2. DISEASES OF THE COLON & RECTUM VOLUME 57: 1 (2014) 99
may also be subject to reduced reimbursement. Hospitals
with higher-than-predicted rates of readmissions may face
financial penalties, and almost half of large teaching hos-
pitals might be subjected to these cuts.5
Because of the enormous medical and financial im-
pacts of unplanned readmissions, numerous studies have
attempted to define risk factors for readmissions after colon
and rectal surgery. Despite numerous studies, widespread
disagreement remains in the medical literature regarding
whether there are modifiable risk factors for readmission
or whether it is largely unavoidable.6,7
None of those stud-
ies were able to delineate definitive strategies for readmis-
sion reduction,8
but all of them agree that the medical and
financial costs associated with this are high. Identifying
modifiable and/or avoidable factors in colon and rectal
surgery would have the potential to improve patient out-
comes and reduce health care-related costs. The aim of this
study was to identify risk factors that are independently as-
sociated with readmission within 30 days of elective colec-
tomy by analyzing the prospective, multicenter Michigan
Surgical Quality Collaborative (MSQC) database.
MATERIALS AND METHODS
The MSQC is a collaboration of 52 community and aca-
demic hospitals throughout the state of Michigan with
the goal to improve quality and patient outcomes.9
Sixty-
two percent of the participating hospitals are community
based without teaching activities.9
The MSQC database is
similar to the rigorously maintained American College of
Surgeons’ National Surgical Quality Improvement Pro-
gram (NSQIP).10,11
Collected data include >200 variables
and include patient demographic characteristics and co-
morbidities, preoperative and intraoperative measures,
and 30-day postoperative outcomes.11
The MSQC colecto-
my project involves 24 of the 52 hospitals and additionally
records procedure-specific perioperative data on patients
undergoing partial colectomy. Data for the MSQC are
meticulously recorded by NSQIP-certified clinical nurse
reviewers at each participating hospital. In case of miss-
ing or inconsistent data, the data abstractors communi-
cate directly with the operating surgeon. Readmissions
are tracked across all of the MSQC-participating hospitals
and are not limited to the hospital where the patient un-
derwent surgery.
All of the cases of elective laparoscopic and open il-
eocolic and segmental colectomies included as part of the
MSQC colectomy project from June 2008 through Novem-
ber 2010 were eligible for inclusion in our analysis. These
operations were defined by Current Procedural Terminol-
ogy codes 44140 and 44160 (open colectomy), as well as
44204 and 44205 (laparoscopic colectomy). The MSQC
database excludes patients with age <18 years, pregnant
women, trauma patients, and patients with ASA classes 5
and 6. Operations resulting in the creation of an ostomy,
rectal resections, or low anastomoses are not included in
the MSQC colectomy project. In addition, cases with com-
plete obstruction or perforation, as well as any emergent
cases, were also excluded from this study, because these are
not elective and risk factors are not modifiable.
To determine risk factors independently associated
with readmission within 30 days of the index operation,
patient characteristics, operative factors, and postopera-
tive complications recorded in the MSQC database were
first subjected to univariate analysis, determining the rela-
tionship of each variable to 30-day readmission. This was
followed by a multivariate logistic regression model, of
both preoperative and postoperative variables, which in-
cluded all of the variables with a p value of <0.10.Variables
with significance on each multivariate logistic regression
model were then entered into a final multivariate logistic
regression model that combined preoperative and postop-
erative variables to determine their independent influence
on the incidence of 30-day postoperative readmission.
RESULTS
From June 2008 through November 2010, 4013 cases met
inclusion criteria. Patient demographic characteristics
are shown in Table 1. Their average age was 64.2±15.0
years with a mean BMI of 28.5±8.3. The readmission rate
among these patients was 7.3% (N = 292).
