered. First, our study included only data of patients who successfully filled at least 1 glaucoma prescription. Because patients with extremely high out-of-pocket costs may have failed to fill a prescription, our results are prone to some selection bias. Second, we did not follow up patients longitudinally but instead evaluated changes in coverage among cohorts of Medicare beneficiaries. Third, because we did not have a comparable control group for Part D beneficiaries, we were not able to evaluate the effect of the differences of the Part D beneficiaries relative to controls over time. Fourth, study end points included prescription drug coverage status and out-of-pocket expenses. Future research should consider evaluating whether gains in prescription drug coverage from the implementation of Part D have improved patient adherence.

Conclusions

Our results suggest that the Part D benefit has improved prescription drug coverage for Medicare beneficiaries with glaucoma. However, inequalities continue to exist. Lack of prescription drug coverage is worrisome relative to adherence to treatment regimens because data suggest that individuals without prescription drug coverage are 4.5 times more likely not to fill a prescription.25 Targeted efforts to improve prescription drug coverage among vulnerable populations with glaucoma would likely improve access to necessary ocular hypotensive medications.

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Article Information

Submitted for Publication: July 21, 2015; final revision received October 21, 2015; accepted October 22, 2015.

Corresponding Author: Dana M. Blumberg, MD, MPH, Bernard and Shirlee Brown Glaucoma Research Laboratory, Department of Ophthalmology, Edward S. Harkness Eye Institute, Columbia University Medical Center, 635 W 165th St, New York, NY 10032 (dmb2196@columbia.cumc.edu).

Published Online: December 23, 2015. doi:10.1001/jamaophthalmol.2015.5090.

Author Contributions: Dr Blumberg had full access to all the data in the study and takes responsibility for the integrity of the data and accuracy of the data analyses.

Study concept and design: Blumberg.

Acquisition, analysis, or interpretation of data: Blumberg.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: All authors.

Administrative, technical, or material support: All authors.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest, and none were reported.

Funding/Support: This project is supported by an unrestricted grant from the glaucoma research fund at the Edward S. Harkness Eye Institute, Columbia University Medical Center (Dr Blumberg).

Role of the Funder/Sponsor: The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References
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Agency for Healthcare Research and Quality. 2014 National healthcare quality and disparities report.http://www.ahrq.gov/research/findings/nhqrdr/nhqdr14/index.html. Updated June 2015. Accessed July 1, 2015.
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Frieden  TR; Centers for Disease Control and Prevention (CDC).  Foreword: CDC health disparities and inequalities report: United States, 2011. MMWR Surveill Summ. 2011;60(suppl):1-2. PubMed
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Lillie-Blanton  M, Hoffman  C.  The role of health insurance coverage in reducing racial/ethnic disparities in health care. Health Aff (Millwood). 2005;24(2):398-408.PubMedArticle
4.
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