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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
https://doi.org/10.1186/s12884-022-04818-5
RESEARCH
Racial-ethnic disparities inpotentially
preventable complications aftercesarean
delivery inMaryland: anobservational cohort
study
Allison Lankford1, Laura Roland2, Christopher Jackson2, Jonathan Chow2, Ryan Keneally2, Amanda Jackson3,
Rundell Douglas4, Jeffrey Berger2 and Michael Mazzeffi2*
Abstract
Background: Potentially preventable complications are monitored as part of the Maryland Hospital Acquired Condi-
tions Program and are used to adjust hospital reimbursement. Few studies have evaluated racial-ethnic disparities in
potentially preventable complications.
Our study objective was to explore whether racial-ethnic disparities in potentially preventable complications after
Cesarean delivery exist in Maryland.
Methods: We performed a retrospective observational cohort study using data from the Maryland Health Services
Cost Review Commission database. All patients having Cesarean delivery, who had race-ethnicity data between
fiscal years 2016 and 2020 were included. Multivariable logistic regression modeling was performed to estimate risk-
adjusted odds of having a potentially preventable complication in patients of different race-ethnicity.
Results: There were 101,608 patients who had Cesarean delivery in 33 hospitals during the study period and met
study inclusion criteria. Among them, 1,772 patients (1.7%), experienced at least one potentially preventable compli-
cation. Patients who had a potentially preventable complication were older, had higher admission severity of illness,
and had more government insurance. They also had more chronic hypertension and pre-eclampsia (both P<0.001).
Median length of hospital stay was longer in patients who had a potentially preventable complications (4 days vs. 3
days, P<0.001) and median hospital charges were approximately $4,600 dollars higher, (P<0.001). The odds of having a
potential preventable complication differed significantly by race-ethnicity group (P=0.05). Hispanic patients and Non-
Hispanic Black patients had higher risk-adjusted odds of having a potentially preventable complication compared to
Non-Hispanic White patients, OR=1.26 (95% CI=1.05 to 1.52) and OR=1.17 (95% CI=1.03 to 1.33) respectively.
Conclusions: In Maryland a small percentage of patients undergoing Cesarean delivery experienced a potentially
preventable complication with Hispanic and Non-Hispanic Black patients disproportionately impacted. Continued
efforts are needed to reduce potentially preventable complications and obstetric disparities in Maryland.
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Open Access
*Correspondence: mimazzeffi@mfa.gwu.edu
2 Department of Anesthesiology and Critical Care Medicine, George
Washington University School of Medicine and Health Sciences, Washington
DC 20037, USA
Full list of author information is available at the end of the article
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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
Background
Caesarean delivery (CD) is the most common surgical
procedure performed in the United States with approx-
imately 30% of all pregnant patients and over one mil-
lion patients per year having CD [1]. Up to 20% of
patients who have CD experience postoperative com-
plications with the most common complications being
postpartum hemorrhage, wound infection, urinary
tract infection, endometritis, surgical site infection, and
reoperation for bleeding or infection [2]. Prior studies
suggest that between 2% and 15% of women have sur-
gical site infection after CD, which increases hospital
length of stay and morbidity [3, 4].
Postoperative complications occur more frequently
in Non-Hispanic Black and Hispanic patients in the
United States. In a prior study that used administra-
tive data from New York state, and included over one
million surgical patients, Non-Hispanic Black patients
had 18% increased odds of postoperative complications
after controlling for preoperative risk [5]. In an obser-
vational study that included over 40,000 bariatric sur-
gery patients, Non-Hispanic Black patients were 72%
more likely to experience postoperative complications,
including hospital readmission, when compared to
Non-Hispanic White patients [6].
