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Effects of Managed Care Enrollment on Publicly Insured Children with Chronic Health Conditions

Effects of Managed Care Enrollment on Publicly Insured Children with Chronic Health Conditions. Amy J. Davidoff, Ph.D. University of Maryland Baltimore County University of Maryland School of Pharmacy Presented at the Annual AcademyHealth Meeting, Seattle, WA June 25, 2006

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Effects of Managed Care Enrollment on Publicly Insured Children with Chronic Health Conditions

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  1. Effects of Managed Care Enrollment on Publicly Insured Children with Chronic Health Conditions Amy J. Davidoff, Ph.D. University of Maryland Baltimore County University of Maryland School of Pharmacy Presented at the Annual AcademyHealth Meeting, Seattle, WA June 25, 2006 Funded by a grant from the Maternal and Child Health Bureau

  2. Setting the stage • Managed care (MC) dominant financing, delivery mechanism in Medicaid, SCHIP • Incentives in MC => improved access, use for primary, preventive care • Concerns about impacts for children with chronic conditions • Disrupt existing provider relationships • Inadequate expertise • Hoops • Skimping? • Need to understand MC impacts, by program type, on children with chronic conditions

  3. Previous studies provide limited information on managed care for children with chronic conditions • Most studies evaluate state specific programs for SSI recipients • Often lack control or comparison groups • Don’t permit comparisons across program types • Results mixed • National cross-plan estimates - don’t address differential effects by health status

  4. Study by Hill et al. (2002) provides useful framework, hypotheses • Qualitative study of Medicaid programs, 8 states • FFS – lacks coordination • Mainstream PCCM, capitated plans • Adequate primary, specialty care • Poor ID of children, lacked non-medical wraparound • Mainstream plans with carveouts – create confusion • Special programs for children with chronic conditions perceived positively

  5. Analytic Approach • Estimate linear probability models, DD interpretation Access/Use = a0 + a1 CC + a2 MCtype + a3 CC*MCtype + a4 X + e • CC = indicator for child w/ chronic condition • MCType = vector MC program types • PCCM, capitated w/ & w/o carveout, special programs • reference is FFS • focus on mandatory

  6. Data • Household survey data: • National Health Interview Survey (NHIS), 1997 - 2002 • Data on managed care plan type abstracted from multiple sources • CMS Medicaid Managed Care Enrollment Reports • SCHIP state plans • Urban Institute, NASHP surveys

  7. Data on Managed Care Plan Type (cont.) Captured information on • Type of MC program, service carve outs • Counties operational • Inclusion of SSI recipients, others with special needs • => Medicaid/SCHIP, county, year, health status specific database of MC program types • Linked to NHIS along multiple dimensions

  8. Study population • Children w/ & w/o chronic conditions • children w/ chronic conditions identified through • Condition checklist • Activity limitation, caused by condition lasting >= 1 year • Reported sad or unhappy most of time, past 6 months • Eligible & Enrolled in Medicaid or SCHIP • Used detailed algorithm that applies state specific eligibility rules to ID likely eligibles

  9. Source: Davidoff et al. analysis of 1997-2002 NHIS

  10. Source: Davidoff et al. analysis of 1997-2002 NHIS

  11. Source: Davidoff et al. analysis of 1997-2002 NHIS

  12. Magnitude of reductions large relative to FFS reference group E.g. for capitated plans w/ carveout: • 7.9 percentage point reduction in probability of specialist visit = 27% reduction • 3.9 percentage point reduction in probability of hospital stay = 30% reduction • Study Limitations

  13. Study limitations • Managed care policy assigned, not reported • Gap between enrollment, assignment => downward bias • Eliminates selection bias related to voluntary enrollment, exceptions, transitions • Does not address selection into public insurance • Limitations of self reported HH survey data

  14. Conclusions • Mandatory enrollment in capitated programs • reduced ER visits, hospital stays • suggests improved outpatient management • Also reduced specialist, mental health, prescription drug use • Failure to find increased access problems suggests appropriate reductions

  15. Conclusions (cont.) • Reductions in use more pronounced with carveouts • Consistent with expectations • Additional research to probe incentives, systems • Effects of special programs difficult to interpret • Not different from FFS • Affected sample small

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