Gaps in Drug Benefits: Impact on Utilization and Spending for Drugs Used by Medicare Beneficiaries with Serious Mental Illness

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Gaps in Drug Benefits Impact on Utilization and
Spending for Drugs Used by Medicare Beneficiaries
with Serious Mental Illness

• Linda Simoni-Wastila, PhD
• (lsimoniw_at_rx.umaryland.edu)
• Christopher Blanchette, MA
• Xiaoqang Ren, MS
• Bruce Stuart, PhD
• Peter Lamy Center on Drug Therapy and Aging
• University of Maryland Baltimore
• School of Pharmacy
• AcademyHealth
• Boston, MA
• June 28, 2005

Funded by the Robert Wood Johnson
Foundation/Health Care and Financing Organization
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Background

• There are growing concerns that the MMA Part D
  benefits donut hole design may result in
  discontinuities in access to prescribed medicines
• Such coverage gaps may be particularly
  detrimental to older and disabled individuals
  with chronic conditions for whom prescription
  drugs represent a necessary treatment modality

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Background

• Prior work found that drug coverage gaps reduced
  prescription drug use by Medicare beneficiaries.
  Using a simulation model, we projected total drug
  spending under Medicare Part D relative to those
  with continuous coverage
• All MC Beneficiaries 92.1
• COPD 79.6
• Diabetes 83.2
• Mental Illness 76.0

(Stuart, Simoni-Wastila and Chauncey Health
Affairs web exclusive 2005)
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Purpose

• To delve into greater detail on how drug coverage
  gaps impact drug use and spending by Medicare
  beneficiaries with serious mental illness (SMI)
• Objectives
• 1) To describe extent of drug coverage gaps
  experienced by SMI Medicare beneficiaries and
• 2) To determine impact of coverage gaps on use of
  and spending for prescription drugs used to treat
  mental disorders

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Methods - Data

• 1997 2001 Medicare Current Beneficiary Survey
  (MCBS) linked to Medicare Part A and Part B
  claims
• MCBS is longitudinal, nationally-representative
  sample of Medicare beneficiaries
• MCBS (linked to Part A and B claims) contains
• Demographics
• Income and health insurance coverage, including
  drug benefits (with begin and end dates of
  coverage)
• Health and functional status
• Utilization and expenditures for all health
  services, including prescription drugs
• Diagnostic information (ICD-9 diagnoses from
  claims self-report from MCBS survey)

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Methods Study Sample

• Pooled sample of three 3-year cohorts (1997-1999,
  1998-2000, and 1999-2001) of community-dwelling
  MCBS respondents
• Excluded from analysis M C plan members, LTC
  residents, and those lost to follow-up ? Sample
  9,219

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Methods Study Sample

• SMI defined as 1 or more SMI diagnoses in
  baseline year at least one other of same
  diagnosis during any of study years
• SMI diagnoses include
• Schizophrenia/psychotic disorders (ICD-9
  294.xx, 295.xx, 297.xx, 298.xx, and 299.xx)
• Manic/Bipolar disorders (ICD-9 296.0, 296.1,
  296.4-296.9)
• Major depression (ICD- 9 296.2, 296.3)
• Application of these criteria resulted in an
  analytic sample of 901 seriously mentally-ill
  Medicare beneficiaries followed for up to 3 years

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Methods Dependent Variables

• Mental health drug use and spending
• Use defined as all Prescription Medication Events
  (PME) per respondent over three year period
• use, annual mean PMEs
• Expenditures defined as all mental health drug
  spending per respondent over three period,
  expressed in constant 2001 dollars (and
  annualized)
• Total mental health drug use and spending, as
  well as by therapeutic class
• Antipsychotics (atypicals, typicals)
• Antidepressants (newer, traditional)
• Anxiolytics/Sedative-hypnotics
• Anti-mania drugs
• Anticonvulsants (mood-stabilizers)

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Methods Independent Variables

• Prescription gap months summed number of months
  over the three-year period during which the
  beneficiary had no evidence of prescription drug
  coverage
• 0 Gap Months (Full drug coverage) ref
• 1-18 Gap Months
• 19-35 Gap Months
• 36 Gap Months (No drug coverage)

