Evidence-Based Practices for Medicaid Beneficiaries with Schizophrenia and Bipolar Disorder. State Variation in Receipt of Evidence-based Practices


Differences between states in the receipt of EBPs could be attributable to underlying differences in the demographic characteristics of state Medicaid populations, differences in structures or orientation of service systems, or specific Medicaid policies and practices that could limit reimbursement of a particular EBP. In this chapter, we describe state-to-state variation in the receipt of EBPs. We used descriptive and multivariate statistics to identify the features of state mental health service systems and Medicaid programs associated with this variation, and the likelihood that an individual beneficiary received services.

Our analysis of state Medicaid program or mental health system characteristics focused on state features that could be directly measured using MAX data or reliably constructed using secondary data sources. Thus, we focused on three main state features: (1) enrollment in managed care, (2) Medicaid prescription drug (RX) policies, and (3) funding for community-based mental health services. Table 4 summarizes the features of states and the size of the study population affected by a particular state feature.

Managed Care. Enrollment in managed care was measured directly using MAX data. As shown in Table 4, 13 percent of the study population located in three states was enrolled in an HMO for part or all of the year. Over 60 percent of beneficiaries in our study who were enrolled in an HMO lived in California, 37 percent lived in Maryland, and 2 percent lived in Indiana. Eight percent of the study population was enrolled in another form of managed care, such as a behavioral health organization (BHO), prepaid IP hospital plan, or primary care case management (PCCM) program. However, in these states, nearly the entire study population was enrolled in managed care, preventing an in-state comparison of managed care enrollees to beneficiaries in the FFS system. In sum, a relatively small proportion of the study population was enrolled in managed care in a few states, so readers should be cautious when drawing conclusions about managed care. The findings may differ if the data included a larger population of beneficiaries enrolled in managed care across many states.

Medicaid RX Policies. Medicaid RX policies were measured using data from the National Pharmaceutical Council. These policies included the state’s use of prior authorization policies for antipsychotics, anticonvulsants, or antidepressants; limits on medication quantity supplies and refills; and copayment requirements for RXs. Most beneficiaries lived in a state without prior authorization requirements or restrictive medication supply or refill limits (Table 4). Nearly one-quarter of the study population (24 percent) lived in a state with a three-dollar copayment for preferred or generic drugs, while 49 percent of the population lived in a state with a three-dollar copayment for nonpreferred or branded medications.

TABLE 4. State Policies by Number of States and Beneficiaries

State Policy or Characteristic

  Number of States with  Policy or Characteristics

  Beneficiaries with Schizophrenia or  Bipolar Disorder Affected byPolicy or Characteristic



SOURCES: The National Pharmaceutical Council, for Medicaid medication management and copayment information. National Research Institute (NRI), for data on the proportion of SMHA funding used for community-based services. MAX provided managed care enrollment data for each beneficiary.
Total 22 143,710 100
Managed Care Arrangements
   No managed care (FFS system) 16 113,761 79
   Enrolled in HMO 3 18,243 13
   Enrolled in BHO 1 2,164 2
   Enrolled in PCCM 1 4,023 3
   Enrolled in prepaid IP hospital program   1 5,519 4
Prior Authorization for Mental Health Medications
   No prior authorization required 14 113,111 79
   Required for antipsychotics 4 13,513 9
   Required for antidepressants 8 30,599 21
   Required for anticonvulsants 3 5,989 4
   Monthly Medication Supply Limit
   Limited to 31 days or less 5 16,776 12
   Supply limit greater than 31 days 17 126,934 88
Limit on Refills per Prescription
   Six or fewer 2 9,763 7
   More than six 20 133,947 93
Beneficiary Copayment for Generic or Preferred Medications
   None 6 24,761 17
   $0.50-$1 7 71,137 50
   $2 3 13,478 9
   $3 6 34,334 24
Beneficiary Copayment for Branded or Nonpreferred Medications
   None 3 6,721 5
   $1 2 52,413 36
   $2 4 14,132 10
   $3 13 70,444 49
Proportion of SMHA Funding Used for Community-Based Services
   0-25% 0 0 0
   26-50% 4 19,610 14
   51-75% 14 62,403 43
   76-100% 4 61,697 43

Funding for Community-Based Mental Health Services. The orientation of the state mental health system toward community-based versus institutional or hospital-based services (as indicated by financing levels), as well as the relationship between Medicaid and SMHAs, was measured using data from a 2007 survey of state mental health directors conducted by the National Association of State Mental Health Program Directors, NRI. As shown in Table 4, 43 percent of beneficiaries in the study lived in one of the four states where more than three-quarters of state mental health system funding was used to provide community-based services.

There are several features of states that could influence the receipt of EBPs but for which we did not have a reliable or authoritative source in 2007. These features include detailed information on the type and scope of mental health benefits covered for adults in each state, limitations on the number or duration of mental health services, and the qualifications required for individuals or organizations to enroll in the program as mental health providers. While information is available on whether states covered certain mental health services in 2007, in general it tended to lack sufficient detail to allow for adequate differentiation between states in the generosity and accessibility of their mental health benefit. Finally, the characteristics of Medicaid providers could not be measured using MAX data. These unmeasured variables could confound the findings and thus these findings should be interpreted cautiously.

We conducted state-level analyses to examine the relationship between certain state features and the proportion of beneficiaries who received an EBP. When there was sufficient variation and reliably collected explanatory variables, we conducted person-level random effects multivariate analyses to further examine whether any beneficiary, SMHA, or Medicaid program characteristics were associated with the receipt of EBPs.

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