Download Increasing hospital costs for Clostridium difficile colitis: Type of

Increasing hospital costs for Clostridium
difficile colitis: Type of hospital matters
Li Wang, PhD,a and David B. Stewart, MD,b Hershey, PA
Background. To assess differences in hospital costs for inpatients with Clostridium difficile (CD) colitis
based on hospital size, rural or urban hospital setting, and hospital designation as a teaching
institution.
Methods. Data from the Pennsylvania Health Care Cost Containment Council (PHC4) were reviewed
for 2005 to 2008. Cost-to-charge ratios were used to derive costs from hospital charges, adjusting costs for
inflation. Propensity score–matched CD colitis and non–CD colitis cohorts were compared. Costs were
modeled by generalized linear regression.
Results. A total of 78,273 patients with CD colitis were identified. The average hospital cost per
admission for patients with CD colitis was $22,094 compared to $10,865 for non–CD colitis patients.
The 2005 to 2008 admission costs for CD colitis rose 9%, while the prevalence of CD colitis decreased by
13%. The costs for patients with CD colitis were consistently twice as much as those for non–CD colitis
patients (P < .0001). Small facilities had the greatest costs overall (P < .0001). Urban and teaching
facilities had greater costs than rural and nonteaching facilities (P < .0001), which corresponded to a
greater proportion of patients with greater comorbidities (P < .0001). Among rural hospitals, the
smallest facilities had the greatest costs (P < .0001), as did urban nonteaching hospitals (P < .0001).
By contrast, costs did not differ among urban teaching hospitals of varying sizes (P = .35).
Conclusion. Costs for inpatient CD colitis in Pennsylvania have been increasing. Teaching and urban
hospitals treat the group of patients with CD colitis with the greatest comorbidity, accounting for their
greater cost of care. The cost of treating CD colitis is comparable among different sizes of teaching
hospitals, which may reflect a more standardized approach toward treatment choices. (Surgery
2011;150:727-35.)
From the Department of Public Health Sciences,a The Pennsylvania State University, and the Division of
Colon and Rectal Surgery,b Department of Surgery, Pennsylvania State Hershey Medical Center, Hershey, PA
OVER THE PREVIOUS 2 DECADES, the incidence of Clostridium difficile (CD) colitis has increased among
hospitalized patients in the United States and Europe.1-3 During this time, the demographic of patients with CD colitis has broadened to include
immunocompetent patients who harbor none of
the risk factors historically associated with developing CD colitis.4-6 A concomitant increase in the severity of CD colitis reported in the United States
has resulted in an increase in both disease morbidity and mortality.7 Associated with the increasing
severity of CD colitis is the growing need for
Presented at the 68th Annual Meeting of the Central Surgical
Association, Detroit, MI, March 17–19, 2011.
Accepted for publication August 18, 2011.
Reprint requests: Li Wang, PhD, Department of Public Health
Sciences, The Pennsylvania State College of Medicine, 600 Centerview Drive, A210, Hershey, PA 17033. E-mail: [email protected].
0039-6060/$ - see front matter
Ó 2011 Mosby, Inc. All rights reserved.
doi:10.1016/j.surg.2011.08.019
colectomy in those patients who fail to respond
to antibiotic therapy.1 Each of these factors contributes substantially to cost of care through the
need for antibiotics, the need for operative treatment, and an increased duration of hospital stay.
The magnitude of this excess cost, however, has
not been studied sufficiently.
One issue that has been discussed with respect
to other diseases8-12 but that has yet to be studied
with respect to CD colitis centers on whether a disparity exists in terms of cost as related to different
hospital settings for CD colitis of varying severity. It
is unknown if hospital size or hospital designation
as a teaching or academic institution has any bearing on cost of care. Issues related to cost of CD
colitis outcomes are particularly complex considering the different patient populations encountered
among different types of hospitals. Based on the
findings that institutional volume and personal expertise are associated with improved outcomes in
the treatment of other diseases, a similar expectation regarding the management of CD colitis
would also seem justifiable, considering the
SURGERY 727
728 Wang and Stewart
complexity involved in deciding on the need for
and timing of colectomy.
