L/O/G/OL/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. IntroductionThe 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

HMOsPPOsPFFSSNPs

Other plans

Affordable C

are Act

Medicare M

odernization Act

Medicare A

dvantage

MA Development

Balanced B

udget Act

Medicare + C

hoice

Part C

begins

1985 1997 2003 2010M

edicare 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

2006 2007 2008 2009 2010 2011 2012 20130

2000000

4000000

6000000

8000000

10000000

12000000

14000000

16000000

Others

PFFS

Regional PPOs

Local PPOs

HMOs

Figure 2. Enrollment in Medicare Advantage Plans, by Plan Type, 2006 -2013

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.

1985-1997

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 1985.

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.

1997-2003

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 .

2003-2010

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

CompetitionAn 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 1985-1993.

• 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 1986-1990 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 1997

• 45% 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

1993-1999.• 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 problem4. 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

My basic model specify the hospitalization of beneficiary I that lies in a hospital located in county c, as a function of MA penetration and competition, health and demographic characteristics, and county characteristics:

is an indicator = 1 if the beneficiary i had a hospital readmission or infection in area j in year t;

is a vector the MA penetration in area j in year t;

is a vector of the MA competition in area j in year t;

is a vector of area time varying characteristics (including measures of area-level population demographics and economics conditions).

Descriptive StatisticsVariable Mean s.e. Min Max N

HMO penetration rate (county level) 7615.59 21737.43 11 397804 2934

PPO penetration rate (county level) 850.159292 1641.17 11 16915 2260

RPPO penetration rate (county level) 282.0223821683.816919

7 11 10829 2502

PFFS penetration rate (county level) 1122.58 1962.68 11 33718 4250

HMO payment rate (county level) 687.6594177 64.4093289 499.92 1393.81 3160

PPO payment rate (county level) 716.4260727 72.4912766 492.14 1092.54 2228

RPPO payment rate (county level) 742.0885406 82.2517377 547.43 1207.54 2412

PFFS payment rate (county level) 715.0885767 80.7733866 535.88 1387.6 4342

HMO competition HHI (MSA level) 0.7168124 0.25256210.157315

7 1 2934

PPO competition HHI (MSA level) 0.8131534 0.22310770.223050

2 1 2260

RPPO competition HHI (MSA level) 0.8798049 0.1898640.466341

9 1 2502

PFFS competition HHI (MSA level) 0.4783837 0.25773810.101864

4 1 4247

County Level Variable Summary

Variable Mean Std. Min Max

unemployment rate 5.9371111 2.5345543 1.7 28.2

population density per square mile662.2584354 2923.44 1.5 70951.8

percent of male 0.4897536 0.0232641 0.3807298 0.8087335

percent of White 80.2587528 15.5395873 16.1 99

percent of African American 10.9821088 13.7395651 0.1 81.5

Median household income 50092.07 12818.6 26131 114200

poverty rate 13.8831519 5.2170333 3.2 36.3

% the old over 65+ 0.1320258 0.0331623 0.0334605 0.3363838

% Medicaid eligibles of 65+ 4277.28 14418.51 13 354325

3-year mortality rate of 65+ 0.0452781 0.0076606 0.0165837 0.11561

No. of hospital beds per 1,000 pop 2.7559088 3.5411678 0 42.010236

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