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The American Journal of Managed Care November 2004 - Part 2
Screening for Depression and Suicidality in a VA Primary Care Setting: 2 Items Are Better Than 1 Item
Kathryn Corson, PhD; Martha S. Gerrity, MD, MPH, PhD; and Steven K. Dobscha, MD
The Veterans Health Administration: Quality, Value, Accountability, and Information as Transforming Strategies for Patient-Centered Care
Jonathan B. Perlin, MD, PhD, MSHA; Robert M. Kolodner, MD; and Robert H. Roswell, MD
VA Health Services Research: Lessons for the World's Healthcare Organizations
Steven J. Bernstein, MD, MPH
Variation in Implementation and Use of Computerized Clinical Reminders in an Integrated Healthcare System
Constance H. Fung, MD, MSHS; Juliet N. Woods, MS; Steven M. Asch, MD, MPH; Peter Glassman, MBBS, MSc; and Bradley N. Doebbeling, MD, MSc
Dual-system Utilization Affects Regional Variation in Prevention Quality Indicators: The Case of Amputations Among Veterans With Diabetes
Chin-Lin Tseng, DrPH; Jeffrey D. Greenberg, MD, MPH; Drew Helmer, MD, MS; Mangala Rajan, MBA; Anjali Tiwari, MD; Donald Miller, ScD; Stephen Crystal, PhD; Gerald Hawley, RN, MSN; and Leonard Pogach, M
Assessing the Accuracy of Computerized Medication Histories
Peter J. Kaboli, MD, MS; Brad J. McClimon, MD, PharmD; Angela B. Hoth, PharmD; and Mitchell J. Barnett, PharmD, MS
The Relationship of System-Level Quality Improvement With Quality of Depression Care
Andrea Charbonneau, MD, MSc; Victoria Parker, DBA; Mark Meterko, PhD; Amy K. Rosen, PhD; Boris Kader, PhD; Richard R. Owen, MD; Arlene S. Ash, PhD; Jeffrey Whittle, MD, MPH; and Dan R. Berlowitz, MD,
Designing an Illustrated Patient Satisfaction Instrument for Low-literacy Populations
Janet Weiner, MPH; Abigail Aguirre, MPA; Karima Ravenell, MS; Kim Kovath, VMD; Lindsay McDevit, MD; John Murphy, MD; David A. Asch, MD, MBA; and Judy A. Shea, PhD
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Problems Due to Medication Costs Among VA and Non-VA Patients With Chronic Illnesses
John D. Piette, PhD; and Michele Heisler, MD, MPA

Problems Due to Medication Costs Among VA and Non-VA Patients With Chronic Illnesses

John D. Piette, PhD; and Michele Heisler, MD, MPA

Objective: To compare rates of cost-related medication underuse and other problems due to medication costs among Department of Veterans Affairs (VA) patients with rates among patients with Medicaid, private health insurance, Medicare, and no insurance coverage.

Study Design: Nationwide survey.

Methods: A total of 4055 chronically ill patients completed an online questionnaire regarding cost-related adherence problems for medications used to treat 16 chronic illnesses. Respondents also reported whether they cut back on necessities due to medication costs, increased their debt burden to pay for prescriptions, and worried about how they would pay for their medications.

Results: Rates of cost-related medication underuse were lower among VA patients (12%) than among patients with Medicaid (25%; P =.0004), Medicare (22%; P =.001), or no insurance (35%; P < .0001). In multivariate analyses, patients with Medicare or no insurance coverage were more likely than VA patients to forego medication at least once per month due to cost (adjusted odds ratios of 3.4 and 3.9; both P ≤ .001). Patients with Medicare or no insurance coverage also were more likely than VA patients to forego basic needs to pay medication costs, borrow money to pay for their treatments, and worry frequently about how they would pay for their medication.

Conclusion: The VA's prescription benefits may prevent problems due to medication costs. Studies assessing the impact of VA prescription coverage on health outcomes and service use will be needed to evaluate the cost-effectiveness of VA drug benefit policies.

