Do Strict Formularies Replicate Failure for Patients With Schizophrenia?
Published Online: March 19, 2014
Dana P. Goldman, PhD; Riad Dirani, PhD; John Fastenau, MPH, RPh; and Ryan M. Conrad, PhD
Between 1995 and 2005, Medicaid spending on drugs increased an average of 13% per year—an increase due in part to physicians favoring newer, more expensive drugs.1,2 To attempt to control costs, many state Medicaid programs responded by imposing policies that encourage the use of lower-cost drugs.2,3 Prior authorization, for example, is designed to reduce pharmacy spending by requiring physicians to seek approval from the state’s Medicaid program before prescribing certain high-cost drugs to patients. These controls are designed to reduce the demand for expensive drugs when lowercost alternatives exist, which ultimately results in reduced Medicaid spending. But these policies may affect healthcare spending and utilization through other channels, especially if patients do not respond well to the preferred drugs. Physicians match patients to the drug and dosage that is optimal for each patient based on various practice guidelines, recommendations, and formulary practices.4,5 On average, several treatments might be equally effective at the population level, but heterogeneous patients will respond differently to each. Removing a drug from coverage could adversely affect those who would have most benefited from it. If the use of these drugs leads to deteriorating health status, the result may be higher nonpharmaceutical medical spending.6
An important example of this trade-off is the second generation of drugs for the treatment of schizophrenia, called atypical antipsychotics, which account for almost 15% of Medicaid spending.7 For this reason, they are increasingly popular targets of state Medicaid formulary restrictions.8,9 Because a number of patients may respond only to 1 drug, formulary restrictions can place patients with idiosyncratic treatment responses at greater risk of uncontrolled symptoms.10,11 Uncontrolled schizophrenia has dramatic costs for patients (about 10% of whom commit suicide), and for society in terms of increased social service use and crime.12 Although lower-cost alternatives to atypicals do exist, they are problematic. The first generation of schizophrenia drugs resulted in improvement of symptoms but with potentially debilitating side effects.10 Atypical antipsychotics were introduced in the 1990s and have largely replaced first-generation treatments because atypicals control schizophrenia better and have fewer negative side effects. For example, about 30% to 40% of patients relapse with first-generation drugs (relative to 80% without treatment), but with second-generation drugs, relapse rates fall to about 25%.10
Formulary restrictions appear to alter doctors’ prescribing behavior. Previous studies have examined the impact of utilization management programs and found that formulary restrictions reduced the use of atypicals by about 5%.9 After prior authorization of atypicals became a requirement in Maine, the risk of discontinuation rose by 29%.2 Studies in Georgia and New Hampshire found that prior authorization reduced the use of targeted drugs and increased the use of other health services.13,14 Previous studies of the impact of restrictions on treatment have focused on individual states. This study, to the best of our knowledge, is the first nationally representative study of formulary restrictions’ impact on treatment. In this study, we examine how formulary restrictions of atypicals affect the likelihood that a patient who has been diagnosed with schizophrenia, and who has had some marker of an unsuccessful response to a particular drug therapy, is continued on that same drug therapy, changes the type of drug, or discontinues all treatment.
Policy information on the restrictions placed on atypical antipsychotics from 1999 to 2005 was collected from 24 state Medicaid programs via a mailed survey and personal communications with policy directors. States reported whether prior authorization, quantity limits, step therapy (fail-first), and other policies applied to a list of drugs identified by US brand name. To supplement this information, additional formulary information was collected using publicly available documents. Regulation data were collected at the individual drug level. The survey included 10 atypicals. All major atypical antipsychotic agents are addressed in the survey, except for paliperidone (brand: Invega) and olanzapine/fluoxetine combined therapy (brand: Symbax), both of which were not yet commercially available during the study period. States reported if each drug was placed under prior authorization, quantity limits, step therapy, dose restriction, or duplicate therapy restrictions in each year.
Medicaid claims for 24 states (12 states that adopted formulary restrictions and 12 states that did not) for a 5-year period (2001-2005) were used to measure medical and pharmacy use at the individual level. We selected the states shown in Table 1 based on the size of the Medicaid population; the fraction of enrollees in fee-for-service Medicaid (with complete claims); and whether the state Medicaid program had imposed restrictions on selected classes of medications over the study period. The years included in this study (2001-2005) captured the widespread introduction and use of prior authorization requirements in many state Medicaid programs, particularly for atypical antipsychotics.
The sample consisted of Medicaid enrollees 18 years and older who have schizophrenia in each of the study states. These patients were identified by (1) the presence of an International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code beginning with 295 in any diagnosis position for inpatient, outpatient, or long-term care claims, and (2) a confirmatory schizophrenia diagnosis at least 30 days after the initial diagnosis. Thus, we eliminated individuals who were diagnosed only once without a subsequent diagnosis. This eliminated individuals with a socalled “rule-out” diagnosis: a physician may make an initial diagnosis of suspected schizophrenia that is later ruled out. The requirement of a subsequent “confirmatory” diagnosis excluded “ruled out” cases from the sample. This criterion also imposed a 30-day minimum window of observation for inclusion in the study. In addition, to be included, a patient must have filled at least 1 prescription for one of the drugs included in our sample. In practice, this restriction eliminated very few patients because those with a subsequent confirmatory diagnosis are almost always given a prescription.
The Figure presents a consort diagram for the sample construction: 944,609 patients over the age of 18 years who have had at least 1 schizophrenia diagnosis. Of these, about 77% had a confirmatory diagnosis after 30 days. Of the remaining population, 63%, or 460,991 patients, were prescribed an atypical.
To estimate the impact of prior authorization on treatment failure and “replication of failure,” a difference-in-differences method (DD) was used. In the DD method, 2 groups—patients in states with restrictions and patients in states without restrictions— were observed in 2 different time periods: 2001 and 2005. Patients living in states that adopted formulary restrictions after 2001 were, in the terminology of DD models, exposed to “treatment” in 2005, while those in nonformulary states were not exposed in either period. This method first calculates the change in the average likelihood of the outcome variable in the treated group, and then calculates the corresponding change in the nontreated group. The excess change in the treated group, above and beyond the change in the nontreated group, represents the estimated DD effect. For example, in states with formulary restrictions, we calculated the change in the likelihood of a patient resuming the same medication after a 30-day gap before and after the implementation of the restriction. We then compared this with the corresponding difference in likelihood within states that never adopted restrictions. The approach removes the effects of trends due, for example, to general changes in atypical use between 2001 and 2005. Because formulary restrictions were measured at the state level, we clustered the standard errors at the state level. We utilized an alpha of 0.10, although the tables included alternative alpha values.
To examine the replication of failure, all patients currently with schizophrenia who are taking an atypical antipsychotic for their condition were identified. Then, patients were classified as failing on a particular therapy if they either were admitted to a hospital for their disease or had a medication gap greater than 30 days (in a baseline year). Patients who failed treatment were followed over time, and their claims were examined for resumption of treatment with the same drug after at least a 30-day gap. As a robustness check, we examined longer gaps, but faced serious sample size limitations due to the limited number of people observed restarting after longer gaps. Finally, we also examined whether individuals on an atypical discontinued drug therapy altogether, switched from an atypical to a typical (first generation) antipsychotic, or switced from one atypical to another.
We included an indicator variable equal to 1 in the year 2005 and an indicator for states that adopt formulary restrictions. The interaction between the 2 indicators, year 2005 and formulary restrictions, is the difference-in-differences estimate discussed above (labeled DD in the tables).
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