Table 2 lists the preoperative variables studied. Uni-
variate analysis demonstrated a host of preoperative
factors with associations to readmission: 1) ASA class 4
(p = 0.02), 2) being functionally dependent (either par-
tial or total, p < 0.0001), 3) diabetes mellitus (p = 0.04),
4) hypertension (p = 0.003), 5) severe COPD (p = 0.02),
6) preoperative dyspnea (p = 0.001), 7) presence of an
open wound (p = 0.011), 8) steroids (p < 0.0001), 9)
TABLE 1. Demographics
Entire cohort (N = 4013) Readmit (N = 292) No readmit (N = 3721) p
N, % (n) 100 (4013) 7.28 (292) 92.72 (3721)
Age (mean ± SD), y 64.2±15.0 65.0±16.0 64.2±15.0 0.38
Age ≥80 y, % (n) 16.7 (672) 20.9 (61) 16.4 (611) 0.06
Men, % (n) 47.7 (1914) 51.0 (149) 47.4 (1765) 0.25
BMI, mean ± SD 28.5±8.3 28.7±6.9 28.5±8.4 0.26
Black, % (n) 11.3 (452) 12.0 (35) 11.2 (417) 0.70
3. KERWEL ET AL: RISK FACTORS FOR POSTOPERATIVE READMISSION100
known bleeding disorder (including congenital clotting
disorders and chronic anticoagulation, p < 0.0001), and
10) anemia (hematocrit <30%, p = 0.04). The readmis-
sion group was found to have, on average, more comor-
bid conditions as defined by MSQC than the no-readmit
group: 2.06±1.80 vs 1.57±1.50 (p = 0.0003). See the
bottom of Table 2 for a definition of these comorbid con-
ditions. A multiple logistic regression analysis of the pre-
operative variables with a p value of ≤0.10 was performed
to determine independent preoperative risk factors for
readmission. The only significant variable resulting from
this analysis was chronic preoperative steroid use (OR,
1.9 [95% CI, 1.14–3.19]; p = 0.014).
Tables 3 and 4 show preoperative laboratory data and
surgical variables studied. Factors on univariate analysis
that were found to have an association with readmission
are anemia (p = 0.04) and wound class 4 (p = 0.007). The
readmission group also had more intraoperative blood
loss than the no-readmit group (0.047). Laparoscopy
showed a trend with decreased readmission rates, but
this did not reach statistical significance. Wound class
4 was included in the analysis of preoperative variables
and found to be an independent predictor of readmission
(OR, 1.15; p = 0.0005)
Table 5 shows the postoperative outcomes studied.
The association between complications and readmission
is striking from a statistical standpoint, with the major-
ity of the complications being highly statistically signifi-
cant for their association with readmission. Univariate
analysis showed the following complications to be sig-
nificant: 1) return to the operating room within 30 days
(readmissions, 22.3%; no readmission, 3.6%; p < 0.0001),
2) anastomotic leak (12.8% vs 2.1%; p < 0.0001), 3) pro-
longed ileus (21.4% vs 6.1%; p < 0.0001), 4) sepsis (14.7%
TABLE 2. Preoperative variables and risk factors
Entire cohort
(N = 4013)
Readmit
(N = 292)
No readmit
(N = 3721) p
Total risk factors, mean ± SDa
1.78±1.7 2.06±1.8 1.57±1.5 <0.0001
Smoker, % (n) 18.7 (744) 12.1 (35) 19.2 (709) 0.004
Alcohol use, % (n) 3.2 (127) 2.1 (6) 3.3 (121) 0.38
Functionally dependent, % (n) 4.8 (193) 10.3 (30) 4.4 (163) <0.0001
ASA, % (n)
1 2.7 (108) 2.4 (7) 2.7 (101) 1.00
2 50.3 (2020) 46.2 (135) 50.7 (1885) 0.13
3 42.6 (1708) 44.2 (129) 42.4 (1579) 0.58
4 4.3 (174) 7.2 (21) 4.1 (153) 0.02
Hypertension, % (n) 56.4 (2245) 63.4 (184) 55.8 (2061) 0.003
