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Correspondence: Address correspondence to Dawn Klein, Psychiatry Research-MEB, University of Iowa, Iowa City, IA 52242-1000. E-mail: dawn-m-klein{at}uiowa.edu
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Key Words: Elders • Prescription medication • Cost • Health insurance • Medicare
Medicare beneficiaries obtain prescription medication coverage primarily through (a) employer-sponsored plans, (b) Medicare health maintenance organizations (HMOs), (c) Medicaid, or (d) individually purchased Medigap plans (Poisal et al., 1999). Four fifths (80%) of Medicare beneficiaries routinely use prescription medications, and approximately one third (12 million) of Medicare beneficiaries have no prescription drug coverage (Poisal et al., 1999; Medicare Reform, 2001). Furthermore, only 59% of the oldest age group (85 years of age and older) has coverage for prescription medications (Poisal et al., 1999).
Although employer-sponsored or Medigap plans, Medicare HMOs, and Medicaid constitute the traditional ways for Medicare beneficiaries to obtain prescription coverage, this will change in 2006 with the enactment of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003. For example, in addition to the new voluntary prescription medication benefit (Medicare Part D), Medigap plans will no longer provide policies that offer prescription medication coverage, and the law will also provide subsidies to employers that provide prescription medication coverage comparable with Part D. Because of these impending changes and the importance of medication cost as a barrier to medication adherence, it is important for researchers to identify the impact of medication coverage on medication delay and to determine other independent factors that may contribute to medication delay (i.e., high prescription medication cost and low income).
Crystal, Johnson, Harman, Sambamoorthi, and Kumar (2000) studied out-of-pocket health care costs for Medicare beneficiaries over the age of 65. They found that the out-of-pocket cost for prescriptions was more than one third of the total out-of-pocket health care costs for this population. Even Medicare beneficiaries with some prescription drug coverage were, on average, responsible for one third of their medication expenses out of pocket (Poisal et al., 1999). Sambamoorthi, Shea, and Crystal (2003) found that 15.7% of Medicare beneficiaries with no medication coverage spent more than 10% of their income on medications.
As expected, the burden of out-of-pocket health care costs is greater for low-income elders (Crystal et al., 2000; Elwood, 2000; Gross et al., 1999; Rogowski, Lillard, & Kington, 1997). It has also been reported that Medicare beneficiaries without prescription medication coverage average fewer prescriptions per year and pay more for prescriptions than those with coverage (Poisal & Chulis, 2000).
Research examining medication adherence and the elderly population has reported the cost of medications as one factor that may affect adherence (Brand, Smith, & Brand, 1977; Col, Fanale, & Kronholm, 1990; Soumerai & Ross-Degnan, 1999; Stuart & Grana, 1998). This is an important issue when one considers that noncompliance for any reason with the use of prescription medication may contribute to emergency room visits, inpatient admissions, and overall health care costs (Col et. al, 1990; Greenberg, 1984; Olshaker et al., 1998; Stuart & Grana, 1998).
Cox, Jernigan, Coons, and Draugalis (2001) found that Medicare beneficiaries who had some insurance coverage for prescriptions but who were at risk for reaching their prescription cap took steps to reduce out-of-pocket medication costs. For example, 23.3% of such beneficiaries took less than the prescribed amount of medication, and 16.3% discontinued medications. These types of nonadherent medication behaviors may place beneficiaries at risk for drug-related morbidity and mortality.
Because of the substantial use of prescription medications and the out-of-pocket health care costs that elderly people may incur for medications, it is vital for researchers to examine cost as a factor that may influence the actual use of prescription medications. Our purpose in this article is to describe the health insurance, demographic, health, and financial status information of respondents that, because of cost, reported a delay in filling a prescription or took less of a medication than the amount prescribed. We hypothesize that elders with Medicare only and no prescription coverage will have the highest rate of delaying medication because of cost. In addition, certain populations, including non-Whites, low income and rural elders, and elders with poor health, will be at greater risk for delaying medication or taking less medication than prescribed because of cost.
