Healthy Marketplace Index:
Hospital Concentration Index
Comparing inpatient hospital concentration measures across geographies and medical diagnoses
In this issue brief, the Health Care Cost
Institute (HCCI), reports inpatient hospital concentration measures. This
report, the second in a series, was
funded by the Robert Wood Johnson
Foundation as part of the Healthy Marketplace Index (HMI) project. As with
all the HMI measures, the concentration measures were calculated for 61
Core-Based Statistical Areas (CBSAs).
The analysis population includes employer-sponsored insurance (ESI)
members under age 65 for 2013.1
The Herfindahl-Hirschman Index
(HHI) is a commonly used measure of
market concentration and is used as
part of the HMI to measure inpatient
hospital concentration.2 In this context, the HHI summarizes how inpatient admissions within a CBSA are
distributed among inpatient facilities.
Hospital concentration measures are
reported as a means of identifying
areas (geographic or diagnostic) for
which additional competition analyses
could be directed to examine cost and
quality drivers or to produce policy
recommendations.3 Higher concentration is associated with less competitive markets, and vice versa, and competition has been shown to have effects on both price and quality.4
HHIs based on total admissions.5 This
suggests that, in some areas, hospitals
may be concentrated for certain types
of admissions, but not others – which
could have important policy implications. It is important to note, however,
that measures of hospital concentration are dependent on the definition of
the geographic size, patient mix, type
or hospital, and type of service. The
measures reported in this brief provide a starting point for developing
additional analyses of concentration
and competition in a particular CBSA.
Index Calculation
An HHI is calculated by summing the
squared shares of all competitors in a
market and is then commonly multiplied by 10,000 for reporting purposes. A maximum HHI value of 10,000
would occur in a monopolistic market
where a single hospital had a 100%
share of the patients. Smaller HHI values indicate markets with less concentration. For example, if 4 hospitals
each have a 25 percent share of the
admissions in a market, the HHI
would be 2,500 (10,000 x
(0.252+0.252+0.252+0.252)).
Issue Brief #14
May 2017
KEY FINDINGS
Market concentration is substantially higher when measured at
the system level rather than the
hospital level
The average system-level concentration
was 86% larger than the average hospital-level concentration.
High concentration among specific types of diagnoses was associated with high overall concentration
Strong correlations were found between
concentration measured by all admission
and concentration measured by admissions for specific diagnostic categories.
share of admissions is calculated for the system rather than each hospital. In both the
hospital-level HHI and system-level HHI, the
shares of admissions sum to 100% and the
HHI is reported as the sum of squared shares
multiplied by 10,000.
Results
HOSPITALS VERSUS SYSTEMS
Table 1 presents descriptive statistics of the
CBSA-level inpatient hospital characteristics.
In this brief, we report HHIs for two
Consistent with the large variation in CBSAdifferent units of analysis for each
level population size, there was large variaOverall, we found that approximately CBSA. One HHI is calculated at a hospition in the number of admissions from the
76% of hospitals in our study were
tal level, using shares of admissions
study CBSAs.6 The average number of admisaffiliated with a hospital system, and, from each CBSA to every hospital. This
sions was 11,751, but admissions among the
on average, 81.90% of admissions
approach treats each hospital as inde- middle 50% of the CBSAs in the study
were to system hospitals. The average pendent.
ranged from 2,557 (25th percentile) to
HHI calculated for hospital systems
15,670 (75th percentile). Across all of the
(2,969) was nearly 50% higher than
The second HHI is calculated at a hos- CBSAs, an average of 89.02% of admissions
the average hospital-level HHI. In gen- pital system level. If a hospital is not
were to hospitals located within the CBSA
eral, we also found that the HHIs
part of a system, the share is equivathat the patient resided in. Moreover, in 45
based on only pregnancy and childlent to the hospital level share. How- of the 61 CBSAs (75%), fewer than 15% of
birth admissions or only newborn and ever, for hospitals within a CBSA that
admissions occurred at a hospital outside
neonate admissions were higher than are part of the same system, a single
the patient’s CBSA.
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Table 1. CBSA-level Inpatient Admission Summary Statistics
Number of admissions Percent admissions to
per CBSA
hospital within CBSA
Average
(Standard Deviation)
25th Percentile
50th Percentile
75th Percentile
11,751
(14,655)
2,557
5,194
15,670
Percent of hospitals
with a system
affiliation
Percent of admissions
to hospitals with
system affiliation
76.01
(4.67)
73.62
76.73
78.91
81.90
(15.69)
74.35
85.63
93.14
89.02
(10.23)
85.71
94.13
95.52
Source: HCCI, 2017.
Among all of the hospitals studied, there
was minimal variation in the percentage
of hospitals affiliated with a hospital
system. On average, approximately 76%
of hospitals were affiliated with a system, and 81.90% of all admissions were
to system hospitals. In half of the CBSAs,
fewer than 15% of admissions were to
non-system hospitals, even though over
20% of hospitals were not affiliated with
a system in at least three-quarters of the
CBSAs. Note, the percentage of admissions to system affiliated hospitals was
larger, on average, than the percentage
of system hospitals.
