L/O/G/O Qianwei Shen Wayne State University Spillover Effect of Medicare Advantage Plans: How the Penetration and Competition of MA Plans Affect the Quality of Medicare

Overview 5. Results 4. Data and Methodology 3. Literature Review 2. Institutional Background 1. Introduction 6. Discussion 7. Conclusion

1. Introduction The Medicare program currently provides two distinct choices to beneficiaries: a government-run fee-for-service plan known as traditional Medicare (TM), and private health plans known as Medicare Advantage (MA). local plans regional plans payment purposes plans HMOs PPOs PFFS SNPs Other plans

Affordable Care Act Medicare Modernization Act Medicare Advantage MA Development Balanced Budget Act Medicare + Choice Part C begins Medicare Part D 2006

Since managed care plans began to provide services to some Medicare beneficiaries in the 1980s, managed care has experienced a rapid growth. Enrollment Growth

Figure 2. Enrollment in Medicare Advantage Plans, by Plan Type,

Because the same hospitals usually serve both MA and TM beneficiaries, the increasing enrollment in MA plans also raises the concerns that whether changes in care induced by the MA program may “spill over” to care delivered to those who remain in the traditional fee-for-service (FFS) plans. This issue is extremely important to policy makers because any spillover effects of MA program to traditional Medicare spending or utilization have a direct implications for designing an efficient MA program.

Research Questions 1.How the quality of traditional Medicare changed in recent years? 2.Whether there is spillover effect from the penetration and competition of HMOs, PPOs and PFFS to the traditional fee-for-service sector?

2.Institutional Background Medicare is the federal health insurance program created in 1965 for all people age 65 and older, regardless of income or medical history, and now covers over 50 million Americans. In 2012, Medicare spending accounted for 16% of total federal spending and 21% of total national health spending.

The Medicare Advantage (MA) program was originated with the Tax Equity and Fiscal Responsibility Act (1982), and the rules to implement risk-based contracting were completed in Medicare uses formal risk adjustment, setting a per-member-per- month payment for each beneficiary, and Part C plans were paid by capitation setting at 95 percent of expected Fee for Service (FFS) spending in the beneficiaries’ county.

In order to reduce Medicare spending, the Balanced Budget Act (BBA) broke the direct link between the growth in county FFS spending and Medicare managed care payment, and the plans were paid the highest of three annual rates per beneficiary per month: (1)a minimum floor payment that began at $367 per month and was to be adjusted annually (floor rate was increased by its estimate of the current year’s national growth rate of Medicare fee-for-service spending minus a statutory reduction of 0.5 percentage point through 2002); (2)a 2 percent increase from the county’s prior year rate; (3)a blend of county-specific and national average rate, only if a so-called budget-neutrality condition was met.

To solve the problem of decreasing plan participation and declining enrollment in MA plans, the Republican-led congress passed the 2003 Medicare Modernization and Improvement Act (MMA) and made it effective March 2004 to increase payments across all areas. Under MMA, Medicare calculated a benchmark based on the highest of four amounts: (1)an urban or rural floor payment; (2)100 percent of risk-adjusted traditional Medicare FFS spending in the county (calculated using a five-year moving average lagged three years); (3)a minimum update over the prior year rate of 2 percent or traditional Medicare’s national expenditure growth rate, whichever was greater; (4)a blended payment rate update.

Medicare Payment as Percent of FFS Spending Source: Medicare Payment Advisory Committee, March 2010.

3.Literature Review Mechanisms of Spillover Effects Spillover Effect MA Penetration Spillover Effect MA Competition Limitations Contributions

Mechanisms of Spillover Effects Penetration: (1)Negative 1. Difficulties in accessing care. 2. Investment in infrastructure 3. Financial and administrative burdens on providers (2) Positive Practice patterns mechanism Competition An increase in HMO competition will increase the adoption of high technology.

System-Wide Expenditures Gaskin and Hadley (1997) Study nonfederal hospitals in the 84 largest MSAs in the country for the period Hospitals in areas with high rates of HMO penetration had a slower rate of growth (8.3%) in expenses than hospitals in low penetration areas (11.2%)

Traditional FFS Spending Baker (1997) Uses county- and metropolitan statistical area-level data. Medicare FFS expenditures are concave in market share, reaching a maximum at HMO market share between 0% and 10% and decreasing thereafter. Chernew, DeCicca and Town (2008) Use data from the annual Cost and Use files of the Medicare Current Beneficiary Survey (MCBS) for the years 1994–2001 Description of the contents A 1% point increase in county-level Medicare HMO penetration is associated with nearly a 1% reduction in individual-level annual spending by fee-for-service enrollees.