Diabetes mellitus, % (n) 17.7 (709) 21.6 (63) 17.4 (646) 0.04
Dyspnea, % (n) 16.3 (649) 21.4 (62) 15.9 (587) 0.001
Cardiac disease, % (n) 13.9 (552) 17.2 (50) 13.6 (502) 0.09
Severe COPD, % (n) 5.8 (233) 8.6 (25) 5.6 (208) 0.016
CVA, % (n) 5.0 (200) 5.9 (17) 5.0 (183) 0.40
Bleeding disorder, % (n) 4.2 (168) 7.9 (23) 3.9 (145) <0.0001
TIA, % (n) 4.0 (160) 4.8 (14) 4.0 (146) 0.44
Steroid use, % (n) 3.7 (149) 7.6 (22) 3.4 (127) <0.0001
10% weight loss, % (n) 3.3 (131) 3.1 (9) 3.3 (122) 1.00
Disseminated cancer, % (n) 2.6 (102) 2.4 (7) 2.6 (95) 1.00
Open wound, % (n) 1.1 (42) 2.4 (7) 0.9 (35) 0.011
DNR, % (n) 1.0 (38) 1.4 (4) 0.9 (34) 0.35
CHF within 30 days, % (n) 1.0 (41) 1.7 (5) 1.0 (36) 0.12
PVD, % (n) 1.0 (40) 1.7 (5) 0.9 (35/3694) 0.21
Dialysis dependence, % (n) 0.8 (31) 0.7 (2) 0.8 (29/3694) 1.00
Ascites, % (n) 0.4 (16) 0.0 (0) 0.4 (16/3694) 0.62
Delirium, % (n) 0.2 (7) 0.3 (1) 0.2 (6/3694) 0.41
DNR = do not resuscitate; COPD = chronic obstructive pulmonary disease; CHF = congestive heart failure; PVD = peripheral vascular
disease; TIA = transient ischemic attack; CVA = cerebrovascular accident.
Bold p values indicate significance.
a
Subjects receive 1 point for each of the following preoperative risk factors as defined by the Michigan Surgical Quality
Collaborative: diabetes mellitus, preoperative sepsis, current smoker, >2 alcoholic drinks per day within 2 weeks, DNR status, ventila-
tor dependence within 48 hours, severe COPD, current pneumonia, ascites within 30 days, esophageal varices, CHF within 30 days,
history of myocardial infarction in the past 6 months, previous percutaneous coronary intervention/percutaneous transluminal
coronary angioplasty, previous cardiac surgery, angina within 30 days, hypertension requiring medication, history of revasculariza-
tion or amputation for PVD, rest pain/gangrene, acute renal failure within 24 hours, dialysis dependence, impaired sensorium within
48 hours, coma, hemiplegia/hemiparesis, history of TIAs, CVA with or without residual neurologic deficit, tumor involving central
nervous system, paraplegia/paraparesis, quadriplegia/quadriparesis, disseminated cancer, open wound, steroid use for chronic
condition, >10% loss of body weight in the last 6 months, ≥4 packed red blood cells preoperatively within 72 hours, chemotherapy
or radiotherapy within 90 days, sepsis within 48 hours, pregnancy, or previous operation within 30 days.
4. DISEASES OF THE COLON & RECTUM VOLUME 57: 1 (2014) 101
vs 3.1%; p < 0.0001), 5) septic shock (4.8% vs 1.0%; p
< 0.0001), 6) pneumonia (5.5% vs 2.1%; p < 0.0001), 7)
unplanned intubation (5.8% vs 2.4%; p < 0.0001), 8) or-
gan space surgical site infection ((SSI) 16.4% vs 1.6%; p
< 0.0001), 9) venous thromboembolism (9.2% vs 1.1%; p
< 0.0001), 10) Clostridium difficile colitis (5.5% vs 1.1%;
p < 0.0001), 11) mechanical bowel obstruction (6.6% vs
0.7%; p < 0.0001), 12) wound dehiscence (2.4% vs 0.8%;
p = 0.010), 13) acute myocardial infarction (3.1% vs 0.5%;
p < 0.0001), 14) cardiac arrest requiring cardiopulmonary
resuscitation (1.7% vs 0.6%; p = 0.024), 15) stroke (1.7%
vs 0.2%; p < 0.0001), 16) progressive renal insufficiency
(4.8% vs 0.5%; p < 0.0001), 17) superficial SSI (14.0% vs
5.1%; p < 0.0001), and 18) urinary tract infection (6.5%
vs 2.2%; p < 0.0001).
