Using HMOs To Serve The Medicaid Population: What Are The Effects On Healthcare Utilization And Does The Type Of HMO Matter? Bradley Herring and E. Kathleen Adams Emory University June 25, 2006 AcademyHealth ARM in Seattle Funded by an RWJF HCFO Grant

Primary Research Questions What are the effects of using HMOs for the Medicaid population? –Does enrollee access to care change? –Do utilization patterns change? –Do overall healthcare expenses change? Are there different effects for commercial HMOs versus Medicaid-dominant HMOs?

Background Enrollees in some form of Medicaid managed care increased from 32.1% in 1995 to 60.7% in 2004 –Primary care case management –At risk health plans: carve out plans and HMOs Enrollees in Medicaid HMOs increased from 14.1% in 1995 to 39.5% in 2004 Little consistent or generalizable empirical evidence for access to care, utilization, or total expenses

State Motivation for Using Managed Care Improve access to care, at current expense: –Improve access to mainstream office-based providers? –Improve quality? Reduce expense, while maintaining access: –Improve use of cost-effective preventive services? –Decrease unnecessary use of the ER? –Better manage chronic conditions? –Use bargaining power to achieve provider discounts? Or perhaps yield predictable budgets?

Might the Type of HMO Matter? Commercial HMOs enrolling both Medicaid and privately insured populations: –Reduce stigma by integrating populations? –More likely to include mainstream providers? –Economies of scale? Medicaid-dominant HMOs – more than 75% of enrollees in Medicaid: –Serve unique needs (economies of scope)? –More likely to include traditional safety net providers? –Inefficient due to learning by doing?

Prior Research Early research summarized in Hurley et al. (1993) and Rowland et al. (1995) More recent research: –State-specific analysis: CA, FL, OH, MN, TN, WI –Nationally-representative survey data: State-level penetration or presence of MMC in a county –We compliment Duggans (2004) work on total state expenditures (i.e., capitation rates) by focusing on underlying utilization-based expenses

Our Empirical Approach Community Tracking Study in 60 U.S. markets –Household Survey for 96-97, 98-99, 00-01, and 03 –We limit to the 51 urban MSAs MSA measures of Medicaid HMO penetration using CMS and InterStudy data for 96, 98, 00, and 02 –CMS lists all Medicaid HMOs and the counties served –We link to InterStudy data to determine whether each HMO is commercial or Medicaid-dominant –Penetration rate: the percentage of all Medicaid enrollees in that HMO type

Medicaid HMO Penetration Rates of Urban CTS Markets by Period Variables: HMO (both types) penetration rate24.7%35.9%32.4%42.1% Commercial HMO penetration rate8.5%14.3%12.4%12.1% Medicaid-dominant HMO penetration rate16.2%21.6%20.0%30.0% Source: Complied CMS and InterStudy data

Our Empirical Approach (cont.) OUTCOME it = f (ß HMO X HMO,it + ß I X I,it + ß AREA X AREA,it + γ MSA MSA i + γ YEAR YEAR t, ε) where OUTCOME it = a specific outcome measure for Medicaid enrollee i during time t X HMO,it = measures of commercial and Medicaid-dominant HMO penetration X I,it = a set of individual characteristics X AREA,it = a set of local area characteristics MSA i = a set of MSA indicator variables YEAR t = a set of year indicator variables ε = an error term

Medicaid Enrollees in the CTS-HS: Three Sets of Dependent Variables Sample: 9134 non-elderly with Medicaid in the CTS-HS –Includes children in SCHIP –Adults and children both together and separate 1 st set: Access measures: –Usual source of care other than the ER –Usual source of care is the ER –Having a difficulty in obtaining care –Being satisfied with ones primary care doctor

Medicaid Enrollees in the CTS-HS: Three Sets of Dependent Variables (cont.) 2 nd set: utilization measures: –Office-based physician visits– Medical practitioner visits –Any mental health services– ER visits –Inpatient stays– Inpatient nights –Inpatient surgeries– Outpatient surgeries 3 rd set: synthetic estimate of total healthcare expenses using CTS-HS utilization & the MEPS: – MEPS to regress actual expense on utilization –The MEPS coefficients are essentially unit prices

Medicaid Enrollees: Independent Variables Variables of interest: –Commercial HMO penetration rate –Medicaid-dominant HMO penetration rate Individual controls: –Age and gender, family type (e.g., single with kids), family income, race/ethnicity, education, self-reported health status Local-area controls: –PCCM, type of SCHIP expansion, Medicaid fee index, MDs/capita seeing Medicaid, hospital beds/capita, FQHC, private HMO penetration, median income, race/ethnicity MSA fixed effects and time trend

Results for Commercial HMOs Child enrollees: –No effect on access –No effect on utilization –No effect on expenses Adult enrollees: –No effect on access –Increase only for mental health visits (p<0.05) –Decrease in expenses (p<0.10)

Results for Medicaid-Dominant HMOs Child enrollees: –Decrease in usual source of care other than ER (p<0.10) –Increase in medical practitioner visits (p<0.10) Increase in ER visits (p<0.05 ) –Increase in healthcare expenses (p<0.05) Adult enrollees: –Increase in using the ER as a usual source of care (p<0.10) –Increase in medical practitioner visits (p<0.05) Decrease in inpatient surgeries (p<0.001) Decrease in outpatient surgeries (p<0.05) –No effect on healthcare expenses

Magnitude of the Effect of Medicaid-Dominant HMOs We simulate the independent effect of the increase in the Medicaid-dominant penetration rate of 16.2% in to 30.0% in : –Proportion reporting a (non-ER) usual source of care: Reduced from 86.2% to 84.8% –Number of visits to the ER: Increased from per year to per year –Total healthcare expenses (in 2003$): Increased from $3004 to $3163 (a 5.3% real increase)

Conclusions Increase in penetration by commercial HMOs: –No change in access to care –Little change in utilization patterns –No increase in expenses (perhaps a decrease for adults) –(Our other work: increase in physician participation) Increase in penetration by Medicaid-dominant HMOs: –Worse access to care –Many changes in utilization –Increase in expenses for children; No change for adults –(Our other work: no change in physician participation)

Policy Implications Whats the real motivation for contracting with HMOs? –Welfare improvements from either improved access and maintained expense -or- lower expense and maintained access Our results suggest that –States may have seen small welfare improvements by contracting with commercial HMOs before their exit –States have seen (and will see) decreases in welfare by contracting with Medicaid-dominant HMOs Attention needed in setting capitation rates and fees –Exits by commercials & pressure from Medicaid-dominants