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AHEAD participants are a nationally representative, multistage probability sample of noninstitutionalized elders. The initial sample was taken from the 1992 HRS household screening, and a supplemental sample of respondents aged 80 and older was identified by the Medicare Master Enrollment File. The first wave occurred in 1993–1994 and included 8,406 participants. Between Waves 1 and 2, 828 participants died; of the 7,578 remaining eligible participants, 7,038 (93% follow-up) participated during the second wave in 1995–1996. Initial participants were aged 70 and older. If the participants were married then their spouses participated regardless of their age, which in Wave 2 resulted in 325 participants that were younger than 70 years of age, with an age range of 41–106 years. For complete AHEAD sampling procedures, see Soldo and colleagues (1997).
For the purposes of this article, we included only those participants aged 65 and older with Medicare. The initial Wave 1 sample did not include institutionalized elders; however, if a respondent was institutionalized after Wave 1, he or she remained in the study and was interviewed at Wave 2. Data from institutionalized elders were excluded because this population may be more likely to have medication coverage, and medical personnel would be overseeing medication administration. We also excluded 13 respondents because some data were missing for the outcome variable. The resulting sample size was 6,535 participants. In this study we expand on an earlier study of medication self-restriction utilizing AHEAD data by Steinman, Sands, and Covinsky (2001), in that we include approximately one third of elders reporting medication delay who were not included in their analysis.
Outcome Variable
As part of the health utilization section of the AHEAD survey, respondents were asked this question: "Sometimes people delay taking medication or filling prescriptions because of the cost. At any time (since Wave 1 or in the last 2 years) have you ended up taking less medication than was prescribed for you because of the cost?" Five percent of the individuals in the sample (n = 332) reported delaying or taking less medication because of cost.
Explanatory Variables
Demographic variables included gender, age, marital status, race, education, and geographic location (rural or urban). Health status was determined by several variables. Respondents were asked to report if a doctor had diagnosed them with cancer, diabetes, high blood pressure, heart disease, lung disease, stroke, arthritis, or a psychiatric condition. A measure was then created to reflect the cumulative number of medical illnesses reported. Self-report and medical record information would be preferable; however, studies have demonstrated the acceptable validity of self-reported health conditions alone (Kehoe, Wu, Leske, & Chylack, 1994; Kriegsman, Penninx, van Eijk, Boeke, & Deeg, 1996).
Self-reported limitations of activities of daily living (ADLs) and measures of mobility determined functional impairment. An ADL limitation was determined as requiring assistance with bathing, dressing, walking, eating, using the toilet, or needing assistance getting in and out of bed. Mobility impairment was determined by a series of questions that asked participants about difficulty with everyday tasks and whether the impairment was expected to last longer than 3 months. These activities included the ability to walk several blocks, jog 1 mile, walk one block, sit for 2 hr, rise from a chair after sitting for a long time, climb several flights of stairs, climb one flight of stairs, stoop, kneel, or crouch, reach or extend arms above shoulder level, pull or push large objects, and lift or carry 10 lb.
Financial variables included household income, net worth, and out-of-pocket medication cost. We examined household income and net worth information from Wave 1 data. Household income was the combination of total family income before tax and total income of other household members before tax for 1992–1993. Net worth was calculated by taking the participant's total asset value and subtracting their debt. We determined out-of-pocket medication cost by the respondents' report of how much they paid on average each month for prescription medications (not how much their monthly prescriptions cost, but their out-of-pocket expense for the medications).
Participants reported their health care insurance coverage, including Medicare, Medicaid, and supplemental insurance or Medigap coverage as well as if their Medicare was managed through an HMO. In a separate question all respondents were asked, "Does/Do any of your health insurance plan(s) pay any part of the cost of prescription medications?" Therefore, we did not ascertain which specific insurance plan provided medication coverage by direct questioning.