Potentially preventable complication (PPCs) are
tracked by the Maryland Health Services Cost Review
Commission (HSCRC) as part of the Maryland Hos-
pital Acquired Conditions Program, which began in
2011. PPCs are identified using statewide administra-
tive data and an algorithm (PPC grouper) developed
by 3M Health Information Systems (Salt Lake City, UT
USA). PPC rates for individual hospitals are calculated
and used to adjust hospital reimbursement when a hos-
pital’s PPC rate is above the statewide mean. ere are
currently fifty-seven diagnoses, which are considered
to be potentially preventable, and are associated with
patient harm. Examples of PPCs include deep venous
thrombosis, pulmonary embolism, and surgical site
infection.
To our knowledge and based upon our literature
review, there are no studies exploring racial-ethnic dis-
parities in PPCs after CD. e aim of our study was to
explore whether there were racial-ethnic disparities
in PPCs after CD in Maryland. We hypothesized that
Non-Hispanic Black patients, Non-Hispanic Asian
patients, Non-Hispanic patients of other races, and
Hispanic patients, would have higher rates of PPCs
compared to Non-Hispanic White patients.
Methods
Patients
Patients who underwent elective, urgent, or emer-
gent CD for any indication in Maryland between fis-
cal years 2016 and 2020 (July 1st 2015 and June 30th
2020) were identified for inclusion using the HSCRC
database, which contains data for all hospitalized
patients in Maryland. The study period was selected
because it represented a period of consistent health-
care policy within the state, where the global budget
revenue program was in place and PPCs were recorded
as a quality metric. Medicare severity diagnosis related
group (DRG) codes were used to identify patients who
underwent CD. The following Medicare DRGs were
used: 783, 784, 785, 786, 787, and 788. Patients were
excluded from the analysis if they were missing race-
ethnicity data.
Patient Variables
Demographics including age group, race, and ethnicity
were collected for all patients. Race-ethnicity data were
based on administrative data officially submitted to the
HSCRC by Maryland hospitals. Race was categorized as
Non-Hispanic White, Non-Hispanic Black, Non-His-
panic Asian, Non-Hispanic patients of other races, and
Hispanic. Non-Hispanic White patients were considered
as the reference group because they were hypothesized
to have the lowest PPC incidence. Further, we collected
marital status and primary insurer (government, com-
mercial, or other). Medical data included all patient
refined (APR) severity of illness at hospital admission,
chronic hypertension, pre-eclampsia, diabetes mellitus,
gestational diabetes, prior CD, and preterm delivery.
Medical diagnoses were based on international clas-
sification of disease (ICD) 9 and 10 codes. Finally, we
collected data on hospital length of stay, total hospital
charges, and unplanned hospital readmission within
thirty days.
PPCs
e HSCRC identifies PPCs using proprietary soft-
ware developed by 3M Health Information Systems
(Salt Lake City, UT USA). Secondary diagnoses that are
not present at hospital admission are used to identify
specific complications using ICD-9 or 10 codes. PPC
methodology was originally developed using admin-
istrative data from California in the late 1990s and has
been refined over time. Patients in our study had PPCs
identified using PPC grouper versions 36.0 and 37.0.
Keywords: Cesarean delivery, Obstetrics, Healthcare quality, Disparities
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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
Supplemental Table1 lists the specific PPCs that were
recorded with PPC grouper 36.0 and 37.0. PPC catego-
ries included extreme complications (e.g. cardiac arrest,
shock), infectious complications (e.g. surgical site infec-
tion, urinary tract infection), and cardiovascular and
respiratory complications (e.g. congestive heart failure,
deep venous thrombosis, acute pulmonary edema).
Primary outcome
e study’s primary outcome was occurrence of any PPC
during hospitalization. Secondary outcomes were total
hospital charges, length of hospital stay, and unplanned
hospital readmission.
