Formulary Restrictions on Atypical Antipsychotics: Impact on Costs for Patients With Schizophrenia and Bipolar Disorder in Medicaid
Published Online: February 24, 2014
Seth A. Seabury, PhD; Dana P. Goldman, PhD; Iftekhar Kalsekar, PhD; John J. Sheehan, PhD; Kimberly Laubmeier, PhD; and Darius N. Lakdawalla, PhD
In an effort to contain rising expenditures on prescription drugs, state Medicaid programs around the United States have increasingly adopted formulary restrictions designed to restrict access to specified high-cost medications.1-5 Second-generation antipsychotics (SGAs), or “atypical” antipsychotics, have been among the most frequently targeted class of drugs.6 Since the first atypical antipsychotics were introduced in the 1990s, they have increasingly replaced first-generation or “typical” antipsychotics and in 2005 accounted for over 15% of all Medicaid spending on pharmaceuticals.7 Their high cost and rapid growth within Medicaid made them natural targets for cost containment. More than one-third of state Medicaid programs and Medicare Part D (MPD) prescription drug plans now require prior authorization or some other restriction for at least 1 atypical antipsychotic.1,2,8 Formulary restrictions on atypical antipsychotics are controversial because they affect patients with severe chronic mental illness, including schizophrenia and bipolar disorder. While these conditions are relatively uncommon in the general population—schizophrenia affects about 1.1% of people in the United States9 while bipolar disorder affects about 2.6%10—they are more common in the Medicaid population. Estimates suggest that the prevalence of diagnosed schizophrenia in the Medicaid population is approximately 1.7%, and it is estimated that over 30% of individuals with schizophrenia are Medicaid beneficiaries.11 Formulary restrictions influence clinical decisions about the type of atypical antipsychotic that a patient receives, but it is known that the efficacy and tolerability of these agents varies substantially from one patient to another.8 This heterogeneity across different treatments means that providers and patients sometimes need to try different treatment regimens to attain desired clinical outcomes, and restricting access to some medications can lead to possible noncompliance with therapy or treatment non-response.
Given the vulnerable nature of these patients, there is concern that such disruption could have adverse consequences. For example, one study of medication nonadherence for individuals with schizophrenia found a 50% increase in the risk of a mental health hospitalization in the first 10 days following a missed prescription refill.12 Other studies have found that adherence to atypical antipsychotics fell3 or that healthcare costs rose.13,14 There is some evidence of a small decrease in pharmacy expenditures associated with formulary restrictions for patients with bipolar disorder, but this was also associated with an increase in treatment discontinuation.5,15
While informative, these studies are limited in that each focuses on only small groups of states (usually 1). More work on a larger number of states with a more diverse set of policy changes is needed to understand the impact of formulary restrictions on health outcomes and medical costs for patients with severe mental illness.6,16 Moreover, while Medicaid expenditures are an important metric of social costs, there are others. Disruptions in antipsychotic therapy could lead to more acute psychotic episodes by affected patients. This can lead to public unrest or even violence, which can be reflected as an uptick in incarceration rates among the mentally ill, driving up the burden of mental illness on society.17
This study examines the relationship between formulary restrictions and healthcare utilization and expenditures for patients with schizophrenia and bipolar disorder from 24 state Medicaid programs. We combined information on formulary restrictions for atypical antipsychotics in these states with data on all of the medical and pharmacy claims in Medicaid for patients with schizophrenia and bipolar disorder from 2001 to 2008. We combined our estimates of formulary restriction effects on healthcare costs with evidence of their effect on incarceration costs. This provides a more complete accounting of the potential unintended consequences of trying to contain costs by restricting access to the full range of therapies for mental illness.
We used claim-level data on inpatient, outpatient, longterm care, and pharmacy claims from the Medicaid Analytic eXtract (MAX) files. Our data included all patients diagnosed with schizophrenia or bipolar disorder from 24 states from 2001 to 2008. (The states are: Alabama, Arkansas, California, Florida, Idaho, Illinois, Indiana, Kentucky, Louisiana, Massachusetts, Maryland, Minnesota, Mississippi, North Carolina, New Jersey, New Mexico, New York, Ohio, Pennsylvania, South Carolina, Texas, Virginia, Wisconsin, and West Virginia. We did not receive 2008 data for Pennsylvania or Wisconsin because they were unavailable at the time of data extraction.) We selected these because other states often deliver services to Medicaid beneficiaries through the use of managed care, and there are issues related to the availability and reliability of claims data for enrollees in Medicaid-funded managed care plans.
The study sample includes all working-age adult enrollees (aged 18-64 years) diagnosed with schizophrenia or bipolar disorder who were first prescribed an atypical antipsychotic (olanzapine, risperidone, quetiapine, aripiprazole, or ziprasidone) during the study period (N = 375,934). We restricted the study sample to patients newly prescribed an atypical antipsychotic, because these patients were more likely to be newly treated for their condition, and thus were most likely to be affected by formulary restrictions. An index date was identified using the start date of the first filled prescription for the first atypical prescribed. We tracked all medical and pharmacy claims 6 months before and 12 months after the index date. Patients with schizophrenia were identified based on medical claims with primary or secondary International Classification of Diseases, Ninth Edition (ICD-9) diagnosis codes of ICD-9-CM 295.x during the study period (2001-2008).
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