Because of the variability of medication coverage within health plans, we could not examine the impact of insurance coverage on medication delay without stratifying health insurance by medication coverage. For example, although the majority of Medicaid participants have medication coverage, not all Medicaid beneficiaries have these benefits. (For example, Qualified Medicare Beneficiaries receive assistance with Medicare Part B premiums and Medicare Part A and Part B cost sharing, but they do not receive prescription medication assistance.) Therefore, we created six categories based on the two main categories of medication coverage or no medication coverage and three insurance groupings of (a) Medicare only, (b) Medicare and Medicaid, and (c) Medicare and a supplemental policy or Medicare HMO. The supplemental policy could be obtained through various sources, including employer, union, self-purchased Medigap plans, or other organizations. Although benefits may vary substantially among supplemental plans, we did not differentiate these in the main analysis because of the limited data availability for how participants obtained their supplemental coverage. However, we did conduct subanalyses on the basis of participants with this information. We also included participants that reported a Medicare HMO in this group because of the supplemental benefits that these plans may provide. Of note, 326 respondents reported Medicare only and prescription coverage. We hypothesize that these respondents may have privately purchased medication plans or discount cards, or they may have medication coverage through other programs (i.e., military health insurance).
Statistical Analysis
We did statistical analyses by utilizing SAS statistical software. We divided explanatory variables into three domains: demographics and health status, health insurance or medication coverage, and other financial variables. We ran a multivariate logistic regression analysis for variables within each domain, and a final model included all significant variables from the previous models. We present the multivariate results, and, for descriptive purposes, we also present the frequencies of medication delay because of cost. Because of the large sample size, we considered results significant at p <.01.
Sample size differed for some analyses as a result of nonresponse on specific questions. Overall, item-specific rates of nonresponse were low. Because the cumulative impact of excluding all subjects with any missing data could be quite large, allowing for nonresponse on specific items makes the selected sample more representative. To ensure that differential nonresponse by race, gender, or age did not influence the results, we reanalyzed the data by substituting extreme values for missing data; the essential findings were unchanged (analysis available upon request). Therefore, data are presented with variable missing responses.
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At the univariate level, 2.3% of elders reported a medication delay if they had an employer- or union-sponsored plan, and 5.2% delayed medication with other plans (
2 = 17.77, df = 1, p <.0001). Additional descriptive analyses revealed that those with employer supplements were three times more likely to have medication coverage than elders with other sources of supplemental coverage (employer = 75%, other sources = 22%; 2 = 807.5, df = 1, p <.0001). However, to determine the impact of type of supplement or medication coverage on medication delay, we conducted a logistic regression with the indicators of (a) employer or union coverage or nonemployer or other coverage and (b) medication coverage or no medication coverage. Results indicated that having medication coverage (2 = 17.26, df = 2, p <.0001, odds ratio or OR = 0.33, and 95% confidence interval or CI of 0.20–0.56) was the important indicator of medication delay, not type of supplemental coverage (2 = 1.83, df = 2, p =.18, OR = 0.72, and 95% CI of 0.45–1.16).
As shown in Table 3, net worth, household income, and out-of-pocket cost for medications were all significantly and independently associated with delay of medication because of cost in the multivariate logistic regression. If a participant reported spending more than $100 a month out of pocket for medications, there was a greater than 10% chance that medication would be delayed. The out-of-pocket cost was based on the actual amount spent by the participant, not the total cost of his or her medication.
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Elders with Medicare and Medicaid were also at risk for medication delay. This is not unexpected if we consider the income and resource guidelines surrounding Medicaid coverage as well as the variability in Medicaid plans. Even with Medicaid assistance, this population may be extremely sensitive to cost-containment strategies such as medication copayment or a restriction in the number of prescription medications that can be filled. Research by Soumerai, Avorn, Ross-Degnan, and Gortmaker (1987) found that cost containment in a state Medicaid program resulted in elderly and disabled persons' decreasing their drug use by 46%, including a decrease of "essential" medications, such as insulin and thiazide diuretics, by 28%.