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Methods - Covariates

• Age (lt65, 65-74, 75-84, 85 ref)
• Gender Female is ref
• Race/ethnicity Non-white is ref
• Education ltHS is ref
• Income FPL gt 300 is ref
• Non-drug supplemental insurance (0/1)
• Geographic region West is ref
• Urbanicity Rural is ref
• Health Status Poor is ref
• Death status (0/1 indicator of died in year 1, 2
  or 3)
• Psychosis or depression (0/1 indicator of
  condition)
• Comorbidity Index (DCG/HCC)

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Methods Analytic Approach

• Descriptive Mental health drug use and spending,
  overall and by gap status
• Multivariate Ordinary least squares regression
  to estimate the impact of gap status on mental
  health drug use and spending
• Tested for endogeneity of the coverage variables
  and found that controlling for comorbidity
  (HCC/DCG) eliminated all endogeneity
• All analyses weighted ? nationally representative
  estimates

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Results Baseline Characteristics
Percent of SMI Beneficiaries
Age lt 65 34.1
Female 61.7
White 82.0
100 FPL 31.0
Fair/Poor Health 44.8
Mental Health Problems Major Depression Psychotic Disorders/Bipolar Non-SMI MH conditions 52.8 55.0 67.3
Died Year 1 Year 2 Year 3 4.3 5.2 6.2
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Annual Mean Total and MH Drug Spending by MC
Beneficiaries (unadjusted)
34.0
10.7
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Drug Coverage Gaps Among MC Beneficiaries with
SMI (unadjusted)
Prescription Coverage Gaps in Months of MC Beneficiaries with SMI Mean Annual PME Fills by SMI MC Beneficiaries
0 (Full drug coverage) 51.4 11.2
1-18 Months 18.7 9.6
19-35 Months 11.5 6.3
36 Months (No coverage) 18.4 6.0
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Proportion of SMI MC Beneficiaries Using Any MH
Drugs, Antidepressants and Antipsychotics by
Coverage Gap Status (unadjusted)
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Regression Results

• The next several slides illustrate the impact of
  having coverage gaps on utilization of and
  spending on
• All mental health drugs
• Antidepressants
• Antipsychotics
• ceteris paribus
• All findings are presented as mean annual
  prescriptions or expenditures

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Annual Mean PMEs (Fills) by Coverage Gap Status
(adjusted)
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Annual Mean Drug Spending by Coverage Gap Status
(adjusted)
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Other Multivariate Findings

• Age is important individuals aged lt65 (i.e.,
  the disabled) had significantly increased use and
  spending of all MH drugs and drug classes
  relative to those aged 85
• Sex, race/ethnicity, income, health status, and
  other covariates varied by therapeutic class
• Comorbidity, as assessed using the DCG/HCC, was
  not a significant predictor of MH drug use or
  spending however, the individual diagnoses of
  depression and psychotic disorders were
  significant positive predictors of drug use and
  spending

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Other Multivariate Findings

• In within therapeutic class analyses (not shown
  here), we found that coverage gaps did not
  influence use of and spending on the newer mental
  health drugs, such as the atypical antipsychotics
  or SSRI/SNRIs, suggesting that coverage status
  may not influence type of drug one receives
• However, when we examined the probability of
  receiving any newer MH drug (ie, any SSRI/SRNI
  or atypical), we found that among any
  antidepressant/ antipsychotic users, newer drug
  use and spending was less likely among those with
  gaps or no coverage relative to those with full
  coverage

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Conclusions and Next Steps

• It is clear that coverage gaps make a difference
  in terms of access to medications used to treat
  Medicare beneficiaries with serious mental
  illness, controlling for comorbidity and other
  important covariates
• Next Steps
• Examine variation in use of and spending for
  other MH therapeutic categories (e.g., mood
  stabilizers anxiolytics newer MH drugs)
• Examine how use and spending differ by age (i.e.,
  eligibility based on disability versus age)
• Answer the question Do differences in mental
  health drug use due to coverage gaps impact the
  use of and spending on other medical services,
  including hospitalization, emergency department
  visits, and psychiatric treatment?