State Regulation and
Hospital Costs
John J. Antel, Robert L. Ohsfelt, Edmund R. Becker
The Review of Economics and Statistics
Vol. 77, No. 3 (Aug. 1995), p. 416 – 422
presented by Susanne Buesselmann, April 2004
Purpose of the Paper
This paper analyzes the hospital regulation experience of
state and federal governments over the last 20 years.
They tried to contain hospital costs through various
regulations on both state and federal level.
Three measures of state-level average hospital costs are
analyzed as follows:
1. Cost per patient day
2. Cost per admission
3. Cost per capita
Data: 48 continental states, from 1968 to 1990
Earlier Studies
Two serious problems are suggested with past studies:
1. Omitted variable bias
They affect both state-level hospital costs and states’
regulatory decision; state hospital cost levels may
affect states’ incentive to regulate;
2. Limited recognition of regulatory interactions
Because of the long data panel many different
regulatory program effects could have been
estimated;
Early studies also show an overestimation of regulatory
effectiveness, particularly with regard to industryspecific price controls or rate regulation.
They generally conclude that only rate regulation
controls costs.
Historical Background
1960s
Adoption of Certificate of Need (CON) by a few states
1970s
Adoption of broad-based mandatory rate-setting programs by
a few states; implementation of investment restrictions by
many states and federal government
Mid-70s
Most states adopted CON after the passage of Section 1122
of the Social Security Act Amendments (1972)
1971 –
1974
Hospital prices were controlled by the Nixon Economic
Stabilization Program (ESP)
1974
National Health Planning Act
1980s
Some states repealed CON regulation following a decrease
in federal support and repeal also the National Health
Planning Act
1984
Medicare implemented a prospective payment system
By 1980s All 50 states had some form of CON or Section 1122 review
Social Security Act 1972
Aim: Control of medical procedures
- Established the Professional Standards Review
Organizations (PSRO) – controlled the utilization of
hospital services
- The federal government instituted investment
regulation with Section 1122 (Medicare and Medicaid
cost reimbursements for expanding hospitals without
prior approval could be denied)
→ Certificate of Need
- Replaced by Peer Review Organizations (PROs) as a
part of the new Medicare prospective payment
system
Nixon’s ESP 1971 - 1974
Focus: Obtaining some sense of the costs and overall
economic implications of major new regulations
Regulatory agencies were required to prepare
inflationary impact statements for all major rules
→ first step towards efficiency of regulations
General wage and price control with two characteristics:
1) General price controls covered hospital wages and
other input prices
2) Since the controls were temporary, hospitals’ longterm financial prospects were less threatened –
hospitals had less incentive to adjust or evade
Regression
ln COSTit  1PRATEit   2CON it  3 S1122it   4 PSROM it
 5 PPSM it   6 ESPit   7 X it  8 ln( t )  f i   it
where
X = hospital output demand and input price measures
t = log time trend
it
fi = state-level fixed effects
Regulation Variables
PRATE
Measure of rate-setting regulation
CON
Dummy variable indicating CON review
S1122
Dummy variable indicating Section 1122 review
PSROM
Measures the influence of PSROs as
percentage of hospital revenue subject to PSRO
reviews
PPSM
Measures joint influence of prospective payment
system as percentage of hospital revenue
subject to implementation in 1984
ESP
Dummy variable for Nixon’s program
Control Variables
X variables stand for hospital demand and input prices.
Demand depends on:
INCOME State per capita real income
REIMB
Percentage of revenue from third-party
payers
POP65
Percentage of population within a state
older than 65 years
The percentage of the population living in metropolitan
areas (METRO) proxies hospital labor and land prices.
Considerations
1) Regulation variables: three year moving averages
(t, t-1, t-2); allows the incremental impact of regulations
as institutions gradually respond to the new rules.
2) Correlation: states with higher costs tend to regulate
more – the cost containment effects of regulatory
variables will be under-estimated (diverse bias
direction if higher state hospital costs dislike
regulation).
3) Does not rely on the comparison of costs in a single
year before and after the regulation → the influence of
transitory factors is limited.