The purpose of this study was to describe the
trend in hospital costs attributable to CD colitis
within the state of Pennsylvania and to describe
how factors such as hospital size, rural or urban
care settings, and status as a teaching facility
affected the cost of treating CD colitis.
METHODS
This study was performed with institutional
review board approval from the authors’ institution. Data from the Pennsylvania Health Care
Cost Containment Council (PHC4) were reviewed
for 2005 to 2008. The PHC4 is an independent
state agency responsible for addressing the problem of escalating health costs, ensuring the quality
of care, and increasing access to health care. The
PHC4 database contains statewide inpatient discharge data and data from outpatient and freestanding ambulatory surgery centers. Patients
with CD colitis were identified if their primary or
secondary diagnoses included the International
Classification of Diseases, 9th edition, Clinical Modification (ICD-9-CM) diagnosis code for Clostridium difficile colitis: 008.45. Only patients whose residence
was in Pennsylvania (approximately 95% of all
the admissions) were included in this study, which
excluded heterogeneous out-of-state travelers. This
was done in part to allow for a meaningful analysis
regarding patient travel distance from their home
residence to the treating hospital. Cost-to-charge
ratios were used to derive costs from hospital
charges, and costs were inflation adjusted to 2008
dollars.
Propensity score–matched CD colitis and non–
CD colitis cohorts were compared. The propensity
score matching was performed for each year based
on the following variables: sex, race, age, admission type, payor type, patient comorbidities, hospital status as a rural or urban facility, hospital
status as a teaching or nonteaching facility, hospital size, and the yearly quarter at the time of
admission. Hospital size (small, medium, or large)
was stratified according to the size criteria used by
the Healthcare Cost and Utilization Program
(http://www.ahrq.gov/data/hcup). The categorization of hospital size was based on the number
of hospital beds, and was specific to the urban/rural and teaching status of the hospital. For rural
hospitals, small size was defined as having 1 to 49
beds, medium as 50 to 99 beds, and large as
$100 beds. For urban nonteaching hospitals, a
bed count of 1 to 124 was considered small, 125
to 199 beds was medium, and $200 beds was
Surgery
October 2011
considered large. For urban teaching hospitals,
1 to 249 beds was considered small, 250 to 424
was medium, and $425 eds was large. The urban
or rural status of a hospital was determined by
whether or not the location of the hospital was
found within a Metropolitan Statistical Area
(MSA). The teaching status was determined by
both PHC4 data entry and by publically available
online lists of Pennsylvania teaching hospitals. Patient comorbidity was derived based on the diagnosis codes for each patient, and a patient’s overall
degree of comorbidity was stratified by using a
Charlson Comorbidity Index (CCI).
Information regarding the number of colectomies performed within the CD colitis cohort was
also collected. The procedural codes contained in
PHC4 data were ICD-9 procedural codes; no Current Procedural Terminology codes were available.
The codes used for partial colectomy were 45.7,
45.71 to 45.76, and 45.79, while the code for total
colectomy was 45.8. Colectomy rates were not the
primary focus of this study, but given their potential influence on cost and an interest in assessing
how common colectomy was required for CD
colitis, these data were included. The propensity
score matching did not involve colectomy as a
factor, because the colectomy rate was extremely
low (<2%) as described in the Results section, and
therefore the mean costs for patients with CD
colitis were hardly affected by the cost of colectomy. In addition, the large number of disease
processes other than CD colitis for which colectomy might have been performed would not have
allowed for comparison of similar patient cohorts,
especially when considering such diseases as inflammatory bowel disease and cancer. Non–CD
colitis indications for colectomy would have introduced bias into cost assessment, as seen, for
example, in the additional costs for an ulcerative
colitis patient undergoing colonoscopies and inflammatory bowel disease medical therapy before
colectomy. Such diseases, disanalogous to each
other and to CD colitis, would have produced
groups inappropriate for comparison. Considering
the extremely low number of colectomies performed in the CD colitis cohort, the influence of
colectomy on cost was negligible.