The postoperative variables with a p value of ≤0.10
were evaluated in a multiple logistic regression analysis
to determine which variables were independent risk fac-
tors. These are reoperation within 30 days, organ space
SSI, venous thromboembolism, Clostridium difficile coli-
tis, acute myocardial infarction, stroke, mechanical bowel
obstruction, prolonged ileus, urinary tract infection, and
superficial SSI. These postoperative variables were then
analyzed with preoperative steroid use in a combined
multilogistic regression analysis. This then identified risk
factors that independently predict readmission (Table 6):
1) postoperative stroke (OR, 10.01; p = 0.001), 2) postop-
erative venous thromboembolism (OR, 6.51; p < 0.0001),
3) organ space SSI (OR, 5.6; p < 0.0001), 4) postopera-
tive progressive renal insufficiency (OR, 3.95; p = 0.001),
5) postoperative Clostridium difficile colitis (OR, 3.61; p
< 0.0001), 6) reoperation within 30 days (OR, 3.12; p <
0.0001), 7) postoperative myocardial infarction (OR, 2.92;
p = 0.03), 8) postoperative mechanical bowel obstruction
(OR, 2.92; p = <0.0001), 9) superficial SSI (OR, 2.78; p <
0.0001), 10) prolonged ileus (OR, 2.23; p < 0.0001), and
11) urinary tract infection (OR, 1.9; p = 0.008). Preopera-
tive steroid use was no longer a significant risk factor when
analyzed with postoperative complications.
DISCUSSION
Major bowel resections have a high rate of patient re-
admission, with the majority (82%) occurring in the
first 30 days postoperatively.12,13
Thirty-day readmission
rates have become a marker of surgical quality and pos-
sible grounds for reimbursement penalties. As Centers for
Medicare & Medicaid Services attempts to involve read-
missions as a component of the total cost of an episode of
care, it is crucial that surgeons identify risk factors associ-
ated with readmissions.14
This analysis of a large series of
elective colectomies in multiple hospitals across the state
of Michigan demonstrated a readmission rate of 7.3%.
Although these results compare very favorably with fre-
quently reported 30-day readmission rates between 11.0%
and 13.7% after colorectal surgery,1,2,4
they confirm that
TABLE 4. Surgical variables
Cohort Readmit No readmit p
Type of surgery
Partial colectomy, % (n) 32.3 (1295) 36.6 (107) 31.9 (1188) 0.2
Right hemicolectomy, % (n) 19.9 (799) 19.9 (58) 19.9 (741) 1.00
Laparoscopic partial colectomy, % (n) 33.7 (1353) 30.1 (88) 34.0 (1265) 0.20
Laparoscopic right hemicolectomy, % (n) 14.1 (565) 13.3 (39) 14.1 (526) 0.79
Laparoscopy, % (n) 47.8 (1918) 43.5 (127) 48.1 (1791) 0.13
Intraoperative blood loss (mean ± SD), mL 137±220 156±180 135±171 0.047
Wound class, % (n)
2 86.6 (3474) 81.2 (237) 87.0 (3237) 0.007
3 9.9 (398) 12.3 (36) 9.7 (362) 0.16
4 3.5 (139) 6.5 (19) 3.2 (120) 0.0069
Bold p values indicate significance.
TABLE 3. Selected laboratory values
Cohort Readmit No readmit p
Anemia (Hct <30%), % (n) 9.4 (362) 12.5 (35) 9.2 (327) 0.036
Mean Hct (mean ± SD), % 38.0±5.8 37.2±5.9 38.1±5.8 0.013
Preoperative glucose (mean ± SD), mg/dL 111±38 114±37 111±38 0.218
Intraoperative glucose, mean ± SD 158±58 166±51 157±59 0.47
Glucose POD1, mean ± SD 143±44 147±52 143±43 0.17
Glucose POD2, mean ± SD 126±37 128±38 126±37 0.46
Hct = hematocrit; POD = postoperative day.
Bold p values indicate significance.