CBSA-LEVEL HHIS
Summary statistics for the hospital and
system-level HHIs are presented in Table 2. The average hospital and system
HHIs were 1,984 and 2,969, respectively. The averages and 50th percentiles
were similar in magnitude within both
sets of HHI measures. Although the system-level HHIs were larger overall, the
variations in the two HHI measures
were also similar. For example, the interquartile ranges (IQR), a common
measure of variability displaying the
difference between the 75th and 25th
percentiles, were similar across both
measures – differences of approximately a CBSA with 3 hospitals, two with 48%
1,700.
shares and one with only a 4% share (an
HHI of 4,624).8
Higher HHIs imply more concentrated
markets and are generally associated
The CBSA-level hospital and system
with less competition.7 As part of the
HHIs are presented in Table 3. Hospital
HMI specifically, higher HHIs indicate
admission related descriptive statistics
that larger percentages of a CBSA’s adare also presented in Table 3, including
missions occurred among fewer hospitotal admissions, the percent of hospitals or systems. The higher system-level tals that are affiliated with systems, and
HHIs imply that inpatient services are
the percent of admissions to hospitals
more concentrated at the system level
that are affiliated with systems.
than the hospital level. In other words,
systems’ shares of admissions account
Although the summary statistics prefor larger shares of total admissions.
sented in Table 2 show that half of HHIs
This is consistent with the fact that
differed by 1,700 or less (the hospital
there are relatively fewer systems than and system HHIs had IQRs of 1,728 and
hospitals and the majority of hospitals
1,696, respectively), there were both
are associated with systems (see Table
high and low outliers. For example, the
1).
hospital HHIs range from a minimum of
241 in New York-Newark-Jersey City,
As a means of measuring how concenNew York-New Jersey-Pennsylvania to a
tration increases at the system-level
maximum of 5,887 in Greensboro-High
compared to the hospital level, sumPoint, North Carolina – a difference of
mary statistics of the ratio of system to 5,646 (Table 3). The difference between
hospital HHIs are also presented in Ta- the minimum system HHI (619 in New
ble 2. On average, the system HHI was
York-Newark-Jersey City, New York86% larger (1.86) than the hospital HHI. New Jersey-Pennsylvania) and the maxiThis is nearly analogous to the differmum (7,477 in Cape Coral-Fort Myers,
ence between a CBSA with 4 hospitals,
Florida) was 6,858.
each with an equal share of 25% of admissions (an HHI of 2,500) compared to
Table 2. CBSA-level HHI Summary Statistics
Average
(Standard Deviation)
25th Percentile
50th Percentile
75th Percentile
Hospital HHI
System HHI
Ratio of System to Hospital
1,984
(1,226)
1,045
1,819
2,773
2,969
(1,340)
1,960
3,040
3,656
1.86
(0.92)
1.22
1.49
2.15
Source: HCCI, 2017.
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Table 3. CBSA-level HHIs and Inpatient Admission Descriptive Statistics
CBSA Name
Appleton, WI
Atlanta-Sandy Springs-Roswell, GA
Augusta-Richmond County, GA-SC
Austin-Round Rock, TX
Baltimore-Columbia-Towson, MD
Baton Rouge, LA
Beaumont-Port Arthur, TX
Boulder, CO
Bridgeport-Stamford-Norwalk, CT
Cape Coral-Fort Myers, FL
Charlotte-Concord-Gastonia, NC-SC
Charlottesville, VA
Chicago-Naperville-Elgin, IL-IN-WI
Cincinnati, OH-KY-IN
Colorado Springs, CO
Columbus, OH
Corpus Christi, TX
Dallas-Fort Worth-Arlington, TX
Dayton, OH
Deltona-Daytona Beach-Ormond Beach, FL
Denver-Aurora-Lakewood, CO
Des Moines-West Des Moines, IA
El Paso, TX
Green Bay, WI
Greensboro-High Point, NC
Hartford-West Hartford-East Hartford, CT
Houston-The Woodlands-Sugar Land, TX
Jacksonville, FL
Kansas City, MO-KS
Knoxville, TN
Hospital
HHI
3,174
744
3,011
1,303
617
2,773
2,835
2,384
1,183
2,967
1,440
4,409
385
1,112
3,865
1,722
2,481
335
2,338
1,221
726
4,373
2,296
2,900
5,887
1,819
447
2,015
757
1,601
Percent of
System
In CBSA
Admissions
hospitals affiliatHHI
admissions
ed with a system
4,023
1,495
3,040
3,783
1,318
3,341
3,040
2,464
1,750
7,477
3,440
4,440
1,001
1,412
3,916
4,029
3,683
1,656
3,120
3,266
2,955
4,710
4,731
3,120
6,275
2,652
1,938
3,031
1,623
3,134
1,248
35,684
2,557
12,419
14,366
1,962
2,015
1,726
5,571
3,137
8,106
1,242
41,242
22,681
2,601
16,337
1,827
48,257
5,061
2,283
15,670
3,428
2,217
2,140
2,617
5,887
34,006
9,551
12,053
3,361
72.76%
93.80%
94.99%
94.82%
92.87%
85.63%
86.55%
83.08%
75.50%
87.50%
93.97%
93.88%
96.18%
94.60%
88.35%
95.38%
73.13%
96.86%
92.85%
62.16%
89.44%
96.47%
96.39%
90.75%
85.71%
87.96%
95.52%
95.16%
96.37%
93.78%
74.00%
75.45%
69.77%
75.00%
72.80%
71.11%
81.94%
78.38%
65.90%
82.14%
82.96%
80.43%
75.46%
71.79%
78.95%
76.73%
76.64%
74.18%
76.79%
80.77%
76.42%
77.92%
78.33%
81.67%
85.06%
67.39%
72.74%
81.11%
74.90%
80.95%
Percent of
admissions to
hospitals with
system affiliation
91.43%
92.99%
82.87%
95.95%
68.51%
76.50%
99.01%
30.88%
64.73%
95.57%
92.96%
98.95%
84.02%
63.30%
96.27%
91.67%
96.55%
89.11%
53.49%
71.40%
88.98%
98.10%
93.14%
58.64%
93.85%
82.95%
95.78%
95.99%
74.35%
71.62%
Source: HCCI, 2017.