To test whether patients with CD colitis differed
from the matched non–CD colitis cohort, v2 tests
were performed. Mann-Whitney-Wilcoxon testing
was used to compare differences in median costs.
Given the non-normal distribution of cost data,
generalized linear regression with multiple covariates was performed to study costs, with a log link
function and the error term having a Gamma
Wang and Stewart 729
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Volume 150, Number 4
Table I. Mean hospital costs per admission for Clostridium difficile colitis vs matched non– Clostridium difficile
colitis patients*
Year
No. of
patients
Rate of CD
colitis
Mean cost per
admission for CD colitis
Mean cost per non–CD
colitis admission
P value
2005–2008
2005
2006
2007
2008
78,273
21,581
19,634
18,849
18,209
1.083%
1.175%
1.081%
1.051%
1.023%
$22,094
$21,325
$21,428
$22,624
$23,173
$10,865
$10,470
$10,928
$10,893
$11,234
<.0001
<.0001
<.0001
<.0001
<.0001
*Costs were adjusted to 2008 dollars. The sample size was the same between the Clostridium difficile (CD) colitis group and the non–CD colitis group within
each year. The significance value refers to a comparison of mean hospital costs between the CD colitis group and non–CD colitis group within the given
period.
distribution. To explore whether rural patients
with CD colitis traveled greater distances to receive
treatment, travel distances were compared between urban and rural patients. The travel distances between the residence of a patient and
the treating facility was defined as the geodetic distance between the centroids of the patient’s ZIP
code and the treating facility’s ZIP code, calculating the shortest distance between the center points
of the 2 ZIP code areas with the aid of geospatial
mapping. The travel distance was determined
through a built-in function within SAS statistical
software (SAS Institute, Inc., Cary, NC).
RESULTS
A total of 7,227,788 inpatient admissions were
recorded in the PHC4 dataset from 2005 to 2008.
Of these, a total of 78,273 admissions for CD colitis
(including primary and secondary admission diagnoses for CD colitis) were found, equaling approximately 1% of the total admissions for the study
period. For the CD colitis cohort, >70% were 65
years of age or older and had Medicare as their
primary payor. More than half (57%) of the
patients with CD colitis were female. Caucasian
patients comprised 87% of all admissions for CD
colitis, while black patients comprised 11%. Approximately 68% of patients were treated at large
hospitals, 27% in teaching hospitals, and 10% in
rural hospitals. An equal number of propensity
score–matched, non–CD colitis patients from the
same time period were also included for comparison. No statistically significant differences existed
between the CD colitis and the matched non–CD
colitis cohorts with respect to any demographic
category (all P values >.8). A total of only 450 total
colectomies were performed for patients with CD
colitis (0.57% of all CD colitis admissions) during
the study period, and a total of 1,061 partial colectomies (1.36% of all CD colitis admissions) were
performed for patients with CD colitis.
Fig 1. Comparison of hospital costs by year between Clostridium difficile colitis (CDC) and matched, non-CDC
patients.
Patients with either a primary or secondary
admission diagnosis of CD colitis comprised 1.1%
of all admissions during the study period (Table I),
with a consistent decrease from 1.2% in 2005 to
1.0% in 2008. The mean hospital costs per admission for patients with CD colitis during the study
period, as calculated in 2008 dollars, was $22,094
compared to a mean hospital cost of $10,865 for
the propensity score–matched, non–CD colitis cohort (P < .0001). Median hospital costs for the
same period were $10,931 for the CD colitis cohort
and $6,485 for the non–CD colitis cohort (P <
.0001). For each study year, the mean hospital costs
per admission for patients with CD colitis were
consistently twice as high compared to the
matched, non–CD colitis cohort (P < .0001). The
mean per admission costs for the CD colitis cohort
increased by 9% from 2005 to 2008 (P < .0001),
but the number of CD colitis-related admissions
during the same time period decreased by 13%
(P < .0001). Fig 1 plots the time trend of mean hospital costs for both CD colitis and the non–CD colitis cohort across the 4-year study period and
shows a consistent difference in costs between
the 2 groups during the study period.
