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State Policies Expanding Dependent Coverage to Young Adults in Private Health Insurance Plans
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State Policies Expanding Dependent Coverage to Young Adults in Private Health Insurance Plans

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Presentation by Joel Cantor at the AcademyHealth Annual Research Meeting adjunct State Health Research and Policy Interest Group meeting panel, "Early Results from the State Health Access Reform ...

Presentation by Joel Cantor at the AcademyHealth Annual Research Meeting adjunct State Health Research and Policy Interest Group meeting panel, "Early Results from the State Health Access Reform Evaluation (SHARE) Program," Chicago, IL, June 27 2009.

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    State Policies Expanding Dependent Coverage to Young Adults in Private Health Insurance Plans State Policies Expanding Dependent Coverage to Young Adults in Private Health Insurance Plans Presentation Transcript

    • State Policies Expanding Dependent Coverage to Young Adults in Private Health Insurance Plans June 27, 2009 Academy Health State Health Research and Policy Interest Group Meeting Chicago, IL Alan Monheit*,^, Joel Cantor*, Derek DeLia*, Dina Belloff*, Margaret Koller*, Dorothy Gaboda* *Rutgers University Center for State Health Policy ^UMDNJ School of Public Health Funded by the Robert Wood Johnson Foundation SHARE Program
    • Outline • Young adult coverage • State dependent coverage expansion policies • Preliminary impact analysis • Conclusions and limitations • Next steps Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 2
    • Young Adults at High Risk of Lacking Coverage and are Large Share of Uninsured 50% 40% 50-64 Under 15% 19 Percent Uninsured 30% 20% 30% 23% 36-49 20% 18% 23% 19-29 12% 13% 30% 10% 30-35 12% 0% < 19 19-29 30-35 36-49 50-64 Age Distribution of Uninsured Source: Kriss JL, SR Collins, B Mahoto, et al. “Rite of Passage? Why Young Adults Become Uninsured and How New Policies Can Help, 2008 Update.” The Commonwealth Fund, Issue Brief, May 2008. Pub. # 1139. Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 3
    • Source of Coverage for Young Adults (Age 19-29) Not Full-Time Students Full-Time Students 12.5 million 7.6 million Own- employer Own- employer Uninsured Uninsured 8% 17% 25% 39% Non-group or college 20% 16% plan 49% Employer- 7% 6% 13% dependent Other Non-group Employer- or college Other dependent plan Source: Kriss JL, SR Collins, B Mahoto, et al…The Commonwealth Fund. Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 4
    • Implications of High Uninsured Rate • Critical developmental period to address risks of obesity, smoking, sexually transmitted infections, etc. • Uninsured young adults are two to four times… – more likely than peers to delay/forgo care or an Rx due to costs – less likely to see a medical provider or have a usual source of care • Uninsured young adults 20% more likely to report trouble paying medical bills or carrying medical debt • Absence from risk pools has consequences for others Sources: Kriss JL, SR Collins, B Mahoto, et al…The Commonwealth Fund. Callahan ST and WO Cooper. 2006. “Access to health care for young adults with disabling chronic conditions.” Archives of Pediatric and Adolescent Medicine. 160:178-182. Merluzzi TV and RC Nairn. 1999. “Adulthood and aging: Transitions in health and health cognition.” In Whitman TL, TV Whitman, and RD White (eds). Life-Span Perspectives on Health and Illness. (pp. 189-206). Mahwan, NJ: Lawrence Erlbaum. Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 5
    • State Dependent Coverage Expansion Enactment Timeline 25 states as of 2008 CT FL ID IN Original enactments shown in black ME Expansions shown in blue italics MD MO MT MN NH SD FL TX SD MA VA IA IL CO RI WA KT UT NM NJ DE WV NJ 1994 2003 2005 2006 2007 2008 Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 6
    • Change in Age of Dependent Eligibility (as of 2008) STUDENTS NON-STUDENTS Number with Reform (25 total) 19* 23 Greatest Increase in Age Limit No limit 12 years Mean Increase in Age Limit 3.5 years** 5.7 years (among reform states) Notes Based on date of enactment. *Includes one state (RI) that increased age limit for part-time students only. ** Excludes two states (TX, IA) that eliminated the upper age limit for full-time students. Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 7
    • Change in Age of Dependent Eligibility (as of 2008) Student Non-Student No Limit 14 12 Increase in Age Limit 10 8 6 4 2 0 RI* DE IN NM VA MN WA CO WV MA IL ME MD MT CT KY UT FL MO SD NH NJ TX IA Based reforms enacted as of December 2008. Center for State Health Policy *RI raisedHealth,limit for part-time students from 18 to 24 (i.e., treating PT as FT students). Institute for age Health Care Policy and Aging Research 8
    • Other Provisions • Unmarried – 22 states • No dependents – 4 states • Other limits – Most states – residency for non-students, but not FT students – 9 states – financial dependence or living with parents – 6 states – continuous or creditable coverage • Included markets – Most states – all regulated markets and public employee plans • Premium rules – 12 states – cost averaged into group premium – 8 states – establish premiums for new dependent enrollees Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 9