It was surprising that only 5.8% of elders with no medication coverage and supplemental insurance or a Medicare HMO delayed medications as a result of cost. However, because health insurance coverage and income are closely related (Kuttner, 1999), it may be speculated that elders with a supplemental policy may be financially more able to cover the cost of prescription medications. In addition, those with supplemental policies have coverage for outpatient services, such as physician visits, which in turn may lower overall out-of-pocket health care costs and allow them to purchase prescription medications.
The insurance findings in this study are supported by Cohen, Bloom, Simpson, and Parsons (1997), who found elders with Medicare only or Medicare and Medicaid to be twice as likely to have unmet medical needs as Medicare beneficiaries with private policies. Furthermore, they found that elders with Medicare only were three times more likely to go without prescription medicine or glasses than those with Medicare and a private policy.
In addition to the insurance findings, certain subgroups, including African American elders, low-income elders, elders with high out-of-pocket medication costs, and elders with poor health, were more likely to delay medications. The finding that African American elders were significantly more likely to delay medication when health insurance status, income, and net worth were controlled is important, although the reasons for this finding are unclear. It may be that, in addition to the financial and health insurance issues, there is a cultural difference in the attitudes and experiences with the health care system that contributes to the actual use of health care and a possible mistrust of the health care system (Bird & Bogart, 2001; Gamble, 1997). The finding regarding increased risk for low-income elders and elders with high out-of-pocket medication cost is consistent with basic economics.
Elders with poor health as measured by multiple comorbid illnesses and mobility impairment were among the most likely to delay taking medication because of cost. This may occur because elders with multiple illnesses and functional impairment are likely prescribed more medications than elders with fewer medical conditions. In turn, their medications cost more, and they may have a greater opportunity to delay medication because of cost. It is important to consider the long-term effects of chronic medication noncompliance because of cost and the subsequent consequences for the individual and the health care system. As we noted earlier, noncompliance for any reason may contribute to emergency room visits, inpatient admissions, and overall health care costs (Col et al., 1990; Greenberg, 1984; Olshaker et al., 1998; Stuart & Grana, 1998).
We found it somewhat surprising that elders between the ages of 65 and 80 were at greater risk to delay medication because of cost than those aged 80 and older, especially when we considered research that has shown prescription medication coverage to be lower among the oldest old (Poisal et al., 1999). However, this finding is consistent with research by Mitchell, Mathews, Hunt, Cobb, and Watson (2001), who found that younger elders were more likely to mismanage medications regardless of their ability to pay for medications. Rogowski and colleagues (1997) also found that the financial burden for prescriptions continued to increase with age up until the age of 85. However, in their analysis as in this study, elders that were institutionalized were excluded, and, if we consider that institutionalization increases with age, perhaps the oldest old participating in the study were disproportionately healthy. Lastly, perhaps this older cohort is uncomfortable providing this information and is subject to social desirability bias. Future research is needed.
The sample size of those who reported a delay in medication because of cost is relatively small if we consider the size of the data set and when we compare it to existing research (Col et al., 1990; Cox et al., 2001; Mitchell et al., 2001; Stuart & Grana, 1998). It may be an underestimate of elderly people that delay or reduce medication use because of the cost. One reason for the possible underestimate is that this age cohort may feel uncomfortable sharing information about not following physician orders or discussing financial difficulties. In addition, because it is a self-report measure it is subject to recall inaccuracies, and because the time period in question is 2 years, participants may forget if they have delayed medications or not filled a prescription because of the cost. A variety of studies have found a range of accuracy in recalling the use of medications and health services (Brown & Adams, 1992; Rost & Roter, 1987; West et al., 1995). Poisal and colleagues (1999) reported that people may be more likely to recall large or traumatic medical expenses rather than smaller routine expenses and thus may be more likely to remember a hospitalization over prescription medication details. Although 5% of the sample seems like a small number, this represents approximately 1.7 million Medicare beneficiaries over the age of 65.