Note: Table continues.
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Table 3. CBSA-level HHIs and Inpatient Admission Descriptive Statistics (cont.)
CBSA Name
Lakeland-Winter Haven, FL
Lexington-Fayette, KY
Louisville/Jefferson County, KY-IN
Memphis, TN-MS-AR
Miami-Fort Lauderdale-West Palm Beach, FL
Milwaukee-Waukesha-West Allis, WI
Minneapolis-St. Paul-Bloomington, MN-WI
Nashville-Davidson--Murfreesboro--Franklin, TN
New Haven-Milford, CT
New Orleans-Metairie, LA
New York-Newark-Jersey City, NY-NJ-PA
North Port-Sarasota-Bradenton, FL
Norwich-New London, CT
Oklahoma City, OK
Omaha-Council Bluffs, NE-IA
Orlando-Kissimmee-Sanford, FL
Palm Bay-Melbourne-Titusville, FL
Peoria, IL
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD
Phoenix-Mesa-Scottsdale, AZ
Portland-South Portland, ME
Providence-Warwick, RI-MA
Racine, WI
San Antonio-New Braunfels, TX
Sheboygan, WI
St. Louis, MO-IL
Tampa-St. Petersburg-Clearwater, FL
Trenton, NJ
Tucson, AZ
Tulsa, OK
Washington-Arlington-Alexandria, DC-VA-MD-WV
Hospital
HHI
2,799
2,538
1,754
2,878
331
977
631
1,088
2,812
1,441
241
2,023
2,433
1,336
1,668
3,234
2,554
4,888
457
603
2,443
1,045
2,187
1,285
2,693
3,769
928
1,807
2,290
2,298
465
Percent of
System
In CBSA
Admissions
hospitals affiliatHHI
admissions
ed with a system
2,888
3,195
3,157
3,517
1,104
1,986
2,173
2,321
3,118
1,960
619
2,648
3,059
1,887
4,422
4,036
4,673
5,031
837
2,684
2,483
1,953
3,270
1,995
3,656
5,884
1,774
2,144
2,470
3,144
1,156
3,149
3,870
15,233
5,315
21,221
16,658
19,696
7,435
3,698
5,386
80,673
3,418
1,463
4,864
4,345
13,980
2,458
3,229
36,228
31,692
1,885
4,759
2,317
18,165
14,049
939
19,541
1,836
5,604
5,194
37,247
72.72%
95.84%
96.77%
95.26%
95.14%
96.83%
95.71%
96.58%
79.66%
94.13%
95.58%
85.08%
65.28%
94.82%
95.14%
94.28%
84.50%
94.61%
94.17%
96.52%
83.40%
87.75%
48.51%
97.19%
95.70%
71.25%
95.02%
69.99%
96.13%
95.23%
89.28%
79.44%
80.00%
78.04%
79.05%
76.97%
77.10%
71.52%
78.72%
72.73%
73.83%
71.14%
76.34%
68.52%
73.62%
75.89%
76.82%
79.61%
81.93%
75.35%
75.36%
58.44%
67.50%
78.87%
78.04%
78.70%
71.43%
78.91%
78.18%
77.52%
73.10%
76.05%
Percent of
admissions to
hospitals with
system affiliation
31.63%
80.28%
89.46%
96.35%
85.63%
74.25%
91.87%
89.29%
77.58%
62.55%
74.86%
58.31%
94.33%
84.00%
79.93%
98.71%
88.65%
87.58%
82.39%
98.33%
70.88%
80.31%
83.94%
79.31%
94.63%
92.86%
88.38%
62.20%
49.48%
92.63%
85.54%
Source: HCCI, 2017.