Statistical analysis
Statistical analysis was performed using SAS 9.4 (SAS
Corporation, Cary NC, USA). Continuous patient vari-
ables were summarized as median and interquartile
range (skewed variables) or mean ± standard deviation
(normal variables). Categorical variables were summa-
rized as the number and percentage of patients. Patient
characteristics were compared between patients who
did and did not have a PPC using the Wilcoxon Rank
Sum test, Student’s T test, Pearson’s Chi-Squared test,
or Fisher’s exact test as appropriate. PPC incidence was
calculated for each hospital in the state and was plotted
on a Figure along with the hospital’s total CD volume.
e number of PPCs in each race-ethnicity group was
compared using Fisher’s exact test. Additionally, we
created scatterplots with fitted regression lines show-
ing unadjusted relationships between PPC incidence
and the percentage of patients from a race-ethnicity
group in each hospital.
To explore whether race-ethnicity had an independ-
ent association with PPCs, we performed multivariable
logistic regression, where occurrence of any PPC was
modeled as the dependent variable. Independent vari-
ables included in the model were race-ethnicity group
and variables that were thought to be a priori confound-
ers including age group, primary payer, year, hospital,
prior CD, chronic hypertension, diabetes mellitus, pre-
eclampsia, admission APR severity of illness, and pre-
term delivery. Odds ratios with 95% confidence intervals
were calculated for all independent variables in the
logistic regression model. Model diagnostics included
goodness of fit testing and area under the receiver oper-
ating characteristic curve analysis. e Strengthening
the reporting of observational studies in epidemiology
checklist was referenced and completed in preparing
the manuscript.
Fig. 1 Figure shows study enrollment and exclusions
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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
Ethics approval
e George Washington University institutional review
board approved the study, determined it to be exempt
as non-human subjects research, and waived the
requirement for written informed consent. All methods
were carried out in accordance with relevant guidelines
and regulations.
Results
Figure1 shows the study enrollment diagram. A total
of 102,940 patients had CD in 33 hospitals during the
five-year study period. One thousand three hundred
thirty-two patients were excluded because of missing
race-ethnicity data and 101,608 CD patients were ana-
lyzed. Among them, 1,772 patients (1.7%), experienced
Table 1 Patient characteristics
APRall patient rened, PPCpotentially preventable complication
Variable No PPC
N=99836 PPC
N=1772
P value
Age group
≤ 19 2313 (2.3) 59 (3.3) <0.001
20-24 12015 (12.0) 215 (12.1)
25-29 24852 (24.9) 411 (23.2)
30-34 33119 (33.2) 550 (31.0)
35-39 21453 (21.5) 391 (22.1)
40-44 5489 (5.5) 121 (6.8)
≥ 45 595 (0.6) 25 (1.5)
Race-ethnicity group
Non-Hispanic White 43495 (43.6) 659 (37.2) <0.001
Non-Hispanic Black 35856 (35.9) 684 (38.6)
Non-Hispanic Asian 6099 (6.1) 111 (6.3)
Non-Hispanic other 4226 (4.2) 79 (4.4)
Hispanic 10160 (10.2) 239 (13.5)
Marital status
Single 39895 (40.0) 760 (42.9) <0.001
Married 56567 (56.7) 933 (52.7)
Separated or divorced 1808 (1.7) 39 (2.1)
Widow 105 (0.1) 0 (0)
Not reported 1459 (1.5) 40 (2.3)
Primary payer
Government 43855 (43.9) 876 (49.4) <0.001
Commercial insurance 54688 (54.8) 876 (49.4)
Other 1293 (1.3) 20 (1.2)
Admission APR severity of illness
Mild 55375 (55.5) 560 (31.6) <0.001
Moderate 33072 (33.1) 583 (32.9)
Severe 10891 (10.9) 517 (29.2)
Extreme 498 (0.5) 112 (6.3)
Chronic hypertension 1980 (2.0) 78 (4.4) <0.001
Pre-eclampsia 8620 (8.6) 307 (17.3) <0.001
Diabetes mellitus 2062 (2.1) 59 (3.3) <0.001
Gestational diabetes 10593 (10.6) 176 (9.9) 0.36
Prior Cesarean delivery 16692 (16.7) 283 (16.0) 0.40
Preterm delivery 2936 (2.9) 101 (5.7) <0.001
Total length of hospital stay 3 [3, 4] 4 [3, 5] <0.001
Total hospital charges ($) 8469 [6440, 11642] 13111 [9152, 20423] <0.001
Unplanned hospital readmission 1635 (1.6) 81 (4.6) <0.001
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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
at least one PPC. Table1 lists characteristics of patients
who had a PPC and those who did not. Patients who
had PPCs were older and were less likely to be married.
