An Evaluation of Hospital Capital Investment
after Balanced Budget Act
Background: Importance of hospital
capital investment
‰ Major, multi-year dollar spending
‰ Building, equipment and fixtures
‰ Enhancing organizational strategic position
- Expansion
- Operating efficiency
- Quality of care
Tae-Hyun “Tanny” Kim, MPH
Michael J. McCue, DBA
Virginia Commonwealth University
Department of Health Administration
Please do not quote or cite findings: they are preliminary.
Contact: kimth@vcu.edu
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Background: Basic facts about
recent trend
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Background: Basic facts in the
post-BBA period
‰ Minimal growth rate of aggregate capital
spending of hospitals during 1997-2001 (HFMA,
2004).
‰ BBA 1997 reduced Medicare payment by
$206 billion over five years (U.S. House, 2004)
‰ Continuously increasing average age of plant
for hospitals: 7.9 to 9.8 years during 19902001 (AHA, 2001)
‰ Hospital total margins and inpatient margins
declined significantly over five years after
1997 (MedPAC, 2004)
‰ BBA 1997 may have an influence on slowing
growth of capital expenditure by affecting
financial performance of hospitals
‰ Bond rating downgrades of hospitals
outnumbered upgrades between 1998 and
2002 by almost three to one (AHA, 2004)
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Importance of study
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Research Questions
‰ Overall, hospitals might have difficulty
funding capital projects in the post-BBA period
‰ Hospitals operating in different environment
may vary in their capital investment
‰ The study contributes further understanding
of capital investment in the hospital industry
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‰ What factors are associated with hospital
capital investment in the post-BBA period?
- How do market conditions influence capital
investment?
- Are operational characteristics associated
with capital investment?
- How are financial factors related to capital
expenditures?
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1
Hypotheses
Methods
‰ Hospitals located in higher market demand
will be more likely to have higher amount of
capital investment
‰ Study design: a pooled cross-sectional
time-series design
‰ Study period: 1998-2002
‰ Hospitals with higher complexity and
limited capacity will be more likely to have
higher amount of capital investment
‰ Data: CMS, AHA, and ARF database
‰ Sample: non-federal, short-term general
U.S. hospitals (16,520 hospital-years)
‰ Hospitals with higher amount of financial
sources will be more likely to have higher
amount of capital investment
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Measurement
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Measurement
‰ Independent variables:
‰ Dependent variable: capital
purchase for buildings, fixtures and
moveable equipment during a fiscal
year
- Market factors (county level)- number of
physicians, population size, % of population over
65, per capita income, and unemployment rate
- Operational factors - bed size, number of total
services, case-mix index and occupancy rate
- Financial factors - days cash on hand, cash flow,
and debt ratio
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Descriptive Statistics
Variable
Capital investment ($1000s)
Ln(capital investment)
Market factors
MDs per population 1,000
Ln(population)
% Population over 65
Ln(per capita income)
Unemployment rate (%)
Operational factors
Beds
Number of services
Occupancy rate
Case-mix
Financial factors
Days cash on hand
Cash flow
Debt ratio
Mean
5,614
10.932
Descriptive Statistics (cont.)
Std. Dev.
13,700
6.603
2.201
11.866
0.135
10.141
5.080
1.960
1.761
0.037
0.271
2.396
189.32
33.531
0.463
1.295
179.78
13.436
0.213
0.250
41.457
13.661
0.836
10
74.669
249.83
8.063
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Variable
Control factors
Herfindahl Index
Ownership
Not-for-profit
For-profit
Public
System affiliation
Teaching hospital
Urban
Region
North East
Central
South
West
Mean
Std. Dev.
0.289
0.267
0.618
0.157
0.225
0.562
0.280
0.600
0.486
0.364
0.418
0.496
0.450
0.489
0.153
0.266
0.384
0.181
0.361
0.442
0.486
0.385
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Results
Methods
Table 2: OLS regression with robust standard errors
Dependent Variable: Log of capital investment
Independent Variables
‰ Multiple regression
‰ Hospital & year fixed-effect model
‰
CIit = αi + γ t + a1MKTit + a2OPERit−1 + a3FINit−1 + εit
Coef.
Std. Err.
P>t
MDs/capita
-0.043
0.046
0.349
Ln(population)
-0.085
0.085
0.313
% Population over 65
-4.078 *
2.019
0.044
Ln(per capita income)
0.530
0.398
0.183
Unemployment rate
0.006
0.030
0.850
Beds
0.002 **
0.001
0.000
Occupancy rate
1.733 **
0.382
0.000
No. of services
0.033 **
0.007
0.000
Case-mix index
1.100 **
0.386
0.004
Days cash on hand
13
0.001
Cash flow
0.0002 *
Debt ratio
-0.086
0.001
0.082
0.0001
0.035
0.052
0.098
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R-squared: .1451
* Statistically significant at the 5 percent level ** Statistically significant at the 1 percent level.
Results
Summary of results
Table 2: OLS regression with robust standard errors
Dependent Variable: Log of capital investment
Control Variables
Coef.
Std. Err.
P>t
Herfindahl index
0.313
0.245
0.201
For-profit
-0.694
0.497
0.163
Public
-0.549 **
0.167
0.001
0.058
0.134
0.667
FP*SYS
-0.371
0.541
0.492
Teaching
System affiliation
-0.099
0.172
0.563
Urban
0.074
0.186
0.689
Northeast
1.089 **
0.182
0.000
Central
0.753 **
0.165
0.000
West
0.182
0.213
0.393
yr2000
-0.626 **
0.091
0.000
yr2001
-2.267 **
0.133
0.000
3.864
0.084
_cons
6.685
‰ Operational factors appear to be significant:
number of beds, occupancy rate, case-mix
index and number of services were positively
associated with capital investment
‰ Cash flow was positively associated with
capital investment
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Discussions/implications
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Discussions/implications
‰ In the post-BBA period, internal aspects (e.g.,
operational factors) may have been more
important than external factors (e.g., market
factors) in hospital capital investment
- Hospitals may have not been able to or needed
to incorporate market conditions in their
investment decision
- However, operational characteristics reflect
market demand to some extent
- The impact of market factors at the MSA level
may be different
‰ Overall, market factors were not significant
(except % of elderly)
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‰ The results partially support a growing
literature suggesting that availability of internal
funds is a significant factor affecting investment
activity
‰ Increase in debt may act as a monitoring
device rather than a facilitating factor in the postBBA period
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