(Am J Manag Care. 2004;10(part 2):861-868)

Managed care plans and their patients are struggling with the burden of skyrocketing prescription drug costs. Patients with chronic illnesses often have inadequate prescription coverage,1-3 and many cut back on medication use due to cost pressures.2,4-10 Because medication underuse can lead to increased morbidity, mortality, and preventable acute-care use,10-12 managed care organizations are striving to develop drug coverage programs that are financially viable while ensuring that plan members can afford the treatments they need.

Department of Veterans Affairs (VA) medical centers offer more comprehensive medication coverage than almost any other payer in the United States. Drugs on the VA formulary are 100% covered for patients with low incomes or service-connected disabilities, and other VA patients pay a $7 copayment for a 30-day prescription. VA patients have no cap on the total cost of their covered drugs, and most patients who incur $840 or more in medication costs during a given year have all subsequent copayments waived. Between 1995 and 2001, the number of patients receiving VA outpatient care increased from 2.8 million to 4.1 million, with many of these new patients entering the system to access prescription drug coverage.13-15 In the context of the current debate over prescription drug costs, the VA's drug coverage policy and its impact on patients' use of prescribed medications provide an important model for inquiry.

In a prior study,12 we compared rates of cost-related medication underuse among diabetes patients in 3 VA facilities to rates among patients with private insurance, Medicare, Medicaid, and no health insurance treated in a county and a university health system. We found that VA patients were less likely than patients with any other type of coverage to report medication underuse due to cost. We also found that patients reporting cost-related adherence problems had poorer glycemic control, more symptoms, and worse physical and mental health functioning. These findings suggest that the VA's comprehensive drug benefits may contribute to the better treatment outcomes among chronically ill VA patients compared with Medicare patients.16,17 In our prior study,12 however, all patients were drawn from 5 healthcare systems, 4 or which were located in Northern California. Thus, it remains unclear whether the findings reflect nationwide patterns of adherence among VA and non-VA patients with chronic illnesses.

The problems chronically ill patients face due to medication costs extend beyond their treatment adherence. For example, one recent study found that 21% of Medicare beneficiaries spent less on basic needs to cover the cost of their prescription drugs.4 However, we know little about the extent to which the VA's prescription drug coverage may buffer chronically ill patients from these other consequences of out-of-pocket treatment costs.

Accordingly, we surveyed a nationwide panel of chronically ill older adults about their problems due to out-of-pocket medication costs. We found that rates of cost-related medication underuse were high among individuals with a variety of chronic health problems.9 We also found that more than 22% of patients reported cutting back on spending for basic needs in response to medication cost pressures, and that 16% reported increasing their debt burden to pay medication costs.18 In the current study, we compared rates of cost-related medication underuse as well as other burdens from medication cost pressures among survey respondents using VA care with rates among patients with other forms of health insurance coverage.


Study Participants

The study was based on surveys completed during November and December 2002 by a nationwide panel of adults living in the United States. Details about the panel's sampling approach and recruitment process are available elsewhere.19-21 In brief, panel members were recruited using random digit dialing; the sampling frame consisted of the entire US population with an assigned telephone number. Potential panel members were offered WebTV and free Internet access in exchange for completing Web-based surveys several times per month. At the time of this study, the panel included over 40 000 members.

We used sociodemographic and health status information about panel members to identify all 5644 individuals aged 50 years and older who reported taking prescription medication for diabetes, depression, heart problems, hypertension, or high cholesterol. The sociodemographic characteristics of these respondents were similar to those of Americans aged 50 years and older, as reported in 2000 Census data. For example, the survey and Census populations were similar with regard to the representation of African Americans (8% vs 10%), women (50% vs 54%), married individuals (70% vs 65%), and individuals with household incomes of $20 000 or less (17% vs 23%). Institutional review boards approved the study protocol.

