Medicaid Pharmacy Cost-Containment Policy Actions and Access to Prescription Drugs and Medical

Medicaid is the largest public health insurance program in the United States, financed by state governments and federal matching funds. It ranks as the second largest source of state spending.¹ The Medicaid program provides health care coverage for almost 60 million eligible Americans who have a low income, are disabled, or are elderly.²

With the economic downturn in 2001, state revenues and budgets declined, leading to substantive bud-get deficits. As unemployment rates rose, more people became eligible for the Medicaid program.³ As a result, total Medicaid spending skyrocketed from $166 billion in fiscal year 1997 to $258 billion in 2002, a 55% increase.⁴ Because of the combined effects of decreasing revenues, increasing number of enrollments, and skyrocketing Medicaid spending, the states were forced to implement Medicaid cost-containment policy actions to restrain expenditures and lower the enrollment growth rate.

Between 1998 and 2002, pharmacy spending had the highest average annual growth at about 19% of Medicaid expenditures.⁵ Pharmacy spending was the fourth largest Medicaid expenditure in 2003, after hospital care, nursing home care, and other personal health care expenditures.⁶ Studies have found that Medicaid pharmacy cost-containment policy actions reduced the unnecessary use of and spending on particular drugs.^7-13 However, several studies demonstrated that these policy actions also affected the well-being of Medicaid enrollees, especially in terms of accessibility to medication and prescription drugs. These problems were more likely to increase when more policies were implemented.^14,15

Among all policy actions, prior authorization requirement was found to have a significant effect on Medicaid beneficiaries, particularly with regard to drug access and delays in obtaining prescription drugs. A mandatory generic requirement (generic substitute) was also found to have a negative effect on access to drugs.¹⁶ However, most of the previous studies focused on one policy at a time and did not control for others, including other pharmacy cost-containment policy actions and nonpharmacy cost-containment policy actions. Socio-environmental factors such as state characteristics were often not controlled for. As a result, the findings in those studies may be confounded and thus biased.

We proposed to evaluate the impact of pharmacy cost-containment policy actions on access to prescription drugs and medical care, controlling for nonpharmacy cost-containment and socio-environmental variables. We used a data set from the Community Tracking Study (CTS) for a sample of 25,988 adults, aged 18 or older, implementing a logistic regression analytic technique to ascertain the effects of pharmacy cost-containment policy actions.

Method
The data used in this study were obtained from the 2003 CTS Household Survey, which is a periodic nationally representative household survey.¹⁷ The samples were randomly selected from 60 communities across the United States, and the data collected in the surveys included health care access, satisfaction, use of services, and insurance coverage. Information on the sociodemographic, employment, and health status of the respondents was also included in the database.

We linked the CTS data with the cost-containment policy actions that were based on “Medicaid Outpatient Prescription Drug Benefits: Findings from a National Survey, 2003” and “States Respond to Fiscal Pressure: A 50-State Update of State Medicaid Spending Growth and Cost Containment Actions,” which were surveys conducted by the Kaiser Family Foundation in 2003.^18,19 The data were further linked with the census demographic data at the state level to obtain information such as poverty level, unemployment, racial composition, and proportion of elderly in the states.

We excluded 19,699 respondents (43%) in the CTS who were younger than 18 years. We also excluded respondents from the states (15) that did not have pharmacy cost-containment policy actions in the Kaiser reports. We further excluded respondents from the District of Columbia, because of the small sample size. This resulted in a total of 28 states available for study.

A cross-sectional study design was developed to evaluate the impact of policy actions by comparing the cost-related underuse of medicine (CRUM) between recipients who were Medicaid cost-containment policy action–eligible and those who were noneligible. Thus, the intervention group consisted of Medicaid beneficiaries with specific policy actions implemented in their states and the control group was composed of Medicaid beneficiaries without specific policy actions implemented in their states and non-Medicaid enrollees with comparable age profiles.

Overall, all Medicaid beneficiaries in the intervention group had at least 2 pharmacy cost-containment policy actions implemented in 2003. Comparing health care across insurance status has been an important subject in health services research. One study recently compared Medicaid enrollees with persons who had other types of insurance in terms of their access to care in the context of Medicaid cost-containment policy actions.¹⁵

The measures of access to prescription and medical care include the following: do not receive need- ed medical care, cannot afford needed prescriptions, postpone needed medical care, and worry about medical care costs. In the CTS survey, the following questions were asked: during the past 12 months, (1) was there any time when you didn’t get the medical care you needed? (2) was there any time you needed prescription medicines but didn’t get them? and (3) was there any time when you put off or postponed getting medical care you thought you needed because you couldn’t afford it?

Each of these outcomes was analyzed as a binary outcome using a logistic regression analysis model. The main predictors in the model included the following 9 prevailing pharmacy cost-containment policy actions: prior authorization, mandatory generics required, copayment method, step therapy or fail-first requirement, limit on number of prescriptions and number of refills per month, preferred drug list, OTC coverage, payment method, and purchasing method.

These pharmacy cost-containment policy actions were used as a summary measure by counting the total number of actions in each state. This summary measure served as the main predictor in our model, which controlled for 8 nonpharma-cy cost-containment policy actions, which were provider payment method, benefit reduction, eligibility cuts, beneficiary copayment, managed care expansion, disease and case management, fraud and abuse, and long-term–care reduction.

Provider payment methods refer to the policy action of cutting or freezing the provider payment rates. Lowering the provider payments would negatively affect providers’ availability to accept these patients, and as a result, as recent research has suggested, patients would have increased difficulty in finding a provider and obtaining timely appointments.²⁰ Managed care expansion has been shown to be associated with reduction of choices of providers. Disease and case management was targeted at high-cost cases, such as those associated with diabetes, asthma, and heart disease. While it was aimed at improving the efficiency of treatments, it was also used to combat fraud and abuse. Long-term care is highly expensive and consumes much of households’ savings; thus, reduction of payment for long-term care would likely strain the budgets of beneficiaries and spill over into affordability of all types of medical care. We believe all those nonpharmacy policy actions have broad implications for access to care by low-income Medicaid beneficiaries.

In addition, patients’ demographic and states’ socio-environmental variables were controlled for, including age, sex, race, educational attainment, family size, household income, body mass index, health status, fraction of minority, fraction of elderly, fraction of women, average individual income, poverty rate, home-ownership rate, state population, and electoral votes in 2000. We conducted separate analyses by examining the effects of pharmacy cost-containment policy actions and nonpharmacy cost-containment policy actions individually and concurrently. All the analyses were weighted to represent the sampling and national population.

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