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The descriptive statistics in Table 3 provide additional context for interpreting
the HHIs. For instance, the percent of
admissions within the CBSA can be used
to focus further investigations of competition. In CBSAs with high HHIs and lower percentages of admissions within the
CBSA, there is likely one or two hospitals located outside of the CBSA that
draws a high share of admissions from
the CBSA. Thus, the competitive environment in these CBSAs may differ from
other CBSAs. The St. Louis, MissouriIllinois CBSA is an example of a CBSA
with this pattern of relatively a high HHI
and low percent of in-CBSA admissions.
The system HHI was 5,884 with only
77.25% of admissions within the St.
Louis CBSA. The HHIs and descriptive
statistics taken together provide a guide
to focus additional analyses.
tems had a larger presence. There were
some CBSAs that had relatively average
hospital HHIs and above average system
HHIs, such as Columbus, Ohio. The hospital HHI in Columbus was near the 50th
percentile (1,722), while the system HHI
was above the 75th percentile (4,029).
Alternatively, there were some CBSAs
with similar levels of concentration
among hospitals and systems. For example, Colorado Springs, Colorado had a
hospital HHI of 3,865 and a system HHI
of 3,916. Likewise, Boulder, Colorado
had a hospital HHI of 2,384 and a system HHI of 2,464.
HCCI CLAIMS MEASURES COMPARED
TO OVERALL HOSPITAL MEASURES
The HHIs based on the HCCI claims data
provide measures of the concentration
of admissions, but HCCI data does not
Comparisons of the hospital and system account for all admissions from a CBSA.
HHIs within a CBSA can also provide
To assess how the HHI measures reportinsight into whether competition occurs ed in this brief compare to the overall
at the hospital level, system level, or
hospital utilization from a CBSA, we also
both. This, in turn, can inform future
calculated hospital and system-level
policy and research. For example, the
HHIs using total admissions, hospital
hospital HHIs in Denver-Aurorabeds, and hospital discharges of MediLakewood, Colorado (726) and Phoenix- care patients from the hospitals includMesa-Scottsdale, Arizona (603) were
ed in each CBSA-level calculation. Correrelatively low compared to the other
lations of all of the HHI measures are
CBSAs in the study. Their system HHIs, presented in Table 4.
however, were respectively 2,955 and
2,684, which were relatively high, sugAt the hospital-level, the correlations
gesting system influence.
between HHIs based on HCCI claims and
total hospital admissions, hospital beds
The HHIs do not need to be outliers to
and Medicare discharges were all apidentify areas where one or a few sysproximately 0.7500 or higher. At the
system level, the correlations were
0.7925 or higher. This suggests that although HCCI data account for only a fraction of total inpatient hospital admissions from a CBSA, the distribution of
the admissions among hospitals and
systems is consistent with that of the
overall inpatient population.
The correlations table also shows the
correlation between hospital and system HHIs. The correlations of the hospital and system HHIs calculated with
HCCI data was 0.7864. This was only
slightly lower than the correlations between the hospital and system HHIs
calculated with total admissions, beds,
and Medicare discharges, 0.8412,
0.8785, and 0.8086, respectively. All
pairs of HHIs were highly correlated,
which implies that even though the system HHIs may be higher in general,
CBSAs with higher system-level HHIs
also tend to have higher hospital level
HHIs (and vice versa). This suggests that
there may be particular hospitals, even
within systems, that account for larger
shares of admissions. Due to hospitals
differing by size (i.e. number of beds), a
large hospital within a CBSA or system
will account for more admissions.
Therefore, the high correlations, while
informative, are not unexpected.
MAJOR DIAGNOSTIC CATEGORY SPECIFIC DIFFERENCES
Using the HCCI claims, we also calculated HHIs for subpopulations of admis-
Table 4. Correlations of Alternative Hospital and System HHIs
HCCI
Total
HCCI
Total
Hospital Hospital
Hospital
Hospital
System
System
Beds Medicare
Admission Admissions
Admission Admissions
HHI
HHI
HHI
HHI
HHI
HHI
HCCI Hospital Admission HHI
Total Hospital Admissions HHI
Hospital Beds HHI
Hospital Medicare HHI
HCCI System Admission HHI
Total System Admissions HHI
System Beds HHI
System Medicare HHI
1.0000
0.7993
0.7475
0.7831
0.7864
0.6817
0.6618
0.6508
1.0000
0.9895
0.9923
0.6411
0.8412
0.8615
0.8109
1.0000
0.9788
0.6127
0.8430
0.8785
0.8121
1.0000
0.9235
0.8256
0.8435
0.8086
1.0000
0.8298
0.7925
0.8203
1.0000
0.9890
0.9892
System
Beds
HHI
System
Medicare
HHI
1.0000
0.9729
1.0000
Source: HCCI, 2017.
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Table 5. Summary Statistics of CBSA-level System HHIs for Top 5
Major Diagnostic Categories
Average
(Standard Deviation)
25th Percentile
50th Percentile
75th Percentile
All
Admissions
MDC 5
MDC 6
MDC 8
MDC 14
MDC 15
2,969
(1,340)
3,006
(1,361)
2,847
(1,333)
2,789
(1,318)
3,464
(1,602)
3,659
(1,728)
1,960
3,040
3,656
2,140
2,907
3,659
1,910
2,717
3,369
1,855
2,742
3,298
2,205
3,405
4,383
2,315
3,743
4,668
Source: HCCI, 2017.