Survey Description and Variable Creation

Respondents were asked about their use and cost-related underuse of prescription medication for each of 16 chronic health problems: arthritis; asthma; chronic back pain or sciatica; diabetes; high cholesterol; chronic obstructive pulmonary disease ("chronic bronchitis, emphysema, or chronic obstructive pulmonary disease"); depression; heartburn, acid reflux, or irritable bowel syndrome; atherosclerosis ("blocked arteries in the heart, angina, or chest pain from heart disease"); heart failure; high blood pressure or hypertension; myocardial infarction ("heart attack"); migraine headache; osteoporosis; stomach or duodenal ulcers; and stroke. On a condition-by-condition basis, participants were asked: "In the past 12 months, have you ever taken less of this medication than prescribed by your doctor because of the cost?" For the current analyses, respondents were coded as having cost-related adherence problems if they reported any medication underuse due to cost for 1 or more of their medications in the prior year.

Respondents reporting cost-related underuse were asked how often they engaged in each of the following behaviors because of the medication cost: taking fewer pills or a smaller dose, not filling a prescription at all, putting off or postponing getting a prescription filled, using herbal medicine or vitamins when feeling sick rather than taking their prescription medication, or taking the medication less frequently than recommended to "stretch out" the time before getting a refill. Participants were coded as foregoing medication at least monthly if they reported any of these behaviors "at least once per month" due to the cost.

Respondents also were asked about 4 other types of problems associated with out-of-pocket medication costs: spending less on basic needs such as food or heat to pay medication costs, borrowing money from family or friends to pay medication costs, increasing credit card debt to pay for medications, and worrying about how to pay for medications at least once per month. See the footnotes to Tables 2, 3, and 4 for the wording of each item.

For the current study, respondents were grouped into mutually exclusive categories using a hierarchy based on their primary source of medical insurance. Patients were assigned to the insurance category that we expected would be associated with the most generous form of prescription drug coverage. Specifically, we identified the following patient groups: VA patients, Medicaid patients who did not use the VA, privately insured patients (without VA use or Medicaid), Medicare patients with no other form of health insurance, and uninsured patients. These categories identify subgroups of patients of particular interest to policymakers (eg, patients with Medicare coverage only) and recognize that individuals often are unable to identify in detail the provisions of their prescription drug coverage.22,23 The sociodemographic variables we examined as possible predictors of problems due to out-of-pocket medication costs included respondents' race, age, sex, educational attainment, and annual household income. We also examined indices of patients' medication cost pressures, including their total number of prescription medications, total monthly out-of-pocket medication costs, and number of chronic health problems.


In initial analyses, we examined bivariate differences in the sociodemographic characteristics and medication cost pressures across groups of patients defined by their primary source of health insurance. We then examined bivariate associations between insurance type and each outcome (medication underuse, foregoing necessities, borrowing from family or friends, increasing credit card debt to pay medication costs, and medication cost worry). Finally, we constructed multivariate logistic regression models to determine the independent effect of insurance type on each outcome, controlling for patients' sociodemographic characteristics (race, sex, age, educational attainment, and income), number of chronic health problems, and number of prescription medications. See Table 1 for the categorization of ordinal and categorical covariates. We included all of the covariates in each regression model although some covariates were not associated with all the outcome variables, both for consistency and because each of the variables has been found to be related to medication adherence problems in prior studies. In all bivariate and multivariate analyses, we used a standard adjustment to interpret the P values associated with the 4 pairwise comparisons between VA patients and patients in the 4 other insurance categories. Thus, a 2-sided P value of .0125 (.05 ÷ 4) was considered equivalent to a nominal P value of .05 in defining statistically significant differences.


Because our hypothesis was that VA prescription benefits would lead to lower rates of medication cost problems by decreasing patients' out-of-pocket costs, out-of-pocket costs were not included as a covariate in our primary multivariate models. Confirmatory analyses included models with out-of-pocket costs as a covariate and fitting models limited to men only (because of the high number of male VA patients). In all analyses, we used sampling weights to adjust the distribution of respondents to match the distribution of the US population on age, sex, race/ethnicity, education, region, and metropolitan residence, thereby correcting for oversampling and survey nonresponse.24,25 The Bureau of Labor Statistics Current Population Survey for October 2002 provided data on the distribution of the US population.26 All analyses were done using Stata 8.1.27


Respondent Characteristics

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