Medicaid Prior Authorization Policies and Imprisonment Among Patients With Schizophrenia
Published Online: July 21, 2014
Dana Goldman, PhD; John Fastenau, MPH, RPh; Riad Dirani, PhD; Eric Helland, PhD; Geoff Joyce, PhD; Ryan Conrad, PhD; and Darius Lakdawalla, PhD
Increasingly, public and private healthcare plans are imposing prior authorization requirements to manage drug spending. Prior authorization plans establish a preferred drugs list (PDL) and require authorization before covering drugs not on the PDL. Such programs are designed to reduce costs by steering utilization toward lower-cost medications, but these policies may also lead to poorer drug adherence.1 Poor adherence to or discontinuation of antipsychotic drugs among patients with schizophrenia is likely to cause acute psychotic episodes2-4 and often results in contact with law enforcement officers due to threatening behaviors brought on by active symptoms, leading to arrest and incarceration.5
While schizophrenia affects only about 1% of the US population,6 it is difficult and expensive to treat and can have a devastating impact if not well controlled.7 The effects of losing continuous effective exposure to medication due to nonadherence are immediate and evident. A study on the temporal relationship between medication nonadherence and hospitalization risk for individuals with schizophrenia found that individuals in the first 10 days following a missed prescription refill had a greater than 50% increase in the risk of mental health hospitalization and a 77% increase in the risk of schizophrenia-specific hospitalization.8
As a result of their behavior, mentally ill people are more likely to be arrested than other people who are stopped by police, and more likely to be subsequently convicted and incarcerated.9 Enforcement officials may not be sufficiently trained to recognize mentally ill patients, or they may feel obliged to bring the schizophrenic offender to the criminal justice system when the healthcare system is unwilling or unable to accept a violent patient. Prison systems are often poorly equipped to treat the mentally ill, and, when released these prisoners are more likely to recidivate,10 which promotes the vicious cycle of mentally ill criminals entering the criminal justice system, suffering further mental health deterioration in prison, and upon release ending up with a significant likelihood of re-arrest due to poorly controlled mental illness.
Evidence also shows that the mentally ill are more costly to incarcerate than those without mental illness and that other types of rehabilitation for the mentally ill may reduce crime at costs lower than those associated with incarceration.11 Over the past several decades, pharmaceutical advancements in the treatment of schizophrenia have been shown to reduce the likelihood of episodes that start the sequence of events leading to incarceration of patients. The second-generation antipsychotics known as atypicals were introduced in the 1990s. These have largely replaced older antipsychotics, because they are associated with lower rates of relapse. About 30% to 40% of patients relapsed with first-generation drugs (relative to 80% without treatment); for second-generation drugs, relapse rates fell to about 25% to 29%.12-14 Furthermore, many patients respond to only 1 drug, so that increased treatment options increase the likelihood of successful treatment.15 The lower rates of relapse seen with atypicals may lead to fewer incidents with law enforcement and reduced incarceration of schizophrenia patients.
The evidence suggests that atypicals improve outcomes for certain patients with schizophrenia. The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study found that perphenazine (Trilafon), an older typical, worked about as well as several newer atypicals for the average patient in the trial.16,17 Subsequent research on the CATIE data clarified that a subset of patients in CATIE strictly benefited from atypical usage, and that providing typicals to all patients would have reduced overall health.18 Taken together, this literature suggests that atypicals represent a valuable treatment option for some patients with schizophrenia.
In this study, we examine the association between Medicaid policy and 2 key outcomes-—namely, utilization of antipsychotics and imprisonment of patients with schizophrenia. We compared the prevalence of patients in prison among states that did or did not institute prior authorization programs for atypical antipsychotics. We also compared prevalence across states that have different levels of atypical antipsychotic utilization. Because of the association between prior authorization regulations and increased risk of discontinuing atypical treatment, and because of the potential link between untreated schizophrenia and incarceration, we hypothesized that prior authorization rules will increase the likelihood that a schizophrenia patient is incarcerated.
Ideally, we would like to have measured the percentage of each state’s population with schizophrenia that is incarcerated, and then examined how this percentage is associated with state prior authorization policy. In practice, we were able to obtain only the percentage of the incarcerated population who were diagnosed as having schizophrenia in each state. If it is assumed that Medicaid pharmacy regulations have no impact on the overall prevalence of schizophrenia in a state, and that they have negligible impact on the rate at which nonschizophrenics are imprisoned, then the impact of pharmacy regulations on the prevalence of schizophrenia in prisons will be comparable with the impact of these regulations on the rate of imprisonment of patients with schizophrenia.
A simplified summary of the underlying process illustrates how restrictive pharmacy policies in Medicaid might lead to a higher prevalence of schizophrenia in prison:
Stage 1: A large majority of patients with schizophrenia are covered by Medicaid.