730 Wang and Stewart
Surgery
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Table II. Analysis for costs of Clostridium difficile colitis per admission (2005–2008)
Variable
Age (y)
<18
18–64
$65
Sex
Male
Female
Race
White
Black
Other
Admission type
Emergent
Urgent
Other
Comorbidity
0
1–2
$3
Payor type
Medicare
Commercial
Other
Hospital size
Small
Median
Large
Teaching
Yes
No
Rural hospital
Rural
Urban
Year
2005
2006
2007
2008
Unadjusted mean ($)
P value
Adjusted mean ($)
SE
P value
48,874
27,449
19,412
Ref.
<.0001
<.0001
40,536
25,142
18,132
1019
166
73
Ref.
<.0001
<.0001
24,899
20,008
Ref.
<.0001
22,576
18,389
118
83
Ref.
<.0001
20,292
34,081
34,520
Ref.
<.0001
<.0001
18,630
33,253
32,260
68
343
768
Ref.
<.0001
<.0001
20,055
21,040
31,955
Ref.
<.0001
<.0001
18,729
18,343
30,167
80
139
263
Ref.
<.0001
<.0001
21,975
21,797
25,548
Ref.
.32
<.0001
19,769
20,113
24,307
84
124
376
Ref.
<.0001
<.0001
19,942
26,360
32,536
Ref.
<.0001
<.0001
18,569
23,198
29,917
73
192
352
Ref.
.73
<.0001
25,465
20,160
22,068
Ref.
<.0001
<.0001
22,847
18,819
20,001
231
146
82
Ref.
.02
<.0001
33,528
17,854
Ref.
<.0001
32,831
16,705
215
67
<.0001
Ref.
11,969
23,194
<.0001
Ref.
10,922
21,448
119
77
<.0001
Ref.
21,325
21,428
22,624
23,173
Ref.
.63
<.0001
<.0001
19,443
19,699
20,522
20,798
126
134
143
147
Ref.
.86
.002
<.0001
Generalized linear modeling with multiple covariates was conducted to determine the factors associated with increased mean hospital costs among
patients with CD colitis. Table II lists the results of a
cost analysis within the CD colitis cohort. The unadjusted mean hospital costs represented the raw
mean for each stratum of each variable included
in the analysis, while the adjusted mean was calculated based on the predicted mean derived from
the estimated linear regression model by controlling for other variables that were held constant at
the sample mean. The unadjusted analysis of the
CD colitis cohort revealed that greater costs occurred in patients <18 years of age, males, nonCaucasian, non–African American race, elective
hospital admissions, non-Medicare, noncommercial
payor type, a CCI score $3, teaching hospital status,
urban hospital status, and small-sized hospitals (all
P <.0001). The adjusted cost analysis produced similar results, with 2 exceptions. Compared to patients
with a CCI score of 0, a CCI score of 1 or 2 produced
no cost difference based on an unadjusted analysis,
while greater costs (P < .0001) were noted at this
level of CCI when other variables were adjusted
for. A second exception involved costs associated
with commercial insurance payors, where greater
costs occurred by unadjusted analysis (P < .0001),
but not when other variables were adjusted for
(P = .73).
Fig 2 provides a map of Pennsylvania by county,
with a color code indicating various 1-way distances
of travel measured from the patient’s residence
Wang and Stewart 731
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Volume 150, Number 4
Table III. Mean costs (all years) for patients with
Clostridium difficile colitis by types of hospitals
Size of hospital
Status
All types
Rural
Urban,
teaching
Urban,
nonteaching
Fig 2. Mean patient travel distance in miles from patient
residence to treating hospital based on the patient’s
county of residence.
to the hospital where they received treatment.
