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Medicaid Coverage and Access to Publicly Funded Opiate Treatment: Oregon’s Experience NIDA/RWJ Journalist Workshop Tucson, AZ December, 2005 Dennis Deck,

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Presentation on theme: "Medicaid Coverage and Access to Publicly Funded Opiate Treatment: Oregon’s Experience NIDA/RWJ Journalist Workshop Tucson, AZ December, 2005 Dennis Deck,"— Presentation transcript:

1 Medicaid Coverage and Access to Publicly Funded Opiate Treatment: Oregon’s Experience NIDA/RWJ Journalist Workshop Tucson, AZ December, 2005 Dennis Deck, Wyndy Wiitala, Kathy Laws RMC Research Corporation Portland, Oregon

2 2 Acknowledgements Funding sources  NIDA R01 DA015060  RWJ SAPRP 51530 Collaborators  Dennis McCarty, Bentson McFarland, OHSU  Roy Gabriel, RMC Data access  Oregon DHS - OMAS and OMAP Presentation based on paper accepted for publication in J Behavioral Health Services & Research.

3 3 Substance Abuse Treatment and Role of Medicaid Medicaid  Primary payer of publicly funded outpatient treatment  Especially true for opiate treatment, a chronic condition where preferred treatment is usually Methadone Maintenance (MMT)  Important from both the client and provider’s 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 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 5 Outpatient SA Tx Access Rates (Percent of eligible adults admitted during year) Deck et al (2000) JAMA - Rate more than doubles despite shift to managed care. - Number served in substance abuse treatment almost quadruples.

6 6 Methadone Utilization Rates (MMT users per 1000 enrolled) Deck & Carlson (2004) JBHSR.. Capped system limits access and promotes administrative discharges Increase driven by higher retention rates despite managed care

7 7 Oregon Health Plan 2 Renewal of Medicaid waiver in 2002 (while state was experiencing unprecedented budget deficit and rising Medicaid costs) New features (preserve expansion while cap costs)  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 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 9 Adult Medicaid Enrollment Monthly Medicaid enrollment of adults (ages 18-64) enrolled in the OHP. Historical (pre-2003) eligibility codes were mapped to their OHP2 equivalents. Greater disenrollment among those with least ability to pay

10 10 Methadone Access Rates* Medicaid eligible adults admitted to MMT per thousand enrolled adults *Monthly adult methadone admissions divided by number of adults enrolled in OHP times 1,000. A=SA/MH benefit cut announced, E=cut takes effect, R=benefit restored but enrollment frozen A E R Between 2002 and 2003, a 58% decline for OHPS and 15% for OHP+ (averaging Apr-Nov) Reflects pent up demand but not sustaine d due to frozen enroll- ment.

11 11 Shift in Client Mix Among OHPS Presenting for Opiate Use Comparison of cohorts on selected predictors with significant differences.

12 12 Results (Odds Ratios) of Model Predicting Placement in MMT among Opiate Admissions 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 yrs5.09 Enabling Stable eligibility1.60 Self referral3.68 No clinic in county.25 Not able to work.21 Single.55 Group home.23 Homeless.36 Propensity (case mix adj).00 All predictors significant at p<.01 or p<.001

13 13 Model Interpretation The odds of being placed in methadone was less than half for individuals presenting for opiate addiction after the benefit cut than before (controlling for changes in client mix). For both cohorts, barriers to access include:  living in a county with no clinic  unable to work due to physical or mental condition  being single or homeless, living in a group home  having co-occurring alcohol or cocaine disorders  being African-American Factors associated with greater access include:  prior history of MMT, long history opiate use  being female  self-referred to treatment, stable Medicaid eligibility See also Deck & Carlson (2002)

14 14 Qualitative Findings State/Regional Perspective  Isolated attempts to cover clients in treatment (but little statewide impact)  Eventual decision to reinstate benefit in recognition that this was wrong place to cut: ”Cutting it was a huge mistake. We would have been better off preserving those services” (state legislator)

15 15 Qualitative Findings Provider Perspective  Anticipated huge loss of revenue and clients (OHPS= 62% of Medicaid eligible clients) “The sky is falling”, “The most devastating event I have ever experienced.”  Clinic closures (2 of 12) and all providers reported staff layoffs and cut backs.  Forced to prepare to discharge clients who could not pay out of pocket  Reduction in wraparound or support services

16 16 Qualitative Findings Client Perspective  Anecdotal reports of extreme duress and negative outcomes (e.g. suicide attempts, MH crises, back on street, resumption of crime) as well as the pain of detoxification for those leaving treatment  About half those enrolled in MMT when cut announced elected to pay out of pocket and thus forced to find ways to cover fees ($12-18/day)  Though benefit was reinstated, only those still enrolled were eligible.  Little known about what has happened to those not in enrolled in treatment prior to cut.

17 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 general loss of capacity (even stronger with Outpatient SA and MH services)

18 18 Implications: Outcomes and Costs Clinical studies have shown improved outcomes for individuals while participating in methadone maintenance programs. The NIH consensus statement lists consequence of untreated opiate addiction as:  Higher rates of illegal activity  Higher medical costs (ER and inpatient use, HIV)  More illicit drug use  Greater mortality  Greater joblessness However, few studies demonstrating that the expected outcomes (or cost offsets) will be realized naturalistic settings with large populations.

19 19 Oregon Felony Arrests by Modality and Arrest History Descriptive analysis with no adjustment of other covariates. Lower probability of arrest during months in treatment, especially MMT Arrests much more likely among those with recent arrest history

20 20 Preliminary Longitudinal Results (36 months following first opiate admission for cohorts presenting 1993-2000) Outcome Independent Variable (Time Varying) Oregon Odds Ratio Washington Odds Ratio Enrolled in methadone during month Medicaid9.73.9 Arrested during month Methadone.29.30 HLM Level 1 model = month from admission, time varying covariate, interactions HLM Level 2 model = propensity for MMT and for Medicaid, prior arrests, cohorts

21 21 Implications: State Policy States face difficult decisions in curbing rising Medicaid costs, especially when facing large state deficits and unfunded federal mandates. Oregon’s benefit cut withdrew coverage for a particularly vulnerable and potentially costly group. There is now general consensus that this was a mistake.

22 22 Limitations Oregon’s 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).

23 23 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

24 24 Analysis Access Rates  Access = Number placed in MMT / Number eligible * 1000  Controls for enrollment decline but unadjusted for change in client mix Model access with logistic regression using Propensity Score Analysis to control for cohort differences  Find first opiate admission in 2002-03 cohorts  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

25 25 Propensity Score Analysis Dealing with non-equivalent groups Hypothetical Distribution of Propensity Scores Predicting 2003 Cohort High Low 2003 Cohort 2002 Cohort At any point, the clients in the two cohorts are well balanced on all observed covariates Number of clients See Rosenbaum and Rubin (1984), Shadish & Clark (2002)

26 26 Balancing Effect of PS on Observed Covariates Old (50-64) MMT in past 2 yrs Live in county w/o clinic Not able to work Groups were defined by quintiles on the propensity score. Group 5 (highest PS) was most representative of the 2003 cohort.

27 27 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), 2093–2099 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., & D’Ambrosio, 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), 43–60. 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), 164–177. 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. 79:516-24. 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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