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Assessing and Addressing Antipsychotic Utilization Among Medicaid Youth: A Researcher-State Policymaker Collaboration

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Title: Assessing and Addressing Antipsychotic Utilization Among Medicaid Youth: A Researcher-State Policymaker Collaboration


1
Assessing and Addressing AntipsychoticUtiliz
ation Among Medicaid YouthA Researcher-State
Policymaker Collaboration
  • Stephen Crystal
  • Center for Education and Research on Mental
    Health Therapeutics
  • Rutgers University
  • Presentation for Session on Collaboration Between
    Researchers and State Policymakers A Model for
    Healthcare Improvement
  • AHRQ Annual Meeting
  • September, 2009

2
AP Use in Medicaid Youth Clinical and Policy
Challenge
  • Increased use of atypical antipsychotic (AAP)
    medications for a broadened range of patients and
    indications, often off-label, has raised a range
    of policy challenges for payers, patients and
    clinicians (Crystal et al, Health Affairs, 2009).
  • Particular concerns about increased use among
    youth, with growing evidence of risks including
    metabolic effects, uncertainties about long-term
    effects on brain development. First-generation
    APs largely reserved for adults with
    schizophrenia and other severe psychotic
    disorders, but this changed following advent of
    the AAPs, perceived as much safer.
  • In 2000s APs most expensive class of medication
    in MA.

3
AP Use in Medicaid Youth Clinical and Policy
Challenge
  • Results from CERTs consensus meeting, expert
    survey, early data analyses and information on
    other mental health treatment challenges
    presented by mental health CERTs at Seattle
    meeting with Medicaid Medical Directors Learning
    Network.
  • MMDs prioritized the issue of APs in youth as top
    priority for a collaborative project.

4
Annual Antipsychotic Use Rates by Gender, Age
Medicaid FFS Youth Ages 6-172001 - 2004
__________________________________________________
___________
Annual rate of use as of enrollees Annual rate of use as of enrollees Annual rate of use as of enrollees Annual rate of use as of enrollees Annual rate of use as of enrollees
2001 2002 2003 2004
Total Gender 2.87 3.19 3.60 4.03
Male 3.99 4.42 4.92 5.46
Female 1.68 1.89 2.19 2.50
Age Group
6-12 2.40 2.65 3.00 3.34
13-15 3.77 4.20 4.64 5.16
16-17 3.59 3.91 4.45 5.01
MAX all states except AZ, DE, DC, OR,
NV, RI, NJ
5
Annual Antipsychotic Use Rates by Foster Care
Medicaid FFS Youth Ages 6-172001 - 2004
__________________________________________________
________
Annual rate of use as of enrollees Annual rate of use as of enrollees Annual rate of use as of enrollees Annual rate of use as of enrollees Annual rate of use as of enrollees
2001 2002 2003 2004

No 2.31 2.59 2.95 3.35
Yes 9.35 10.56 12.11 13.22
MAX all states except AZ, DE, DC, OR, NV, RI,
NJ
6
Hierarchical Diagnostic Groups Among AP Users
Medicaid FFS Youth Ages 6-17 ___________________
___________________________________________
2001 2002 2003 2004
N 112,551 134,839 172,226 201,920
Schizophrenia 3.2 2.8 2.4 2.2
Autism 5.1 5.2 5.0 5.0
Bipolar disorder 13.9 14.6 15.2 16.8
Conduct disorder/DBD (No ADHD) 11.6 11.3 10.3 9.8
Conduct disorder/DBD AND ADHD 10.7 10.4 9.8 9.7
ADHD 25.8 26.8 27.9 29.0
Anxiety or depression 9.5 9.4 9.1 8.9
Substance abuse 0.3 0.4 0.4 0.4
Adjustment-related disorders 1.8 1.6 2.0 1.6
Other mental health disorders 6.3 6.2 5.9 5.9
None of above 11.7 11.4 12.0 10.7
MAX all states except AZ, DE, DC, OR, NV, RI,
NJ
7
Payer/Stakeholder Concerns
  • Widespread use despite limited evidence base.
    Concerns about adequacy of initial assessment,
    monitoring, drug tx without close followup or
    psychosocial treatment.
  • Especially high use in particular subgroups (e.g.
    foster care).
  • Antipsychotic polypharmacy concerns about
    dosing.
  • Use among children under 6.
  • Wide variation in use across clinics,
    geographical subareas without apparent clinical
    rationale.
  • Unclear what are best practicesdifficult to
    balance appropriate oversight and avoiding
    interference with clinical management. What
    types of cases might call for additional review
    and through what methods?
  • These concerns led to the two CERTs efforts to
    work with experts and states on issues of youth
    AP use.

