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Medicaid Coverage and Access to Publicly Funded Opiate Treatment: Oregon

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Medicaid Coverage and Access to Publicly Funded Opiate Treatment: Oregon s Experience AHSR Santa Monica, CA October, 2005 Dennis Deck, Wyndy Wiitala, Kathy Laws – PowerPoint PPT presentation

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Title: Medicaid Coverage and Access to Publicly Funded Opiate Treatment: Oregon


1
Medicaid Coverage and Access to Publicly Funded
Opiate TreatmentOregons ExperienceAHSRSanta
Monica, CA October, 2005
  • Dennis Deck, Wyndy Wiitala, Kathy Laws
  • RMC Research Corporation
  • Portland, Oregon

2
Acknowledgements
  • Funding sources
  • NIDA R01 DA015060
  • RWJ SAPRP 51530
  • Collaborators
  • Dennis McCarty, Bentson McFarland, OHSU
  • Toni Krupski, Kevin Campbell, DASA
  • John Mullooly, KCHR
  • Roy Gabriel, RMC
  • Data access
  • Oregon DHS - OMAS and OMAP
  • Presentation based on paper accepted for
    publication in JBHSR and updated trend data.

3
Substance Abuse Treatment and Role of Medicaid
  • Medicaid
  • Primary payer of publicly funded outpatient
    treatment
  • Especially true for opiate treatment, a chronic
    condition
  • Important from both the client and providers
    perspective
  • State context
  • Some states (e.g. Oregon) have implemented
    various initiatives to expand eligibility or
    benefits
  • Rising health care costs and recent budget
    deficits have put some of these initiatives at
    risk
  • Legislatures pressured to make Medicaid budget
    neutral

4
Oregon Health Plan
  • OHP elements phased in
  • Expanded eligibility to childless couples and
    single adults (Section 1115 waiver, 1994)
  • Mandatory enrollment in managed care
  • Prioritized list of covered services
  • Integration of substance abuse treatment (1995)
  • Prior studies
  • Increase in number and rate entering outpatient
    treatment
  • No evidence of decline in severity or outcomes
  • Stability of eligibility important for access,
    retention, outcomes
  • Increase in number but lower rate entering
    methadone
  • Increase in methadone retention rates (1yr)

5
Outpatient Access Rates (Percent of eligible
adults admitted during year)
Rate more than doubles despite shift to managed
care. Number served in substance abuse
treatment almost quadruples.
Deck et al (2000) JAMA
6
Methadone Utilization Rates(MMT users per 1000
enrolled)
Increase driven by higher retention rates despite
managed care.
Capped system limits access and promotes
administrative discharges.
Deck Carlson (2003) JBHSR, Deck Carlson
(2004) JBHSR
7
Oregon Health Plan 2
  • New features (Section 1115 waiver renewed 2002)
  • Split benefit
  • OHP Plus (mandatory programs like TANF SSI
    full benefit)
  • OHP Standard (expansion program reduced
    benefit)
  • Increase cost sharing measures
  • Greater enforcement of premium payment for OHPS
  • Co-payments for some services
  • Greater latitude to keep plan budget neutral
  • Legislative emergency board action
  • Eliminate SA/MH/dental services from OHPS benefit
    (including methadone)
  • Announced Dec 02 but took effect Mar 03

8
Hypothesis
  • OHP Standard adults admitted for opiate
    addiction after cut (2003) will have reduced
    access to methadone relative to their
    counterparts before cut (2002) controlling for
  • Selection bias due to Medicaid disenrollment
  • Client characteristics that predispose or enable
    placement in methadone maintenance

9
Methods
  • Subjects
  • 2,244 adults (ages 18-64) admitted to publicly
    funded treatment for opiate addiction
  • 2002 and 2003 cohorts
  • Quantitative Data
  • State treatment database (Client Process
    Monitoring System CPMS)
  • Linked records to Medicaid eligibility history
  • Qualitative Data
  • Interviews with providers and other key informants

10
Analysis
  • Access Rates
  • Access Number placed in MMT / Number eligible
    1000
  • Controls for enrollment decline but unadjusted
    for change in client mix
  • Compare Cohorts using Propensity Score Analysis
  • Find first opiate admission in 2002-03 and
    identify cohort
  • Calculate Propensity Score (Rosenbaum and Rubin)
  • Logistic Regression predicting 2003 cohort
  • Enter admission characteristics as covariates
  • Save predicted score for covariate in subsequent
    analysis
  • Impute missing with second model dropping problem
    variables
  • Test Hypothesis
  • Logistic Regression predicting methadone
    placement
  • Enter dummy variable for cohort (2003 vs 2002)
  • Enter propensity score to control for client mix
  • Enter additional covariates that are correlates
    of access