Stage 2: The state’s restrictive prior authorization policy leads to discontinued, reduced, or inappropriate medication.
Stage 3: Suboptimal medication leads to uncontrolled symptoms.
Stage 4: Active symptoms or deteriorated economic conditions that result from uncontrolled symptoms lead to encounters with law enforcement and arrest.
Stage 5: Repeated or serious arrests lead to imprisonment.
Our hypothesis is that Medicaid prior authorization regulations limit access to atypicals, and that this increases the likelihood that a patient will progress down the list from stage 2 to stage 5.
Our analysis made use of the 2004 Survey of Inmates in State Correctional Facilities (SISCF) and the 2004 Survey of Inmates in Federal Correctional Facilities (SIFCF) conducted for the Bureau of Justice Statistics by the Bureau of the Census; these surveys have been used in previous research.19 They provide nationally representative data on inmates held in state and federal prisons obtained through personal interviews of more than 18,000 inmates in about 300 prisons. These data contain individual-level information on inmates’ mental health conditions and various personal characteristics. A benefit of the SISCF data is that they also contain state indicators, which allow us to match the data to our original survey of antipsychotic coverage.
Using a mailed survey that was conducted in 2009, we collected information from 30 state Medicaid programs on their utilization review policies for atypical antipsychotics over the period 1999 to 2008.20 This survey asked whether prior authorization policies applied to a list of drugs identified by US brand name. To supplement the survey information, we examined Medicaid pharmacy program websites for relevant documents and contacted Medicaid program personnel. This allowed us to identify the 4 states (AK, CA, MA, and NY) that had prior authorization for all atypicals before 2003, along with 24 states that we can determine had no prior authorization before the 2004 SISCF survey. For the remaining states, we are unable to determine the prior authorization policy in 2003, because information on the timing of prior authorization implementation is unclear or unavailable from the mailed survey or websites. (See Appendix A for a list of states by policy status.)
State-level utilization data were obtained from the State Drug Utilization Data Files available from CMS. These data, which include the number of prescriptions filled for each drug by each state Medicaid program by calendar quarter, were obtained for 2003 atypical antipsychotics. State-level Medicaid enrollments as of June of each year were obtained from the Kaiser Family Foundation’s State Health Facts database.
Prevalence in the General Population
We used prevalence of serious psychological distress (SPD) estimated from the 2003-2004 National Surveys on Drug Use and Health, produced by the Substance Abuse and Mental Health Services Administration (SAMHSA), as a proxy for the prevalence of schizophrenia in the general population. Serious psychological distress was measured using the K6 screening instrument for nonspecific psychological distress. In 2003-2004, SPD was noted in about 10% of the population 18 years or older. If we can assume that the percentage of schizophrenia in SPD does not vary by status of prior authorization or level of atypical utilization, then such an approximation does not affect interpretation of our results.
We estimated the probability that an inmate is screened as positive for psychotic symptoms, and whether an inmate reports a prior schizophrenia diagnosis, using a linear probability model. In addition to an indicator variable that equals 1 if the state in which the inmate is incarcerated has a prior authorization rule for atypical antipsychotics, we included the prevalence of schizophrenia in the general population in the state and several individual inmate characteristics found in Table 1.
As documented in Table 1, the probability that a prisoner was previously diagnosed with schizophrenia is relatively low, and this suggests the linear probability modeling approach. Logistic regression is known to perform poorly in binary dependent variable models where positive outcomes are statistically rare; in contrast, linear probability model performance is invariant to the mean of the dependent variable.21 In any event, however, the association between prior authorization (or atypical usage) and the prevalence of mental illness within prisons is robust and statistically significant across linear probability, logistic regression, and probit models. Therefore, our results are not primarily dependent on functional form. All our modeling results are presented for the logistic regression model in eAppendix Tables 1 and 2. The results are qualitatively similar.
The outcome variable is an indicator of whether an inmate has screened positive for psychotic symptoms. We utilize 2 questions from the survey. In the first, the survey asked inmates whether during the past year they had seen or heard things that other people said were not there, felt that other people were able to read or control their mind, or felt that someone other than the corrections staff had been spying on or plotting against the inmate. Inmates who answered yes to any of these questions were screened as positive for psychotic symptoms in our analysis. This question measures the presence of psychotic symptoms. Note that it is broader than schizophrenia. Our second measure focuses on a much narrower definition, based on a question that asks the inmate if they have ever been diagnosed by a healthcare provider with schizophrenia or a psychotic disorder. This definition will undercount those inmates who are unwilling or unable to identify themselves as schizophrenic but has the advantage of not resulting from self-diagnosis. As shown in Table 1, 2840 inmates screened positive using the more inclusive definition while 775 reported a prior diagnosis. Significantly, all those with a prior diagnosis also tested positive for the presence of psychotic symptoms.
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