Patients who had PPCs were also less likely to have
commercial insurance and had higher admission sever-
ity of illness. Specifically, patients who had PPCs had a
two-fold higher prevalence of chronic hypertension and
pre-eclampsia (both P<0.001). Median length of hospi-
tal stay was longer in patients with PPCs (4 days vs. 3
days, P<0.001), median hospital charges were approxi-
mately $4,600 dollars higher (P<0.001), and unplanned
hospital readmissions were more frequent (4.6% vs.
1.6%, P<0.001).
Figure 2 shows the PPC incidence for individual
hospitals in Maryland, which varied from 0% to 4.3%.
Table2 lists select PPCs of interest and their incidences.
e majority of patients who had a PPC (84.1%), had a
single event, while 5.5% of patients had 3 or more PPCs.
Infectious complications including “major puerperal
infection” and “reopening of surgical site for infection”
were two of the most common PPCs. Table3 shows the
number of PPCs by race-ethnicity group. e number
of PPCs differed significantly between groups (P<0.001)
and the largest difference occurred in patients who had
a single PPC. Figure3 shows unadjusted relationships
between race-ethnicity group and PPC incidence in
Maryland hospitals.
Table4 lists the results of the multivariable logistic
regression model. e risk-adjusted odds of having a
PPC were significantly different for patients from dif-
ferent race-ethnicity groups (P=0.05). e AUROC for
the multivariable model was 0.72 suggesting good dis-
crimination. Hispanic and Non-Hispanic Black patients
had higher risk-adjusted odds of having a PPC com-
pared to Non-Hispanic White patients, OR=1.26 (95%
CI=1.05 to 1.52) and OR=1.17 (95% CI=1.03 to 1.33)
respectively. Other variables that had a significant asso-
ciation with PPC occurrence included age, year, prior
CD, pre-eclampsia, admission APR severity of illness,
and hospital (all P<0.05).
Discussion
In a five-year, statewide observational cohort study
that included over 100,000 CD patients, PPCs occurred
in 1.7% of patients. PPCs were associated with both
increased length of hospital stay and increased hospital
charges. After adjusting for admission severity of illness
and other potential confounders, Hispanic and Non-His-
panic Black patients were disproportionately impacted by
PPCs. ere also appeared to be considerable variation
in the incidence of PPCs between hospitals, suggesting
that the quality of obstetric care may vary considerably
between hospitals.
Fig. 2 Figure shows five-year PPC incidence for individual hospitals that performed Caesarean delivery in Maryland from fiscal year 2016 to 2020
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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
In 2011, Maryland began to collect data on PPCs as part
of its hospital acquired conditions program, which is dis-
tinct from the Centers for Medicare and Medicaid Ser-
vices (CMS) hospital acquired conditions program. It is
estimated that common hospital acquired conditions (e.g.