Pennsylvania has approximately 50% of its
counties designated as rural. As shown in Fig 2, patients living in northern Pennsylvania travelled
greater mean distances than those in the south,
and patients close to the 2 largest metropolitan
areas (Philadelphia and Pittsburgh) travelled the
least distance. Classifying each patient’s place of
residence as either rural or urban, patients living
in rural areas had a greater mean 1-way distance
of travel compared to patients living in urban areas
(rural, 17.1 miles vs urban, 7.2 miles; P < .0001).
Costs for patients with CD colitis were further
studied by stratifying treating hospitals according
to the size of the facility and based on each
facility’s designation as a rural hospital, an urban
teaching hospital, or an urban nonteaching hospital (Table III). Patients with CD colitis were treated
in >200 hospitals, with only 25 of those facilities
being designated as teaching hospitals. Teaching
hospitals performed a disproportionately large
number of admissions for CD colitis compared to
their number, involving 27% of admissions for
the study period. Small facilities had the greatest
mean hospital costs overall (P < .0001).Urban
and teaching facilities had greater costs than rural
and nonteaching facilities (P < .0001). When facilities were differentiated only by teaching status, the
mean hospital costs were $33,528 for teaching facilities compared to $17,854 for nonteaching facilities (P < .0001). When only urban/rural status was
considered, the mean costs of patients with CD colitis were $23,194 for urban facilities vs $11,969 for
rural hospitals (P < .0001). The greater costs for
patients with CD colitis at urban and teaching hospitals was associated with the finding that those
Small
($)
Medium
($)
Large
($)
P
value
25,465
18,117
37,100
20,160
7,888
32,726
22,068
12,274
34,039
<.0001
<.0001
.35
25,239
20,128
16,557
<.0001
hospitals had a higher proportion of patients
with higher CCI scores (P < .0001). Among rural
hospitals, the smallest facilities had the greatest
costs (P < .0001), as was the case with urban nonteaching hospitals (P < .0001). By contrast, costs
did not differ among urban teaching hospitals of
varying sizes (P = .35). The patterns of cost difference by hospital type were similar to patterns in
duration of stay by hospital type, which may be associated with this difference in cost. For small rural
hospitals, the average duration of stay among patients with CD colitis was 14 days vs 7 days for medium rural hospitals and 9 days for large rural
hospitals (P < .05). For urban nonteaching hospitals, the mean duration of stay was 22 days for small
hospitals vs 12 days for medium facilities and 11
days for large hospitals (P < .05); however, there
was no statistically significant difference in duration of stay among various sized urban teaching
hospitals, with small and medium urban teaching
facilities having a mean duration of stay of 13
days vs 14 days for large hospitals for patients
with CD colitis.
DISCUSSION
During the 4-year time period analyzed in this
study, inpatient admissions for CD colitis in Pennsylvania comprised only 1% of the >7 million
admissions during that time span. With the recent
increase in the frequency of severe forms of CD
colitis reported in the literature, including those
patients who either die from the infection or who
require colectomy, CD colitis has become a disease
that now involves more commonly surgeons in its
treatment. These factors may lend to a perception
among surgeons that CD colitis is more common
or more severe than it actually is when considered
in a broader context, and the statewide data
presented in this study underscore the fact that
while previous papers13-15 have shown that the disease is more common relatively than it used to be,
732 Wang and Stewart
that nonetheless, in more absolute terms and while
looking beyond a single institutional experience,
CD colitis still represents a small number of hospital admissions overall.
The incidence of CD colitis and the rate of
admission for CD colitis has been reported to be
increasing,16,17 but these reports cover much
greater periods of time than the present study,
and they are not based on the most recent data.