Results Simple Regression I
Cost per Day
Cost per
Admission
Cost per Capita
PRATE
-0.0011
-0.0011
0.0007
CON
0.0438
0.0492
-0.0155
S1122
-0.0008
-0.0051
-0.1067
PSROM
-0.0004
-0.0002
0.0031
PPSM
0.0071
0.0063
0.0006
ESP
-0.1911
-0.1648
0.0272
INCOME
0.00002
0.00003
0.0001
REIMB
0.0044
0.0053
0.0144
POP65
-0.0147
0.0137
0.1021
METRO
0.0045
0.0044
0.0030
R2
0.8676
0.8921
0.6132
Variable
Results Simple Regression II
PRATE
Lower per day and per admission costs, no
statistically significant effect on per capita costs
CON
Higher per day and per admission costs, no
statistically significant effect on per capita costs
Lower per capita costs, ineffective in controlling
per day or per admission costs
S1122
PSROM Increased cost per capita, no statistically
significant effect on costs per day or admission
PPSM
Increased cost per day and per admission, no
significant effect on costs per capita
ESP
Lower per day and admission costs, no
statistically significant effect on per capita costs
Results with Interaction Variables I
Variable
Cost per Day
Cost per Admission
Cost per Capita
PRATE
-0.0050
-0.0033
0.0046
CON
0.0488
0.0582
0.0688
S1122
0.1943
0.1317
0.0991
PSROM
-0.0017
0.0004
0.0004
PPSM
0.0102
0.0084
0.0006
ESP
-0.1932
-0.1762
-0.0085
PRATE x CON
0.0051
0.0030
-0.0053
PRATE x S1122
-0.0010
-0.0012
0.0010
PRATE x PPSM
-0.000003
-0.00002
0.00003
PRATE x PSROM
-0.00001
0.00002
0.00002
CON x S1122
-0.0992
-0.0465
-0.2533
CON x PPSM
-0.0036
-0.0022
0.0035
CON x PSROM
0.0036
0.0010
0.021
S1122 x PSROM
-0.0042
-0.0040
-0.0008
Results with Interactions Variables II
• Standard F-Test supports the interactive model at the
5% level in the per day and per admission cost
regressions, and at the 10% level in the per capita
cost regression.
• PRATE and CON estimates are less significant for
the per admission and per day regressions.
• S1122 estimates are now positive and significant in
the per day and per capita regressions.
• Including interaction variables suggests some review
of hospital regulation effects on cost.
Results LSDV I
Variable
Cost per Day
Cost per Admission
Cost per Capita
PRATE
0.0018
0.0019
0.0051
CON
0.0331
0.0106
0.0327
S1122
0.1704
0.1432
0.0261
PSROM
-0.0013
-0.0013
0.0035
PPSM
0.0090
0.0089
0.0056
ESP
-0.1101
-0.1525
-0.0536
PRATE x CON
-0.0024
-0.0023
-0.0042
PRATE x S1122
0.0004
0.0002
0.0009
PRATE x PPSM
-0.0001
-0.0001
-0.0001
PRATE x PSROM
-0.00004
-0.00003
-0.00001
CON x S1122
-0.0296
-0.0047
0.0135
CON x PPSM
-0.0021
-0.0003
0.0023
CON x PSROM
0.0027
0.0030
-0.0002
S1122 x PSROM
-0.0031
-0.0032
-0.0003
Results LSDV II
• Only looking at the non-interactive coefficient estimates
suggest that – excluding ESP – no form of regulation
operation alone controls hospital costs.
• Cost decreasing effects of Nixon’s Act seems anomalous,
but since they are not permanent, they are said to be
irrelevant.
• Some cost increases can be limited with regulation
interaction.
• Standard F-Tests reject the models without state dummy
variables at the 1% level for each cost.
→ The state dummy variable model suggest a substantial
revision of our understanding of how rate regulation
affects hospital costs.
Results Control Variables
• Most of the output demand and input cost coefficient
estimates are consistent with expectations while the
income and reimbursement coefficients are of
particular economic and policy significance.
• A higher third-party payment leads to a rise in demand
for hospital services.
• Hospital services are a normal good (LSDV
coefficients are small, but generally positive).
• Small values of income elasticity (0.007 – 0.45)
indicates that increasing income has only a small
effect in driving up hospital costs.
New Medicare System
Here: Medicare increases all hospital costs – contrary to
earlier studies;
But panel data covers the complete implementation of the
Medicare system!
Sloan et al. (1988): Higher daily costs are due to the
increased average acuity of patients as the new Medicare
system limits hospital utilization by less acutely ill patients.
Also higher effect on per capita costs!
That implies either that the Medicare system cannot
effectively restrict utilization, or that other unmeasured
factors are associated with PPSM accounting for the higher
costs.
Interactions of Regulations
Per capita cost regressions imply that CON regulation in part
compensates the higher per capita costs associated with rate
regulation.
While rate regulation alone does not reduce costs, it may
limit the cost increasing effects of the new Medicare system
– per day and per admission state dummy regressions
suggest that rate regulation moderates the cost increases
due to the new Medicare system.
Two possibilities:
1. State rate controls covering all patients may limit cross
subsidization of Medicare recipients by other health
care consumers
2. Rate regulating states may be better able to adjust to
the new Medicare system
Conclusion
•
•
•
•
Limited effectiveness of hospital cost regulation
No single form of hospital regulation implies lower costs
Regulations are often associated with higher costs
Neither federal utilization controls nor state and federal
hospital investment restrictions have lowered hospital
costs
• Regulations working together may in some instances
limit cost increases
• Indication of state-specific heterogeneity
• Future studies should focus on issues of regulatory
evasion, interactions of regulations, and possible
regulatory redistribution of hospital costs