Lastly, although the question appears to have good face validity, it may not have been specific enough for some elders to say "yes" to a medication delay. Mitchell and colleagues (2001) asked rural elders about specific strategies for how they mismanaged medication because of cost. For example, did they take less medicine to make it last, or borrow money from someone for medicine, or did they do something else? This type of questioning was not feasible in this large epidemiologic study. It may not capture elders that go without other necessities or that find obtaining medication problematic but do what they need to in order to purchase their medication.
It is not possible to determine from our data if those that reported not taking or delaying medication as a result of cost were actually financially able to afford medication but unwilling to pay for it. For example, because of the high cost of some medications, patients may decide that the medication is too costly and that they do not really "need" the medication, even if they can afford it. There is also no indication of the clinical importance of medications that were delayed. It is important to note that these data are from 1995–1996, and current findings about medication delay because of cost may be different. Recent trends including rising medication costs (Kuttner, 1999; Levit et al., 2003) and a decline in medication coverage by coverage source (Goldman & Zissimopoulos, 2003; McCormack et al., 2002) may contribute to increased difficulties with medication costs. Lastly, because of the cross-sectional nature of the data, the long-term impact of delaying medication or other noncompliance issues that may affect long-term health care utilization and health status are not examined.
The passage of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 will impact medication coverage for elders. The legislation creates a voluntary drug benefit (Medicare Part D) with a $35.00 monthly premium, $250.00 annual deductible, and 25% cost sharing on prescriptions until $2,250. There is no drug coverage between $2,250 and $5,100, after which the beneficiary will pay the greater of $2 for generics or $5 for brand drugs or 5% coinsurance. This benefit will go into effect in 2006; in the meantime, a Medicare drug discount card is currently available.
The Act also establishes premium and cost-sharing subsidies for low-income beneficiaries. For example, beneficiaries eligible for Medicare and Medicaid (called dual eligibles) and others that qualify for low-income subsidies will not have to pay 100% of their medication costs when they reach the $2,250 limit. However, it should be noted that, under the new law, dually eligible beneficiaries will no longer receive prescription medication benefits through Medicaid. They will need to enroll in a Part D plan, which may have some negative consequences. In at least 24 states, the copayment obligations under the new law will be higher than what beneficiaries currently pay; as a result, they may actually pay more out of pocket for medications when they are enrolled in Part D. In addition, the selection of drugs available through Part D may be more limited than what is currently available, and beneficiaries will be responsible for 100% of the medication cost if it is not covered by their Part D plan (Guyer & Schneider, 2004).
The lack of coverage between $2,250 and $5,100 is also concerning. Beneficiaries that reach this initial limit will have spent $750 out of pocket and will spend $2,850 more before catastrophic coverage begins ($3,600 total out of pocket), not including premium costs. Elders with prescription costs this high may find it difficult to obtain prescriptions during this gap in coverage. In this study, we found that if elders spent more than $100 a month out of pocket for medications, there was a greater than 10% chance medication would be delayed because of cost.
Other criticisms noted about the new legislation include concern that (a) the country cannot afford a $400 billion drug benefit at this time; (b) it does little to address the high cost of prescriptions; and (c) channeling the drug benefit through private plans will continue the trend of high and rising drug prices, resulting in inadequate prescription assistance (Bodenheimer, 2001; Cundiff, 2003).
Despite these concerns, the legislation is an initial step toward providing prescription medication coverage to seniors, and it does provide targeted assistance to low-income elders and elders with high prescription costs, who are identified as being at risk for medication delay because of cost in this study. It will also provide the opportunity for all elders to have access to prescription medication coverage. As this policy becomes enacted, it will be important to monitor its impact on at-risk elders identified in this study.
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1 Psychiatry Research-MEB, University of Iowa, Iowa City.
2 Department of Epidemiology, University of Iowa, Iowa City.
Decision Editor: Linda S. Noelker, PhD
Received for publication September 25, 2003. Accepted for publication March 29, 2004.
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