    • Factors Potentially Limiting Impact • ERISA preemption – e.g., In NJ, ~33% of state population subject to state regulation (25% in state-regulated plans; 8.6% in state health benefit plan) • Possible burdens on insurers or employers – Taxable as income for those over 23 years • Possible impact on premiums and costs – Risk selection – Premium rules • Unanticipated consequences – Non-group or other risk pools – Young adult behavior (e.g., marriage, child bearing) Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 10
    • Impact Analysis Strategy • CPS March Supplements (2000-2008) – Utah and Massachusetts excluded – 15 states implementing by 2007, ~23 state-years of experience • Young adults (ages 19-29) – Restricted: Single adults living with a parent (n=66,654) – Full: All young adults (n=227,002) • Five linear probability models predicting “COVERAGE” – Covered by employer-sponsored insurance (ESI) as dependent (on parent’s policy, in restricted model) – Covered as ESI policyholder – Non-group coverage – Public coverage – Uninsured • Adjusted for complex sample design (Davern, et al.) Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 11
    • Model Specification COVERAGEi = a1 + a2TARGETi + a3(TARGETi*POLICYs,t) + a4Xi + a5Zs,t + a6ADOPTs + a7STATEs + a8YEARt + ei Where: TARGET = expansion population dummy (regardless of year) POLICY = state policy in effect dummy TARGET*POLICY = interaction of being in target population and living in a state post-policy implementation (a3 is DD estimator) X = vector of individual characteristics Z = vector of time-varying state characteristics ADOPT = predictors of state policy adoption STATE = state fixed effects YEAR = time fixed effects Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 12
    • “TARGET” define by… • State of residence • Age • Marital status • Student status • Other state-specific eligibility criteria Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 13
    • Other Variables… • Individual characteristics (X vector) – Demographics (age, sex, race/ethnicity) – Fair/poor health – Student status – Educational attainment – Family income (% FPL) – Marital status (unrestricted model) – Live with parent (unrestricted model) • Time varying state characteristics (Z vector) – Unemployment rate – Percent college graduate • Policy adoption predictors (ADOPT vector) – Number of benefit/provider coverage mandates – Party of governor and legislature – Number of insurance department staff – Elected insurance commissioner – State net budget revenues Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 14
    • Hypotheses • Policy impact as intended – Positive and significant DD estimate for ESI as dependent – Negative and significant DD estimate for Uninsured • Unintended substitution effect – Positive and significant DD estimate for ESI as dependent – Negative and significant DD estimate for ESI policyholder, non- group coverage, and/or public coverage Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 15
    • Policy Impact Estimates Change in Probability of Coverage (t-statistic) Coverage Outcome DD estimates DD estimates Single, Live w/Parent All Young Adults ESI as dependent* 0.0267 0.0193 (2.02) (2.96) Uninsured 0.0007 0.0086 (0.05) (0.89) ESI as policyholder -0.0202 -0.0201 (-1.64) (-2.31) Non-Group Coverage -0.0094 -0.0067 (-1.23) (-1.17) Public Coverage -0.0022 -0.0011 (-0.24) (-0.18) *Dependent on parent’s ESI plan in restricted model, any dependent ESI in unrestricted model Bold indicates significant at p<.10 level Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 16
    • Predicted Coverage Status Standard Population of Young Adults (ages 19-29) Based on Unrestricted Model (n=227,002) No Expansion Expansion Policy 35% 30% 25% 20% 15% 10% 5% 0% ESI dependent Uninsured ESI policyholder Non-group Public Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 17
    • Conclusions So Far • Very popular strategy, policy details vary • Expanded dependent coverage appears to substitute for other private insurance – ESI dependent coverage increase of about 2 to nearly 3 percentage points in the target population – Offset by drop in own-name ESI – No impact on uninsured rate Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 18
    • Limitations • Early experience – 23 state-years experience as of 2007 – Nearly half (11 state-years) in first year of implementation, including 4.7 state-years in 9 states that implemented in 2007 • Some eligibility characteristics unmeasured – Parental coverage status and state of residence (eligibility assigned by young adults’ state of residence) – Financial dependence of young adults on parents – Parent’s plan ERISA status – Assumed to be random with respect to adoption Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 19
    • Next Steps • Update analysis with 2009 CPS – Add 19 more state-years (including 5 states implementing in 2008) • Additional modeling – Confirm linear probability models with Logit or Probit – Refine policy variable (e.g., # years post-implementation, examine specific state policy features) – Consider DDD approach comparing to middle aged adults • Implementation case studies – Stakeholder interviews in several states TBD • NJ Family Health Survey analyses, 2001 and 2009 – Pre-post impact analysis – Estimates of eligible population – Risk selection Center for State Health Policy Institute for Health, Health Care Policy and Aging Research 20