Reports that describe increasing rates of CD colitis
are based on data no more current than 2005 to
2006, and to the best of the authors’ knowledge,
there have been no studies that have included
data from more recent time periods. Although
our study is oriented toward issues related to cost
over a short period of time, the authors noted a decrease in the rate of inpatient CD colitis in Pennsylvania from 2005 to 2008. Of note is that the
incidence of CD colitis reported in this study was
a measurement recorded carefully in a statewide
dataset, and was not a number reached through
computational maneuvers or methods that would
have introduced selection bias. PHC4 has been
quite active in documenting the incidence of CD
colitis and reporting this to state legislators, with
reports published by PHC4 indicating that the
hospital-acquired infection rates (including CD colitis) have decreased by as much as 8% from 2007
to 2008.18
The percentage of patients with CD colitis
requiring total colectomy was quite low at only
450 patients, representing 0.56% of the total
number of CD colitis–related admissions in the
study period. Partial colectomy was performed for
1.4% of all CD colitis–related admissions. Cost and
not colectomy rates was the primary focus of this
study, but the low colectomy rate helps provide a
more balanced view of the status of the disease
over a large population. While any single institution may experience a period during which an
outbreak of severe CD colitis occurs and that may
be associated with a greater rate of colectomy
during that outbreak, caution is needed in generalizing those experiences to patients at large.
While the authors do not wish to diminish the
importance of CD colitis as a potentially lethal
infectious disease, statewide data such as that
presented in the present study help maintain
balance in gauging the true scope of the disease
in terms of its incidence, severity, and need for
colectomy. Colectomy was not included in the
criteria for matching for reasons given in the
Methods section of the paper. Given that only 2%
of patients with CD colitis underwent a colectomy,
these patients did not require exclusion while
Surgery
October 2011
computing mean CD colitis costs. Sensitivity analysis revealed that excluding patients with CD colitis
who underwent a colectomy would have decreased
the mean CD colitis costs by only $700, far less than
the cost difference of approximately $10,000 between the CD colitis and non–CD colitis cohorts.
Therefore, despite the fact that a small percentage
of patients with CD colitis underwent a colectomy,
while a corresponding number of patients from
the non–CD colitis cohort may not have undergone colectomy, this scenario would not mitigate
the findings of the present study.
The cost of CD colitis during the study period
increased for each year evaluated, being twice as
great as that of a propensity score–matched non–
CD colitis control group. Although the number of
CD colitis–related admissions decreased during
the same period by 13%, hospital costs in the CD
colitis group increased simultaneously by 9%. Increasing costs during this period were undoubtedly
affected by the national trend in increasing costs
for drugs including antibiotics. Additional reasons
for the rising costs of CD colitis are left for future
research that would focus on what components of
total cost are increasing.
Adjusted cost analysis revealed several interesting findings. Based on the type of admission, the
greatest costs measured while controlling for other
factors were associated with elective admissions.
This observation reflects probably the fact that
elective admissions associated with CD colitis are
usually admissions for other diagnoses, with the
development of CD colitis during the admission as
a secondary problem (secondary CD colitis). This
would combine the cost of the primary indication
for admission with the cost of management of CD
colitis, the latter of which would increase drug and
hospital charges through an increased duration of
stay. Urgent and emergent admissions may include
those patients with more severe CD colitis who may
have undergone earlier colectomy. In those patients who are elderly and have a greater number
of medical problems, less aggressive care may lead
to lesser costs by withholding operative management and maximally aggressive medical therapy
related to an anticipated poor outcome.
Greater costs were seen with smaller hospital
sizes, urban hospitals, and teaching facilities. The
finding of greater costs at smaller hospitals as
opposed to larger facilities is interesting, considering that one would expect that smaller facilities
would have a lesser threshold for transferring
patients who might be more ill and who would
require more intensive and therefore more expensive care. Smaller facilities that were also rural were
Wang and Stewart 733
Surgery
Volume 150, Number 4
found to have a lesser CCI than larger facilities.