Quality Indicators Input Process Output The number of specialists Adoption some specific technologies like MRI, Hospital staffing levels Length of stay Number of tests performed Access to care Admissions for conditions that could be prevented through timely and effective Effectiveness of care Patients’ satisfaction with care Readmission rate Mortality rate

System-Wide Quality Blendon et al. (1998) Uses the data from a survey conducted in % of Americans believe that managed care decreases the quality of care Mobley and Magnussen (2002) Examine managed care penetration affect hospital efficiency related to excess staffing in California hospitals in 1995 Do not find a significant relationship between managed care penetration and nurse staffing ratios Hueston and Sutton (2000) Use national birth certificate data for 1996 HMO penetration is unlikely to influence national cesarean section rates.

System-Wide Quality Escarce et al. (2006) Use six medical conditions as quality indicators in California, New York, and Wisconsin for the period of 1994 to 1999 Higher HMO penetration was associated with lower mortality rate in California but higher mortality rate in New York. Baker and McClellan (2001) Analyze a cohort of cancer patients with a new diagnosis of cancer in 1992–94 Managed care is associated with increased diagnosis rates, and could well indicate better screening and better preventive care.

Spillover Effect on FFS Beneficiaries Meara et al. (2004) Use a sample of 206,450 Medicare beneficiaries included in the Cooperative Cardiovascular Project (CCP) An increased market share of managed care at the county level is negatively related with use of coronary angiography among AMI patients with traditional Medicare plans Heidenreich et al. (2002) Examine the care of 112,900 fee-for-service Medicare beneficiaries who were admitted with an acute myocardial infarction between February 1994 through July 1995 Patients with FFS care living in areas with high managed care market share were more likely to be treated with beta-blockers and aspirin. Keating et al. (2005) Study a sample population who were diagnosed with breast or colorectal cancer during An increase in the market share of managed care has limited or no effect on quality of care received by patients in fee-for-service sector.

Spillover Effect from Competition Shen et al. (2010) Examine trends in hospital costs and revenues with the period of 1994 to 2005 A higher HMO concentration will lead to lower hospital revenue. Mukamel et al. (2001) Use 1990 data for 1,927 hospitals in 134 metropolitan statistical areas (MSAs). HMO penetration is negatively associated with 30-day postadmission mortality rate. HMO competition have a marginally negative significant relationship with the mortality rate,

Research Gaps 1.Most of the literature relies on data before MMA 2003, limiting the applicability of their finding to the current policy context. 2.Most study only included information about HMOs. 3.Most studies have been unable to address the adverse selection problem 4.Unobserved heterogeneity may make the estimation biased.

Contributions 1. I use more recent data than prior studies. 2. By using the MCBS data, I can calculate hospital-acquired infection and 30-day readmission as the quality measure. 3. The analysis of market penetration and competition is conducted at MSA level, which is a better estimate of market compared to county level. 4. The data contain information on area characteristics and economic characteristics like unemployment rate, which allows careful control of market structure and economic fluctuation. 5. I include both the penetrations of HMOs and PPOs considering the expansion trend of PPOs in recent years.

4.Data and Methodology Data Recourses: MCBS CMS ARF My study period is from 2006 to 2009, a period of time concurrent with the introduction of part D and regional PPOs, and before the implementation of ACA. This was a period of a fast growth occurred in MA plans enrollment, changes in many features of managed care. The unit of observation is the individual, and hospital and MA market fixed- effects are included to remove bias that might result from time-invariant unobserved heterogeneity across hospitals and counties.

Basic model

Descriptive Statistics VariableMeans.e.MinMaxN HMO penetration rate (county level) PPO penetration rate (county level) RPPO penetration rate (county level) PFFS penetration rate (county level) HMO payment rate (county level) PPO payment rate (county level) RPPO payment rate (county level) PFFS payment rate (county level) HMO competition HHI (MSA level) PPO competition HHI (MSA level) RPPO competition HHI (MSA level) PFFS competition HHI (MSA level)

County Level Variable Summary VariableMeanStd.MinMax unemployment rate population density per square mile percent of male percent of White percent of African American Median household income poverty rate % the old over % Medicaid eligibles of year mortality rate of No. of hospital beds per 1,000 pop

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