8
Collaborative CERTs Project with MA Medical
Directors Learning Network AP Use in Kids
  • Grew out of Seattle MMDLN/CERTs meeting focusing
    on mental health challenges identified by MMDs.
  • AHRQ supported initiative benchmarking of AP
    prescribing patterns for kids, with states
    conducting analyses of their own data using
    common variable definitions and table shells.
    Concurrent effort to describe relevant state
    policies/program structures.
  • Periodic conference calls to develop common
    definitions, data dictionary, procedures.
    Challenging problems of measurement as states use
    their own data in different ways and policies
    differ (e.g., age-specific guidelines definition
    of polypharmacy).
  • States discussed potential best practices in
    fall 2008 meeting at AHRQ.     

9
Multistate Analysis Using MAX
  •  MAX data set up for efficient cross-state
    comparison with ability to pool data from
    multiple states. Extensive pre-processing
    includes translation of state codes into a common
    set of codes.
  • Analysis by a single research team provides for
    consistent, replicable, documented coding
    consistent inclusion criteria pooling of
    relevant subgroups across states ability to
    identify and follow up on anomalies potential
    for multivariate analysis multiple iterations of
    analyses etc all of which have been key to
    research analyses.
  • However, pre-processing and other administrative
    steps add substantial time lag. Most recent data
    currently in researchers hands are for 2004 with
    2005 just beginning to be shipped.   

10
Separate Data Analyses at State Level
  •  Separate analyses by individual states represent
    an alternative model.
  • Advantages include builds experience and
    expertise within states and increases likelihood
    of subsequent followup and integration of
    measurement into ongoing monitoring and quality
    improvement activities. For example, metrics
    that are effective at aggregate level may also be
    effective at provider and beneficiary level to
    identify and act on treatment patterns that
    suggest need for review.
  • Allows use of most recent data, avoids
    time-consuming process of negotiating data use
    agreements with multiple states.   

11
Separate Data Analyses at State Level
  •  Challenges  making sure that data from
    different data systems, programmed by different
    staff, are analyzed in comparable way.
    Challenges in understanding/documenting inclusion
    criteria taking account of different program
    structures (e.g. FFS vs. managed care), differing
    mix of eligibility categories and diagnostic
    subgroups, etc.
  • Resources required in distributed data analysis
    approaches to assure consistency, validity,
    comparability. Limited number of feasible
    iterations cannot pool relevant subgroups (e.g.
    eligibility categories, ages, etc) across states.
  • Tradeoff between simplicity of methods and
    required coding versus more-complex measures to
    improve validity (e.g. challenges with
    polypharmacy, adherence, etc.).
  • Challenges in comparing data across states
    without adjustment/documentation of case-mix,
    eligibility differences, etc.

12
Data Dictionary
  • Data Dictionary developed to provide common
    definitions for
  • Demographic splits (age, gender, eligibility
    types, FFS/managed care, etc.).
  • Dose (identify excessive dosing, by age group)
  • Multiple drug exposure (define how to discern
    crossover and medication changes).
  • Poly-prescribers (may be reflective of continuity
    of care)
  • Diagnosis (what diagnoses do kids treated with
    APs receive).
  • Maximal gap in days (are prescriptions being
    taken without interruption).
  • Mental health eligibility descriptions (e.g,
    carve outs in MH services and FFS pharmacy
    services).
  • Program characteristics (each State can be
    characterized by programs central and local
    to compare trends and practices).

13
Separate Data Analyses at State Level
  • Despite limitations, conduct of analyses at state
    level has provided 16 states with a first look at
    their own utilization patterns and positioned the
    states well to extend analyses into examination
    of trends identification of treatment patterns
    at provider and beneficiary level that suggest
    need for further examination provided
    information to inform policy development and
    laid groundwork for quality improvement
    initiatives and more systematic use of quality
    metrics.
  • Perhaps most importantly, collaborative approach
    has enabled states to exchange information and
    insights about policies, potential best
    practices, and potential pitfalls.
  • Meeting to discuss practices and utilization
    challenges, states identified too young, too many
    and too much as flags for followup action at
    beneficiary and aggregate level.

14
MMDLN Partnership Too young, too many, too much
  • Use in 5 year olds
  • More than 11,000 users under age 6 identified.
  • Range 0.02 - 0.67 mean approx .22.
  • Several states examining options for additional
    reviews/approval procedures in this population.