This finding may indicate that the patients who are
kept at smaller and/or rural facilities are those
who tend to be less ill, but who may have greater
hospital stays requiring greater durations of antibiotics and in-hospital observation. Smaller hospitals may also lack physician specialists as well as
multidisciplinary coordination of patient care,
which may further contribute to issues related to
efficiency of care, which could affect cost. The
effect on cost based on hospital designation also
demonstrated that teaching status brought stability
to hospital costs. While only a small percentage
(10.6%) of the hospitals in this study were designated as teaching facilities, this minority of hospitals cared for a disproportionately large percentage
(27%) of all CD colitis–related admissions during
the study period and cared for patients with a
greater number of comorbidities than their nonteaching counterparts. The reason that teaching
status brought homogeneity to CD colitis–related
hospital costs may reflect an institutional commitment to education, greater adherence to national
quality guidelines, and institutional mechanisms
for quality and peer review such as regular morbidity and mortality discussions and review of
national guideline compliance.
Our study has weaknesses and limitations. As
with all administrative data, there is no detailed
clinical information to explore certain specific
aspects of treatment. It would be interesting to
evaluate the frequency with which rural hospitals
transfer patients with CD colitis to tertiary care
facilities, which would provide more information
regarding the complex relationship between patient characteristics and greater costs at tertiary
care centers. This type of information is not
available in the PHC4 dataset. While this is a
definite limitation in the data presented, it would
certainly apply to only a minority of patients. The
impact produced by hospital transfers on the study
results would be minimized by the large number of
patients included in the study, as well as the fact
that hospital transfers would also be possible in the
propensity score–matched cohort, so that the present analysis does not deal with a confounding
element that would preferentially affect only 1 cohort. Another potential weakness is related to its
use of discharge data, which may not be as accurate as data obtained from reviewing medical
charts. There may also be concerns about possible
‘‘upcoding’’ performed by hospitals to increase
charges by using less strict criteria for diagnosing
various infectious diseases. While this potential is
always present in studies of this kind, upcoding
alone would not be serious enough to affect our
conclusions. This study used both primary and
secondary diagnosis codes for inpatient admissions
to identify patients with CD colitis. The diagnosis
codes for inpatient data are much more accurate
than the diagnosis codes used at outpatient office
visits, because of strict criteria used to justify the
admission of patients. The rate of CD colitis in
small hospitals was not appreciably different than
at larger hospitals. For example, when analyzing
2008 data, the CD colitis rate among all admissions
was 1.31% for small hospitals, 0.96% for medium
hospitals, and 1.01% for large hospitals. The similarity of CD colitis rates across various sizes of
hospitals does not point to an obvious upcoding
problem.
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14. Loo VG, Poirier L, Miller MA, et al. A predominantly clonal
multi-institutional outbreak of Clostridium difficile-associated
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Available from: http://www.phc4.org/reports/hai/07/
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DISCUSSION
Dr. Frederick Luchette (Maywood, IL): Dr Stewart, very
nice presentation. This study used a large state databank
that has inherent strengths and weaknesses. Dr Stewart
describes a trend in inpatient cost for management of
Clostridium difficile colitis as increasing over the 3-year
study period. It concludes that, as one would expect,
teaching and urban hospitals treat patients with more
comorbidities, which he suggests accounts for the higher
cost of care. I’m not sure that one can make this conclusion based on the data used in this study.
You touched on this in the introduction: in recent
years, there has been both an increased incidence and
severity of Clostridium difficile colitis evolving during the
last decade. This current epidemic may be driven by a
specific strain, NAP1/B1, which has been well documented in the numerous reports in North America
and Europe. It is characterized by significant mobility
and mortality associated with an increased rate of medical failure to antibiotic treatment, leading to colectomy.
So is the increased cost for the treatment at small rural
hospitals related to protracted stays for treatment?
Similarly, is the higher cost of the care at the urban
teaching facilities because of the more complex patient
population at these hospitals and possibly more frequent
colectomies for the more virulent strain of Clostridium
difficile seen in these institutions?
Another concern I have is with the accuracy of the
data in the Pennsylvania Health Care Cost Containment
Council, which is using discharge coding. Many hospitals
will not use strict criteria for diagnosing various infectious diseases, which is referred to as upcoding. This
aggressive coding allows the hospitals to increase
charges, and thus reimbursement, particularly at small
rural hospitals. Could the higher cost at the small rural
hospital facilities just be inaccurate because of the
upcoding? Stated another way, how do we know that
all the patients discharged with a diagnosis of Clostridium
difficile colitis from the small rural hospitals actually had
that diagnosis and disease?