pressure ulcers, surgical site infections, catheter associated
urinary tract infections) increase healthcare spending in
the Medicare program by approximately 150 million dollars
per year, adding significant cost to United States healthcare
[7]. Both CMS and Maryland penalize low-performing
Table 2 Select potentially preventable complications in cohort
*2205 total PPCs in 1772 patients
PPCpotentially preventable complication
Variable N (%)
Number of PPCs per patient
1 1490 (1.5)
2 185 (0.2)
3 or more 97 (0.09)
Select PPC incidences
Neurologic
Stroke or intracranial hemorrhage 5 (0.005)
Respiratory
Acute pulmonary edema and respiratory failure without ventilation 86 (0.08)
Acute pulmonary edema and respiratory failure with ventilation 14 (0.01)
Aspiration pneumonia 7 (0.007)
Pulmonary embolism 6 (0.006)
Cardiovascular
Cardiac arrest 7 (0.007)
Deep venous thrombosis 4 (0.004)
Infectious
Clostridium difficile colitis 4 (0.004)
Sepsis 19 (0.02)
Major puerperal infection 102 (0.1)
Reopening of surgical site for infection 60 (0.06)
Urinary tract infection 8 (0.008)
Catheter associated-urinary tract infection 3 (0.003)
Renal
Renal failure requiring dialysis 1 (0.001)
Hematologic
Perioperative hemorrhage without hemorrhage control procedure 42 (0.04)
Perioperative hemorrhage with hemorrhage control procedure 16 (0.02)
Obstetric
Medical and anesthesia obstetric complications 391 (0.4)
Table 3 Number of potentially preventable complications by race-ethnicity group
*P<0.001 for the comparison between groups
PPC potentially preventable complication
Number of PPCs Non-Hispanic White Non-Hispanic Black Non-Hispanic Asian Non-Hispanic
other races Hispanic
0 43495 (98.5) 35856 (98.1) 6099 (98.2) 4226 (98.2) 10160 (97.7)
1 569 (1.3) 556 (1.5) 87 (1.4) 67 (1.6) 211 (2.0)
2 62 (0.1) 85 (0.2) 12 (0.2) 7 (0.1) 19 (0.2)
3 or more 28 (0.1) 43 (0.2) 12 (0.2) 5 (0.1) 9 (0.1)
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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
hospitals with a financial deduction of approximately 1%
when hospital acquired conditions (i.e. PPCs) occur at a
high rate in an individual hospital.
CD is the most common surgical procedure performed
in the United States with over 500,000 patients per year
having CD. ere are few studies describing the incidence
of PPCs after CD. Cardiovascular events are reported to
occur in 0.2% of CD patients [8], infectious complica-
tions are reported to occur in 5-9% of patients [9–11],
and VTEs are reported to occur in 0.3% of patients [12].
To our knowledge and based on our literature review, few
studies have explored racial disparities in PPCs after CD.
Prior studies have demonstrated that that Non-Hispanic
Black patients and Hispanic patients are more likely to
undergo primary CD, which puts them at greater risk for
complications during childbirth [13–15]. Prior studies
have also shown racial disparities in preterm birth rates
[16, 17].
ere are multiple potential causes of racial dispari-
ties in maternal and neonatal outcomes including poor
access to antenatal care, disproportionate representa-
tion in low-quality hospitals, lack of adequate health-
care insurance, and a higher prevalence of comorbid
conditions including diabetes mellitus, hypertension,
and anemia [18, 19]. In the United States, differen-
tial access to high-quality hospitals is thought to be a
major factor affecting healthcare outcomes with Non-
Hispanic Black patients and Hispanic patients having
less access to high-quality hospitals [20, 21]. Our data
confirm that in Maryland the racial composition of
patients differed dramatically by hospital, and that in
hospitals with a high percentage of Hispanic patients
there were more PPCs.
Our study highlights a continued need to address
disparities in the quality of obstetric care provided
in Maryland. Although PPCs may not be avoidable
in every case, there are interventions that can reduce
select PPCs, including surgical site infection. For exam-
ple, appropriate antibiotic prophylaxis, appropriate
preoperative skin preparation, use of clippers rather
than razors, placental removal by traction rather than
with manual removal, and suture closure of the subcu-
taneous tissue in deep wounds may all reduce surgical
site infections after CD [3]. Device-related infections,
such as catheter associated urinary tract infection, may
be avoidable with early device removal and other best
practices [22]. Standardizing perioperative procedures
is an important aspect of ensuring quality and safety in
surgical care. e implementation of Enhanced Recov-
ery After Surgery (ERAS) protocols effectively elimi-
nated racial disparities in postoperative length of stay
among patients undergoing colorectal surgery [23].