Note: The five most frequent MDCs were MDC 5: Diseases and Disorders of the Circulatory System, MDC 6: Diseases and Disorders of the Digestive System,
MDC 8: Diseases and Disorders of the Musculoskeletal System and Connective Tissue, MDC 14: Pregnancy Childbirth and the Puerperium, and MDC 15: Newborns & Other Neonates with Conditions Originating in Perinatal Period.
sions. We calculated system HHIs for the
five most common Major Diagnostic
Categories (MDCs) based on admissions
from the 61 CBSAs in the HMI project.
The top five MDCs made up 69% of the
total admissions and accounted for 63%
of the total dollars spent.9 The HHIs by
MDC provide insight into what particular types of services, if any, may influence overall hospital concentration. The
top 5 MDCs were MDC 5: Diseases and
Disorders of the Circulatory System,
MDC 6: Diseases and Disorders of the
Digestive System, MDC 8: Diseases and
Disorders of the Musculoskeletal System
and Connective Tissue, MDC 14: Pregnancy Childbirth and the Puerperium,
and MDC 15: Newborns & Other Neonates with Conditions Originating in
Perinatal Period.
the distributions of HHIs for MDCs 5, 6,
and 8 were generally similar to the distribution of system HHIs for all admissions. The HHIs for MDCs 14 and 15
were generally higher than the others.
For example, the average HHIs for MDCs
14 and 15 were respectively 17% and
23% higher than the average of HHI
based on all admissions. This implies
that fewer hospitals accounted for larger shares of admissions for those two
MDCs compared to all admissions in
general.
in the correlations presented in Table 6.
All of the HHI measures were highly
correlated, ranging from a minimum of
0.8337 (between MDCs 5 and 15) to a
maximum of 0.9793 (between MDCs 14
and 15). This suggests that within
CBSAs, if there was a higher (or lower)
all admissions HHI, there was likely
higher (or lower) concentration of MDC
specific admissions as well.
The CBSA-level system HHIs for the top
5 MDCs are presented in Table 7. In general, the HHIs by MDC were similar to
There was also more variability in the
the system HHIs calculated with all adHHIs for MDC 14 and MDC 15 with their missions – with higher HHIs for MDCs
IQRs being 2,177 and 2,353, respective- 14 and 15. However, examination of the
ly. The IQRs of the other 3 MDC specific HHIs by CBSA reveals numerous inHHIs and the all admissions HHI were
stances that do not follow the general
all between 1,443 (MDC 8) and 1,696
pattern. Identifying deviations from the
(All admissions).
general pattern is potentially useful in
Table 5 presents the distribution of
identifying areas to focus further invesCBSA-level system HHIs for the top 5
tigation, such as why is there a higher
The relationships between the CBSAMDCs. The summary statistics show that level MDC specific HHIs are summarized concentration of admissions for some
Table 6. Correlations of System HHIs for Top 5 Major Diagnostic Categories
All
Admissions
MDC 5
All admissions
MDC 5
1.000
0.9362
1.0000
MDC 6
MDC 8
MDC 14
MDC 15
0.9655
0.9252
0.9640
0.9255
0.9178
0.8535
0.8802
0.8337
MDC 6
MDC 8
MDC 14
MDC 15
1.0000
0.8980
0.9116
0.8562
1.0000
0.8869
0.8345
1.0000
0.9793
1.0000
Source: HCCI, 2017.
Note: The five most frequent MDCs were MDC 5: Diseases and Disorders of the Circulatory System, MDC 6: Diseases and Disorders of the Digestive System,
MDC 8: Diseases and Disorders of the Musculoskeletal System and Connective Tissue, MDC 14: Pregnancy Childbirth and the Puerperium, and MDC 15: Newborns & Other Neonates with Conditions Originating in Perinatal Period.
