L/O/G/O
Spillover Effect of Medicare Advantage
Plans: How the Penetration and
Competition of MA Plans Affect the
Quality of Medicare
Qianwei Shen
Wayne State University
Overview
1. Introduction
2. Institutional Background
3. Literature Review
4. Data and Methodology
5. Results
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).
plans
HMOs
PPOs
PFFS
SNPs
Other plans
payment
purposes
local plans
regional plans
MA Development
1985
1997
2003
2006
2010
Enrollment Growth
Since managed care plans began to provide services to some Medicare
beneficiaries in the 1980s, managed care has experienced a rapid
growth.
16000000
14000000
12000000
Others
PFFS
10000000
Regional PPOs
8000000
Local PPOs
6000000
HMOs
4000000
2000000
0
2006
2007
2008
2009
2010
2011
2012
2013
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-permonth 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
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 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
•
Length of stay
• Number of tests performed
• Access to care
• Admissions for conditions
that could be prevented
through timely and effective
Input
Process
Output
•
•
•
•
• The number of specialists
• Adoption some specific
technologies like MRI,
• Hospital staffing levels
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 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 fixedeffects 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:
𝑌𝑖𝑗𝑡 = 𝛼𝑖 + 𝑃𝑒𝑛𝑒𝑡𝑟𝑎𝑡𝑖𝑜𝑛𝑗𝑡 𝛼1 + 𝐶𝑜𝑚𝑝𝑒𝑡𝑖𝑡𝑖𝑜𝑛𝑗,𝑡 𝛼2 + 𝑋𝑖𝑡 𝛼3 + 𝑍𝑗𝑡 𝛼4 + 𝜀𝑖𝑗𝑡
𝑌𝑖𝑗𝑡 is an indicator = 1 if the beneficiary i had a hospital readmission or
infection in area j in year t;
𝑃𝑒𝑛𝑒𝑡𝑟𝑎𝑡𝑖𝑜𝑛𝑗𝑡 is a vector the MA penetration in area j in year t;
𝐶𝑜𝑚𝑝𝑒𝑡𝑖𝑡𝑖𝑜𝑛𝑗,𝑡 is a vector of the MA competition in area j in year t;
𝑋𝑖𝑡 is a vector of individual characteristics including age, education, etc ;
𝑍𝑖𝑗𝑡 is a vector of area time varying characteristics (including measures of
area-level population demographics and economics conditions).
Descriptive Statistics
Variable
HMO penetration rate (county level)
Mean
s.e.
Min
Max
N
7615.59
21737.43
11
397804
2934
850.159292
1641.17
11
16915
2260
282.0223821683.8169197
11
10829
2502
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
0.157315
0.2525621
7
0.223050
0.2231077
2
0.466341
0.189864
9
0.101864
0.2577381
4
1387.6
4342
1
2934
1
2260
1
2502
1
4247
PPO penetration rate (county level)
RPPO penetration rate (county level)
PFFS penetration rate (county level)
1122.58
HMO competition HHI (MSA level)
0.7168124
PPO competition HHI (MSA level)
0.8131534
RPPO competition HHI (MSA level)
0.8798049
PFFS competition HHI (MSA level)
0.4783837
County Level Variable Summary
Variable
unemployment rate
population density per square mile
Mean
Std.
Min
Max
5.9371111
2.5345543
1.7
28.2
662.2584354
2923.44
1.5
70951.8
percent of male
0.4897536
0.0232641
percent of White
80.2587528
15.5395873
16.1
99
percent of African American
10.9821088
13.7395651
0.1
81.5
50092.07
12818.6
26131
114200
13.8831519
5.2170333
3.2
36.3
0.1320258
0.0331623
% 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
Median household income
poverty rate
% the old over 65+
0.3807298 0.8087335
0.0334605 0.3363838
0 42.010236
L/O/G/O
Thank You!
www.themegallery.com