Dr. David Stewart (Hershey, PA): Let me start with the
last question first. As with any discharge data, upcoding
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may exist; however, it is unlikely to have caused the
higher costs of small hospitals in our study. Upcoding
may increase the cost of a patient who does not have
CD colitis, but its effect on the average cost for CD colitis
can be in either direction, depending on whether the patient included from upcoding has higher or lower cost
compared to the average cost of the correctly coded
CD colitis patients. Also as we see, the rate of CD colitis
was similar across small, medium and large sized hospitals. So even if upcoding may exist, it does not differentially affect small hospitals.
You mentioned NAP1 strain. I have an IRB-approved
tissue bank at our hospital. I collect Clostridium difficile
samples and then I analyze them for NAP1 strain using
PFGE. I use PCR to identify TCDC mutations. I look at
MICs for vancomycin and flagyl. And this just began
less than a year ago. So we have about 25 samples that
have been isolated, strained, and typed. And almost every one of those samples was NAP1, had binary toxin,
had toxins A and B, had basement-low MICs for flagyl
and vancomycin. And in addition, had other virulence
factors that aren’t as well publicized and aren’t as well
understood.
So I tend to think that the higher incidence and
severity of Clostridium difficile colitis might not be because
of a particular strain. I’m more convinced now, seeing
some of this preliminary small-size data, that maybe
NAP1 designation is important because it covaries with
some other unidentified virulence factor.
Because none of the NAP1 strains in our sample had
any longer length of stay when compared to a matched
cohort, none of them required surgery, none of them
required ICU care, and yet 82% of the samples we’ve
collected thus far were NAP1. At least at our hospital,
NAP1 is the strain that people develop with all of the associated virulence factors. And yet, for some reason,
most of our patients don’t end up needing colectomy,
even at a tertiary referral center. We average about 10
a year.
Dr. Thomas Hayward (Indianapolis, IN): How did
you handle the data irregularities inherent in administrative cost data? There are commonly extreme values
from zero cost to very high charges, just because of low
sampling errors as a file. In common practice, you often
substitute the average if they differ more than a standard
deviation or two from the mean.
Question number 2: how did you handle transfers, or
was there a way to pull out transfers from the triage
hospital from the rural to the tertiary care facility? Was
that data available in your data set?
Thirdly, the incidence of Clostridium difficile acquired
disease decreased over your study, although it had
been increasing for most of the decade. Why do you
think this happened? And could it be a result of the
SCIP measures that were first introduced in 2005, where
perioperative antibiotics were limits to a 24-hour course
or less for the first time among many of our colleagues.
And of course, the PQI supplement became instituted,
and that should be available in a coded database. Or
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do you think it is because of upcoding or decreased coding for complications because of publication of complication data? Or do you think it’s something else?
Dr. David Stewart (Hershey, PA): In terms of costs,
the possible effect of outliers on costs is minimal due
to the large sample size in our study (78,273 CD colitis
patients). In addition, several ways were also used to
clean data to ensure the cost accuracy, such as equating
the cost-to-charge ratio outliers to the nearest reasonable
values, and excluding patients with zero charges.
Secondly, this study did not examine transfers, for the
average cost analyzed was for per admission not per
patient. If a patient was transferred and had two discharge records from two facilities, then this patient
contributed two observations to the study sample.
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Lastly, you mentioned decreasing incidence. I tried to
be very careful not to couch this study in terms of an
epidemiologic study, which I would define the latter as
being looking at disease shifts at the population level
over broad sweeps of time. I only looked at a very small
cross section of time, more for the purpose of evaluating
cost.
And I just wanted to have incidence and costs put on
par there so that you could see that our incidence is
going down over this very short time period, which
matches other in-state markers of healthcare-acquired
infections as well as making my point that, even with the
incidence decreasing, our costs are going up, which is
something that the PHC4 has been commenting on for
the last decade.