15
MMDLN Partnership Too young, too many, too much
  • Poly-pharmacy
  • Two levels Use of multiple antipsychotics use
    of multiple (4) MH Drugs during year.
  • Analytic issues Distinguishing intended or
    unintended true poly-prescribing from tapered
    switches
  • MMDLN project uses simplified algorithm given
    practical limitations of distributed data
    analysis approach (overestimation of true
    polypharmacy)
  • Work in NYS to develop and validate a better AP
    polypharmacy measure that can be used by other
    states.
  • Also looked at too much (dosing).

16
Potential Applications by States Analyzing Their
Own Utilization Data
  • Examining AP use patterns within their state on
    ongoing basis can be useful tool to support
    policy development.
  • Potential development and use of metrics for
    quality/appropriateness/need for case review, at
    aggregate, provider and beneficiary level.
    Ability to identify, followup on
    providers/beneficiaries with outlier patterns
    warranting review.
  • Periodic utilization analyses can help Medicaid
    programs
  • determine the magnitude of regional variation in
    AP prescribing patterns in their State.
  • engage their mental health community to
    examine the systematic and data-driven concerns
    surrounding AP prescription patterns.
  • inform and support quality improvement efforts.
  • Ability to evaluate changes in utilization
    patterns as new policies and programs are
    initiated.

17
Collaborative CERTs / MMDLN Project
  • Potential further development of this
    collaborative effort
  • Further identification of best practices,
    evaluation of policy changes.
  • Further development of metrics for use at program
    and provider levels
  • Collaborative educational and other initiatives
    to improve evidence based use of medications
  • Analyses of use patterns in greater depth (e.g.,
    use of validated AP polypharmacy measures
    duration of use multi-diagnosis patterns)
  • Initiatives to evaluate/improve adherence,
    particularly in subpopulations where consistent
    tx is key.
  • Atypical antipsychotics in adults

18
Comments
  • Expanded and broadened use of APs in Medicaid
    youth is ongoing policy challenge, in the face of
    uncertain efficacy and safety for many subgroups
    of treated population. Collaboration has
    tremendous value for addressing this challenge.
    However, time- and labor-intensive needs
    investment in communicating across planetary
    (Mars/Venus) divides trust-building much
    communication about data and other issues.
  • This effort has benefited from enormous
    investment of effort and commitment from MMDs.
    Important to identify the right organizational
    level for collaboration (MMDs are very
    appropriate) and to continually keep lines of
    communication clear with higher authorities
    (e.g., NASMD briefings). Respecting political
    sensitivities and avoiding surprises are
    important.

19
Comments
  • Not a short-term or one-shot effort. Best
    approached as a continuing process where initial
    efforts can be built on and initial kinks
    untangled. Greatest payoffs come as result of
    continuing collaboration.
  • In some respects structured communication on
    practices and experience with policies is
    most-valuable result, at least in middle term.
  • Development and use of metrics is also highly
    valuable not necessary for each of 50 states to
    reinvent the wheel.
  • To do distributed data analysis properly
    requires substantial resources and documentation
    to assure consistency and comparability. Need
    for funding sources for this work.

20
Comments
  • Important to communicate about limitations and
    challenges in comparing analyses across states
    and to distinguish between research-grade
    analyses and those that narrow the degree of
    uncertainty, despite challenges.
  • When youve seen one Medicaid state, youve seen
    one Medicaid state. State level data best
    interpreted in light of local knowledge about
    beneficiary characteristics, program structures,
    sorting into eligibility categories (e.g. FFS
    versus managed care), coding issues, etc. (One
    example among many coding for foster care status
    not necessarily consistent across states).

21
Value of Collaborative Researcher/Policymaker
Initiatives
  • Despite resource and other challenges, this
    collaborative approach has provided 16 states
    with a first look at their own utilization
    patterns and positioned the states well to extend
    analyses into examination of trends
    identification of treatment patterns at provider
    and beneficiary level that suggest need for
    further examination provided information to
    inform policy development and laid groundwork
    for quality improvement initiatives and more
    systematic use of quality metrics.
  • Collaborative approach has enabled states to
    exchange information and insights about policies,
    potential best practices, and potential pitfalls.
  • Collaborative efforts, under the right
    circumstances, are of interest to Medicaid
    programs and offer great potential for improving
    care for a large, important and vulnerable
    population of beneficiaries.

22
Contact Information
  • Stephen Crystal, Ph.D.
  • Director, Center for Education and Research on
    Mental Health Therapeutics
  • Rutgers University 30 College Avenue New
    Brunswick, NJ 08901 voice 732-932-8579 fax
    732-932-8592
  • scrystal_at_rci.rutgers.edu
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