5. KERWEL ET AL: RISK FACTORS FOR POSTOPERATIVE READMISSION102
readmissions are indeed a problem. Although the 30-day
mortality rate in patients who were readmitted was not
significantly higher than in patients who did not return to
the hospital (2.1% vs 1.7%; p = 0.64), other studies have
shown worse long-term outcomes at 1 year, especially
among cancer patients.1,4
In our multivariate analysis, we demonstrated that
postoperative complications accounted for the majority of
risk factors that were independently associated with 30-
day readmissions. Although not all postoperative compli-
cations are avoidable, this factor may be more amenable to
strategies aimed to reduce preventable complications than
patient factors and comorbidities, because many patient
factors cannot be modified in the preoperative period
before colon resection. The strong association between
readmissions and postoperative complications has been
shown before in other studies.1,2,15,16
Of interest, the article
by Kassin et al16
reached the same conclusions that we have
using a similar analysis with similar methodology for gen-
eral surgery patients.
The complications with the highest incidence in our
cohort were prolonged ileus (7.2%), superficial SSI (5.7%),
sepsis (4.0%), anastomotic leak (3.3%), and organ space
SSI (2.6%). All of the other complications related to read-
missions had an incidence of well below 3%. These data
suggest that an effort to reduce those complications might
reduce readmission rates. A reduction in prolonged ileus
has been shown with narcotic-sparing enhanced recov-
ery pathways (ERPs) and use of minimally invasive tech-
niques.17–19
As more high-quality studies become available
TABLE 5. Postoperative outcomes
Cohort Readmits No readmits p
In-hospital death, % (n) 1.7 (70) 2.1 (6) 1.7 (64) 0.64
Prolonged ileus, % (n) 7.2 (285) 21.4 (62) 6.1 (223) <0.0001
SSI–superficial, % (n) 5.7 (230) 14.0 (41) 5.1 (189) <0.0001
Return to OR within 30 days, % (n) 4.9 (197) 22.3 (66) 3.6 (132) <0.0001
Sepsis, % (n) 4.0 (159) 14.7 (43) 3.1 (116) <0.0001
Anastomotic leak, % (n) 3.3 (113) 12.8 (37) 2.1 (76) <0.0001
Unplanned intubation, % (n) 2.6 (105) 5.8 (17) 2.4 (88) <0.0001
SSI–organ space, % (n) 2.6 (106) 16.4 (48) 1.6 (58) <0.0001
UTI, % (n) 2.5 (100) 6.5 (19) 2.2 (81) <0.0001
Pneumonia, % (n) 2.4 (95) 5.5 (16) 2.1 (79) <0.0001
VTE, % (n) 1.7 (69) 9.2 (27) 1.1 (42) <0.0001
Clostridium difficile colitis, % (n) 1.4 (58) 5.5 (16) 1.1 (42) <0.0001
Septic shock, % (n) 1.2 (50) 4.8 (14) 1.0 (36) <0.0001
Mechanical obstruction, % (n) 1.1 (43) 6.6 (19) 0.7 (24) <0.0001
Wound dehiscence, % (n) 1.0 (39) 2.4 (7) 0.8 (32) 0.010
Progressive renal insufficiency, % (n) 0.8 (33) 4.8 (14) 0.5 (19) <0.0001
SSI–deep space, % (n) 0.7 (30) 1.0 (3) 0.7 (27) 0.48
Acute myocardial infarction, % (n) 0.7 (29) 3.1 (9) 0.5 (20) <0.0001
Cardiac arrest, % (n) 0.7 (28) 1.7 (5) 0.6 (23) 0.024
Acute renal failure, % (n) 0.6 (23) 1.0 (3) 0.5 (20) 0.23
Stroke, % (n) 0.3 (11) 1.7 (5) 0.2 (6) <0.0001
Median length of stay, days 5 (0–82) 6 (1–58) 5 (0–82)
SSI = surgical site infection; OR = operating room; UTI = urinary tract infection; VTE = venous thromboembolism.
Bold p values indicate significance.
TABLE 6. Risk factors for readmission based on multivariate analysis
OR 95% CI, lower 95% CI, upper p
Postoperative CVA 10.0 2.70 37.0 0.001
Postoperative VTE 6.51 3.75 11.31 <0.0001
Organ space SSI 5.63 3.38 9.37 <0.0001
Postoperative progressive renal insufficiency 3.95 1.74 8.94 0.001
Postoperative Clostridium difficile colitis 3.61 1.81 7.18 <0.0001
Postoperative reoperation 3.12 2.03 4.79 <0.0001
Superficial SSI 2.78 1.87 4.16 <0.0001
Postoperative mechanical bowel obstruction 2.92 1.35 6.33 0.007
Postoperative acute myocardial infarction 2.92 1.12 7.57 0.028
Prolonged ileus 2.23 1.53 3.24 <0.0001
Postoperative UTI 1.89 1.05 3.38 0.033
CVA = cerebrovascular accident; SSI = surgical site infection; UTI = urinary tract infection; VTE = venous thromboembolism.