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Table 7. CBSA-level System HHIs for Top 5 Major Diagnostic Categories
CBSA Name
Appleton, WI
Atlanta-Sandy Springs-Roswell, GA
Augusta-Richmond County, GA-SC
Austin-Round Rock, TX
Baltimore-Columbia-Towson, MD
Baton Rouge, LA
Beaumont-Port Arthur, TX
Boulder, CO
Bridgeport-Stamford-Norwalk, CT
Cape Coral-Fort Myers, FL
Charlotte-Concord-Gastonia, NC-SC
Charlottesville, VA
Chicago-Naperville-Elgin, IL-IN-WI
Cincinnati, OH-KY-IN
Colorado Springs, CO
Columbus, OH
Corpus Christi, TX
Dallas-Fort Worth-Arlington, TX
Dayton, OH
Deltona-Daytona Beach-Ormond Beach, FL
Denver-Aurora-Lakewood, CO
Des Moines-West Des Moines, IA
El Paso, TX
Green Bay, WI
Greensboro-High Point, NC
Hartford-West Hartford-East Hartford, CT
Houston-The Woodlands-Sugar Land, TX
Jacksonville, FL
Kansas City, MO-KS
Knoxville, TN
All
admissions
MDC 5
MDC 6
MDC 8
MDC 14
MDC 15
4,023
1,495
3,040
3,783
1,318
3,341
3,040
2,464
1,750
7,477
3,440
4,440
1,001
1,412
3,916
4,029
3,683
1,656
3,120
3,266
2,955
4,710
4,731
3,120
6,275
2,652
1,938
3,031
1,623
3,134
4,435
1,508
3,612
3,659
1,672
3,611
2,907
2,421
1,546
7,287
2,817
4,620
915
1,624
4,303
3,198
5,337
1,498
2,833
3,109
2,140
5,190
4,637
3,121
6,750
2,901
1,772
2,491
1,614
3,155
3,177
1,411
2,556
3,083
1,359
3,957
2,769
2,565
1,573
7,360
2,938
5,072
848
1,353
3,577
3,494
3,369
1,798
3,011
3,406
2,817
4,397
4,449
2,675
6,343
2,403
1,629
2,717
1,218
3,007
3,772
1,577
2,985
2,857
1,583
4,907
2,826
1,986
1,855
6,758
3,278
4,744
983
1,530
3,298
4,973
2,251
980
3,027
2,848
2,916
4,551
3,561
3,906
6,679
2,635
1,913
2,719
1,765
3,332
4,541
2,113
4,313
4,584
1,239
3,357
4,407
2,984
1,979
8,558
3,730
5,300
1,272
1,762
4,584
4,383
4,568
1,947
3,507
3,211
3,448
4,885
4,811
3,662
7,246
2,889
2,332
3,754
1,981
3,395
4,770
2,645
5,066
4,517
1,279
1,994
5,303
2,860
2,000
8,488
4,177
5,850
1,434
1,864
4,668
4,387
4,765
2,018
3,799
3,749
3,372
4,945
5,400
3,954
7,911
2,808
2,594
4,581
2,062
3,018
Source: HCCI, 2017.
Note: Table continues. The five most frequent MDCs were MDC 5: Diseases and Disorders of the Circulatory System, MDC 6: Diseases and Disorders of the
Digestive System, MDC 8: Diseases and Disorders of the Musculoskeletal System and Connective Tissue, MDC 14: Pregnancy Childbirth and the Puerperium,
and MDC 15: Newborns & Other Neonates with Conditions Originating in Perinatal Period.
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Table 7. CBSA-level System HHIs for Top 5 Major Diagnostic Categories (cont.)
CBSA Name
Lakeland-Winter Haven, FL
Lexington-Fayette, KY
Louisville/Jefferson County, KY-IN
Memphis, TN-MS-AR
Miami-Fort Lauderdale-West Palm Beach, FL
Milwaukee-Waukesha-West Allis, WI
Minneapolis-St. Paul-Bloomington, MN-WI
Nashville-Davidson--Murfreesboro--Franklin, TN
New Haven-Milford, CT
New Orleans-Metairie, LA
New York-Newark-Jersey City, NY-NJ-PA
North Port-Sarasota-Bradenton, FL
Norwich-New London, CT
Oklahoma City, OK
Omaha-Council Bluffs, NE-IA
Orlando-Kissimmee-Sanford, FL
Palm Bay-Melbourne-Titusville, FL
Peoria, IL
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD
Phoenix-Mesa-Scottsdale, AZ
Portland-South Portland, ME
Providence-Warwick, RI-MA
Racine, WI
San Antonio-New Braunfels, TX
Sheboygan, WI
St. Louis, MO-IL
Tampa-St. Petersburg-Clearwater, FL
Trenton, NJ
Tucson, AZ
Tulsa, OK
Washington-Arlington-Alexandria, DC-VA-MD-WV
All
admissions
MDC 5
MDC 6
MDC 8
MDC 14
MDC 15
2,888
3,195
3,157
3,517
1,104
1,986
2,173
2,321
3,118
1,960
619
2,648
3,059
1,887
4,422
4,036
4,673
5,031
837
2,684
2,483
1,953
3,270
1,995
3,656
5,884
1,774
2,144
2,470
3,144
1,156
2,895
3,223
2,309
3,676
1,578
2,193
2,957
2,503
3,095
2,022
649
2,292
3,031
2,553
3,368
3,872
4,087
4,765
800
2,224
3,823
2,945
3,987
1,770
3,464
5,782
1,965
2,252
2,156
3,292
1,173
2,455
3,028
2,596
3,291
1,105
1,852
2,381
2,381
3,297
1,963
538
2,423
3,238
1,902
3,807
4,155
4,126
5,818
772
2,552
1,910
2,566
2,869
1,814
3,695
5,285
1,958
3,048
2,275
3,216
1,019
2,116
2,969
3,041
2,729
1,155
1,769
2,190
2,325
2,371
2,124
557
2,828
2,867
1,518
4,346
4,036
4,698
4,039
926
1,867
2,809
2,139
2,817
1,695
2,742
5,284
1,848
1,825
2,949
2,051
1,085
3,405
4,485
3,973
4,050
1,306
2,205
2,075
2,403
2,827
1,845
713
4,111
3,988
2,332
6,335
4,142
6,149
5,244
1,073
3,247
2,579
1,649
3,699
2,404
4,024
7,186
1,722
3,363
2,861
3,828
1,345
3,743
4,792
4,844
4,115
1,367
2,231
2,005
2,769
2,340
1,749
781
4,440
4,112
2,413
6,860
4,502
6,455
5,105
1,155
3,358
2,677
1,654
3,876
2,966
4,374
7,955
2,315
3,153
2,938
4,327
1,550
Source: HCCI, 2017.