11
Adult Enrollment in OHP
Monthly enrollment of adults (ages 18-64)
enrolled in the OHP. Historical (pre-2003)
eligibility codes were mapped to their OHP2
equivalents.
12
Methadone Access RatesMedicaid eligible adults
admitted to MMT per thousand enrolled adults
From 2002 to 2003 (averaging Apr-Nov), we
observed a 58 decline for OHPS and 15 for OHP
R
A
E
Monthly adult methadone admissions divided by
number of adults enrolled in OHP times
1,000. ASA/MH benefit cut announced, Ecut takes
effect, Rbenefit restored but enrollment frozen
13
Shift in Client Mix Among OHPS Presenting for
Opiate Use
Comparison of cohorts on selected predictors with
significant differences.
14
Balancing Effect on Observed Covariates
MMT in past 2 yrs
Old (50-64)
Live in county w/o clinic
Not able to work
Groups defined by quintiles on propensity score.
15
Model Predicting Access (Odds Ratios)
  • 2003 Cohort (vs 2002) .40
  • Predisposing
  • Old (50 vs 25-49) 1.84
  • Male (vs female) .61
  • African Am (vs white) .41
  • Need
  • Meth/amph problem .54
  • Alcohol problem .55
  • Yrs opiate use (Ln) 2.47
  • MMT in past 2 yrs 5.09
  • Enabling
  • Stable eligibility 1.60
  • Self referral 3.68
  • No clinic in cnty .25
  • Not able to work .21
  • Single .55
  • Group home .23
  • Homeless .36
  • Propensity .00

All predictors significant at plt.01 or plt.001
16
Qualitative Findings
  • Client Perspective
  • Medicaid disenrollment disproportionate among
    those with least ability to pay and least likely
    to have other source of coverage.
  • Anecdotal reports of negative outcomes (e.g.
    suicide attempts, back on street, resumption of
    crime) as well as the pain of detoxification
  • About half those in MMT when cut announced
    elected to pay out of pocket and thus forced to
    find ways to cover fees
  • Though benefit was reinstated, only those still
    enrolled were eligible.
  • Provider Perspective
  • Anticipated huge loss of revenue and clients
  • Clinic closures (2 of 12) and all reported staff
    layoffs
  • Forced to titrate and prepare to discharge
    clients who could not pay
  • Reduction in wraparound services
  • State/Regional Perspective
  • Isolated attempts to cover clients in treatment
  • Eventual decision to reinstate benefit, some
    recognition that this was wrong place to cut

17
Discussion
  • Access
  • Fewer OHPS clients presented for opiate
    treatment.
  • Those that did were less than half as likely to
    be placed in methadone
  • New admissions
  • Proportionately fewer new opiate admissions
  • Biggest cost offsets would be expected for this
    group
  • System capacity
  • Strong and immediate provider response
  • OHP decline suggests possible spill over effect
    (even stronger with Outpatient SA and MH
    services)

18
Limitations
  • Oregons Medicaid expansion population may be
    somewhat unique (but no reason to expect
    different results with other poverty groups).
  • Propensity score analysis only adjusts for
    observed covariates (but data set included rich
    source of covariates).
  • Retrospective study using administrative
    databases (but covers the population rather than
    a small sample).

19
Implications
  • Benefit cut resulted in fewer seeking opiate
    treatment and less access to most appropriate
    source of care.
  • Reasonable to assume that untreated opiate
    addiction may result in negative consequences in
    the form of arrests, ER use, mortality, etc.
  • Thus, states would do well to consider the impact
    of cuts to leveraged services likely to have cost
    offsets.

20
Preliminary HLM Results(36 months following
first opiate admission for cohorts presenting
1993-2000)
Outcome Time Varying Covariate OregonOR WashingtonOR
Enrolled in methadone during month Medicaid 9.7 3.9
Arrested during month Methadone .29 .30
Level 1 model month from admission, time
varying covariate, interactions Level 2 model
propensity for MMT and for Medicaid, prior
arrests, cohorts
21
References
  • Deck, D.D. , McFarland, B.H., Titus, J.M., Laws,
    K.E., Gabriel, R.M. (2000). Access to substance
    abuse treatment . Journal of American Medical
    Association. 284(16), 20932099
  • Deck, D.D. Wiitala, W. Laws, K. (in press).
    Medicaid coverage and access to publicly funded
    opiate treatment. Journal of Behavioral Health
    Services and Research.
  • Carlson, M.J., Gabriel, R.M., Deck, D.D., Laws,
    K.E., DAmbrosio, R. (2005). The impact of
    managed care on publicly funded outpatient
    adolescent substance abuse treatment Service use
    and 6-month outcomes in Oregon and Washington.
    Medical Care Research and Review, 62(3), 320-338.
  • Deck, D.D. Carlson, M.J. (2005). Retention in
    methadone maintenance treatment in 2 western
    states. Journal of Behavioral Health Services
    Research, 32(1), 4360.
  • Deck, D.D. Carlson, M.J. (2004). Access to
    publicly funded methadone maintenance treatment
    in two western states. Journal of Behavioral
    Health Services Research, 31(2), 164177.
  • Deck, D.D. McFarland, B.H. (2002). Use of
    substance abuse treatment services before and
    after Medicaid managed care. Psychiatric
    Services, 53(7), 802.
  • McFarland, B.H., Deck, D.D., McCamant, L.E.,
    Gabriel, R.M., Bigelow, D.A. (in press).
    Outcomes for Medicaid clients with substance
    abuse problems before and after managed care.
    Journal of Behavioral Health Services and
    Research.
  • Rosenbaum P.R., Rubin D.B. (1984). Reducing bias
    in observational studies using subclassification
    on the propensity score. Journal of the American
    Statistical Association. 79516-24.
  • Shadish, W.R., Clark, M.H. (2002). An
    introduction to propensity scores. Metodologia de
    las Ciencias del Comportamiento Journal, 4,
    291-300.
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