Bold p values indicate significance.
6. DISEASES OF THE COLON & RECTUM VOLUME 57: 1 (2014) 103
demonstrating the superiority of ERPs over the conven-
tional postoperative management of colorectal patients, a
continuing decrease in prolonged ileus may be seen. How-
ever, reducing the rate of superficial SSIs has proven to be a
difficult task despite tremendous effort on the part of physi-
cians and hospitals. Although process measures such as the
Surgical Care Improvement Program were introduced to
reduce infectious complications after surgery and are now
considered standard of care, the ability of these measures
to actually improve outcomes is highly controversial.15,20,21
This leads to the more general question of how to ap-
proach complications in colorectal surgery that are difficult
to impact.Similar to superficial SSIs,anastomotic leaks have
been studied extensively, but undisputed risk factors and
strategies to avoid them, short of avoiding an anastomosis,
remain elusive.Penalization for readmission related to some
complications may, therefore, not be the right approach.
Notably, several important patient-related factors, such
as age,diabetes mellitus,and cardiac comorbidities were not
found to be independent predictors of 30-day readmission,
although they must contribute to some degree by increasing
the risk for complications. In contrast to our study, Schnei-
der et al1
found patient-related factors such as older age and
severity of comorbidities to be important predictors, and
Wick et al2
found an association between a longer initial
length of stay (LOS (>7 days)) and readmission. Although
we did not find that older age was a risk factor, our data
do indicates that accumulating risk factors puts a patient at
risk for readmission (OR, 1.22), although not to the degree
that postoperative complications do (Table 6). The chain of
events among preoperative risk factors, postoperative com-
plications, and readmission is difficult to unravel. For many
patient factors and complications, this degree of correlation
between preoperative risk factors and postoperative com-
plications will always remain unclear, and any analysis of a
database that collects preoperative and postoperative data,
such as the NSQIP, does not allow us to completely unravel
this chain of events.This is a limitation that our study shares
with other recent similar analyses1-3
on readmission, as well
as most studies involving the NSQIP in general.1,16,22
The
commonly used methodology of performing univariate fol-
lowed by multivariate analysis aims to reduce confounding
factors but cannot completely exclude them.
Our results did not demonstrate an association be-
tween LOS and readmission rate. This finding is particu-
larly interesting in light of the increasing introduction of
ERPs, which have been shown to lead to a reduction in
LOS but have raised concerns about increased complica-
tions and readmission rates. These findings are consistent
with an increasing number of studies that confirm the
safety of ERPs.3,8,17–19,23
When discussing these findings, several strengths and
limitations of our study methodology have to be consid-
ered. Our results are derived from a thoroughly main-
tained multicenter database that adheres to strict data
recording and quality standards. We analyzed a compre-
hensive list of variables for their association with post-
operative readmission, many of which would be difficult
or impossible to assess in a randomized clinical trial. Be-
cause of its inclusion of a wide variety of hospitals, from a
rural community to large university hospitals, our patient
population may be considered representative of a real-
world patient care setting. Nevertheless, this study comes
with the limitations associated with any database analy-
sis, and true causal relations cannot be determined. The
MSQC database does not record reasons for readmissions
within 30 days, and, therefore, it is not possible to deter-
mine whether some readmissions were planned. In addi-
tion, our findings might be influenced by current surgical
practices in the state of Michigan, which may limit their
national generalizability.
In summary, postoperative complications account
for the majority of risk factors behind readmissions after
elective colectomy, whereas preoperative, patient-related
risk factors have less direct influence. Current strategies
addressing readmission rates should focus on reducing
preventable complications while still accepting that much
may not be completely avoidable. In addition, the issue of
readmission may need to be refocused on defining accept-
able rates of complications instead of widespread policies
aimed at penalizing all readmissions.
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