Note: The five most frequent MDCs were MDC 5: Diseases and Disorders of the Circulatory System, MDC 6: Diseases and Disorders of the Digestive System,
MDC 8: Diseases and Disorders of the Musculoskeletal System and Connective Tissue, MDC 14: Pregnancy Childbirth and the Puerperium, and MDC 15: Newborns & Other Neonates with Conditions Originating in Perinatal Period.
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8
types of treatments and what implications does that have on cost and quality?
The importance of particular differences
will be determined by the research
question, but some examples of noteworthy CBSAs include: Dallas-Fort
Worth-Arlington, Texas where the MDC
8 HHI is substantially lower than the
other HHIs or Oklahoma City, Oklahoma
and Corpus Christi, Texas where the
MDC 5 HHI is relatively higher than the
others. Conversely, in Knoxville, Tennessee, all HHIs were similar in magnitude, even those for MDCs 14 and 15.
results in a measure that reflects the
competition, price, and quality.13
hospital (or system) concentration from
the perspective of patients residing
There are numerous reasons it is diffiwithin a CBSA.
cult to interpret the impact of concentration on hospital price or quality, esThere are numerous ways to define the pecially directly from the HMI
relevant set of hospitals to be included
measures. A direct comparison of the
in an HHI calculation, depending on the HMI inpatient price index to the inpaspecific research question. One alterna- tient concentration measures is potentive methodology for this report would tially misleading as prices may influence
have been to calculate HHIs based only concentration just as concentration can
on admissions to hospitals within each impact prices.
of the study CBSAs. Table 8 presents
summary statistics of HHIs calculated
There are also a number of limitations
using this alternative approach.11 Given to the generalizability of all of the HMI
the scope and purpose of the HMI prometrics as discussed in a previous HMI
Data and Methods
ject, however, the methodology and re- issue brief.14 In particular, all the analsults we present throughout this report yses were conducted with HCCI data,
The HCCI claims based concentration
were the most feasible, while still inwhich were a convenience sample of the
measures were calculated using inpaU.S. ESI population. Additionally, the
tient claims from all 61 CBSAs included formative and within scope of the project.12 The correlation of the two sets of choice of CBSA as the geographic unit of
in the HMI project. The HCCI inpatient
CBSA-level results were 0.8723 and
interest is not necessarily a relevant
claims were matched to the American
0.9147, for the hospital and system
market boundary for all hospital compeHospital Association’s (AHA) Annual
Survey Database™.10 The AHA database HHIs respectively. A notable difference tition analyses. The definition of a hospital market can differ in size and scope
includes information on a hospital’s lo- was that the alternative hospital location
based
approach
resulted
in
higher
by geography, patient mix, type of hoscation (e.g., CBSA), service category, and
HHIs.
pital, or type of service. Finally, the reownership types, as well as system affilsults presented for the 61 CBSAs includiation, number of hospital beds, and
ed in the HMI may not generalize to othnumber of Medicare discharges.
Limitations
er CBSAs or to non-CBSA areas.
The HHI calculation included only adThere is a large body of research on the
missions of individuals from the 61
role of competition in health care marConclusion
CBSAs in the HMI analysis. Therefore,
kets. The HMI reports on hospital inpawe excluded any admissions of individ- tient facility concentration due to the
In this issue brief, HCCI reports inpauals residing outside of a CBSA to hospi- feasibility (e.g., data availability and
tient admission HHI measures for 61
tals included in the study. However, ad- scope) as well as the importance of hos- CBSAs. The HHI is a commonly used
missions of patients from study CBSAs
pital markets (e.g., rising hospital prices, measure of market concentration and
to hospitals outside of the study CBSAs growth in quality measure availability,
an indicator of the level of competition –
were included. Shares of hospital (and
and increased hospital consolidation).
higher concentration is associated with
system) admissions were calculated for The HHIs presented in this brief are in- less competitive markets. The measures
each hospital (and system) based on
tended to provide insight into the conprovide benchmarks for future analyses
total admissions of patients from a giv- centration of inpatient hospital services and allow for identifying patterns, such
en CBSA to any non-federal, general
within the studied CBSAs because con- as higher concentration of admissions
acute care hospital (and system). This
centration is known to be related to
for MDCs 14 and 15. More generally, the
Table 8. Hospital Location Based System HHI Summary Statistics
Average
(Standard Deviation)
25th Percentile
50th Percentile
75th Percentile
Correlation with patient based HHIs
Hospital HHI
System HHI
2,674
(1,911)
1,204
2,438
3,690
0.8723
3,632
(1,836)
2,239
3,432
4,701
0.9147
Source: HCCI, 2017.
www.healthcostinstitute.org
9
measures are intended to be a resource
for identifying geographic areas or populations where a more thorough competition analyses may complement specific
research related to inpatient prices or
quality.
were chosen on the basis of relevance to
a broad spectrum of research and policy
evaluations. These geographies are not
necessarily the appropriate market definitions for evaluating hospital competition for regulatory or legal investigations.
Endnotes
5. In addition to the all admissions HHI
measures, we examined concentration
1. Additional details regarding the popu- levels for the top 5 most prevalent Major
lation and geographic units of analysis
Diagnostic Categories (MDCs). Major
are available in Healthy Marketplace
Diagnostic Categories are groupings of
Index: Medical Service Category Price
principal diagnoses that generally correIndex. See, Health Care Cost Institute.
spond to an individual organ system or
Healthy Marketplace Index: Medical Ser- etiology.
vice Category Price Index. Health Care
6. Additional details regarding the CBSA
Cost Institute, Apr. 2016 Web.
-level populations are available in Ap2. See http://www.justice.gov/atr/
pendix A of Healthy Marketplace Index:
herfindahl-hirschman-index for a more Medical Service Category Price Index. See,
detailed description of an HHI.
Health Care Cost Institute. Healthy Marketplace Index: Medical Service Category
3. See Gaynor, M. and Town R.,
Price Index. Health Care Cost Institute,
“Competition in Health Care Markets,”
Handbook of Health Economics, vol. 2 Ed. Apr. 2016 Web.
Pauly, MV, Mcguire, TG, and Barros, PP.
Waltham, MA North Holland 2012 pages: 499–637 for a thorough discussion of
the existing literature.
4. However, neither of the HMI concentration analyses should be considered a
comprehensive competition analysis.
The HMI results alone are not suitable
for regulatory or antitrust enforcement
purposes. HCCI data comprise only a
sample of any hospital’s total admissions. Even in areas where HCCI data
account for a large share of the ESI
claims, hospitals admissions include
patients with individual (e.g., non-ESI)
insurance, Medicare, Medicaid, Medicare
Advantage, and so on and the uninsured.
Additionally, the HMI measures have
been calculated for geographies that
Authors
Eric Barrette and Kevin Kennedy
[email protected]
571-257-1584
Health Care Cost Institute, Inc.
1100 G Street NW, Suite 600
Washington, DC 20005
202-803-5200
7. See https://www.ftc.gov/sites/
default/files/attachments/mergerreview/100819hmg.pdf, for the Federal
Trade Commission/Department of Justice criteria for market concentration.
8. Eighty-six percent more than 2500 is
4650.
9. The five most frequent MDCs were
Diseases and Disorders of the Circulatory System, Diseases and Disorders of the
Digestive System, Diseases and Disorders of the Musculoskeletal System and
Connective Tissue, Pregnancy Childbirth
and the Puerperium, and Newborns &
Other Neonates with Conditions Originating in Perinatal Period.
10. The AHA Annual Survey Database is
a census of United States hospitals
based on the AHA Annual Survey of Hospitals. The AHA data includes information on more than 6,200 hospitals,
with nearly 1,000 variables. The survey
data are supplemented with data from
secondary sources including the United
States Census Bureau and accrediting
organizations.
11. The total admissions included in the
analysis was still limited to patients
from the 61 study CBSAs. In this alternative approach, if a patient from one
CBSA was admitted to a hospital in a
second CBSA the admission is counted
in the second CBSA, but not the first. If
patients from any of the 61 CBSAs were
admitted to a hospital not located in any
of the 61 study CBSAs, that admission
was excluded from the analysis.
12. This approach was more feasible
from a reporting standpoint because
HCCI reporting rules prohibit reporting
results based on fewer than 5 providers
in any geographic area. There are multiple CBSAs with fewer than 5 hospitals
systems and or hospitals, which would
have resulted in multiple HHIs being
suppressed.
13. See Gaynor, M. and Town R.,
“Competition in Health Care Markets,”
Handbook of Health Economics, vol. 2 Ed.
Pauly, MV, Mcguire, TG, and Barros, PP.
Waltham, MA North Holland 2012 pages: 499–637 for a thorough discussion of
the existing literature.
14. Health Care Cost Institute. Healthy
Marketplace Index: Medical Service Category Price Index. Health Care Cost Institute, Apr. 2016 Web.
Acknowledgements
This HCCI research project was independently initiated by HCCI an dis part
of the HCCI research agenda
Support fort his project was provided in part by the Robert Wood Johnson
Foundation. The views expressed here do not necessarily reflect the views of
the Foundation.
Copyright 2017
Health Care Cost Institute, Inc.
Unless explicitly noted, the content of this report is licensed under a Creative
Commons Attribution Non-Commercial No Derivatives 4.0 License
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