Similarly, Enhanced Recovery After Cesarean (ERAC)
delivery protocols may reduce or even eliminate racial
disparities in PPCs after CD.
Fig. 3 Figure shows unadjusted relationships between race-ethnicity group composition and PPC incidence in Maryland obstetric hospitals
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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
Future studies should explore why PPCs are more
common in patients of different race-ethnicity. Contrib-
uting factors may include reduced access to high-qual-
ity hospitals, unconscious and conscious bias among
healthcare workers, and differential access to regular
antenatal care. Obstetric quality bundles and health-
care worker bias training may reduce racial disparities in
PPCs and should be evaluated as potential interventions.
Our study’s principal strength is that it uses statewide
validated data from Maryland’s HSCRC, which is used
to assess hospital quality and adjust reimbursement. Our
study also has limitations. First, clinical diagnoses were
based on ICD codes rather than being entered by trained
clinical personnel. Second, although we used APR sever-
ity of illness at admission to adjust for risk, this may not
have been a complete risk adjustor. ird, our data are
from a single state and hence they may not reflect prac-
tice throughout the United States. Fourth, race-ethnicity
data were reported to the HSCRC by individual hospitals
in Maryland and their practices for collecting this infor-
mation may have been variable. Fifth, there may have
been unobserved confounders that were not controlled
for in our analysis. Finally, some PPCs may have been
underreported in the HSCRC dataset.
Conclusions
In summary, in a large observational cohort study, we
found that PPC incidence is variable by hospital in Mary-
land and that Hispanic patients and Non-Hispanic Black
patients were disproportionately impacted. Further-
more, we found that there was considerable variation in
PPC incidence by hospital, suggesting that the quality
of obstetric care differs by hospital. ese findings high-
light the continued need to address healthcare disparities
through innovative programs in the United States. Also,
further studies are needed to determine whether finan-
cial penalties for hospitals with a high PPC incidence
leads to improvement in the quality of care or further
harm for vulnerable groups who are disproportionately
represented in these hospitals.
Abbreviations
APR: all patient refined; CD: Cesarean delivery; CMS: centers for medicare and
medicaid; ERAC : enhanced recovery after Cesarean; ERAS: enhanced recovery
after surgery; HSCRC : health services cost review commission; ICD: interna-
tional classification of disease; OR: odds ratio; PPC: potentially preventable
complications.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12884- 022- 04818-5.
Additional le1.
Acknowledgements
We would like to thank the Maryland Health Services Cost Review Commis-
sion for providing the data for this study, particularly Oscar Ibarra. The Health
Services Cost Review Commission was not responsible for the study design or
analysis.
Authors’ contributions
AL This author made substantial contributions to the conception, design,
acquisition, analysis, and interpretation of study data, drafted the manuscript,
provided critical revisions to the manuscript, agreed to be accountable for
all aspects of the work, approved the final manuscript, and is the author
responsible for archiving the study files. LR This author made substantial con-
tributions to the conception, design, acquisition, analysis, and interpretation
Table 4 Multivariable regression analysis for occurrence of any
potentially preventable complication
Hospital was also included in the model as an independent variable. The P value
for hospital was <0.001. Individual odds ratios for 33 hospitals within the state
were not included in the table
AUROC for the model was 0.72,
APR all patient rened, CD Caesarean delivery
Variable Odds ratio with 95% CI P value
Age Group
<30 Ref 0.009
30-34 1.04 (0.93 to 1.29)
35-39 1.13 (0.94 to 1.29)
≥ 40 1.37 (1.13 to 1.65)
Race group
Non-Hispanic White Ref 0.05
Non-Hispanic Black 1.17 (1.03 to 1.33)
Non-Hispanic Asian 1.20 (0.97 to 1.49)
Non-Hispanic other 1.15 (0.90 to 1.47)
Hispanic 1.26 (1.05 to 1.52)
Primary payer
Government Ref 0.24
Commercial 0.93 (0.82 to 1.04)
Other 0.76 (0.48 to 1.20)
Year
2016 Ref <0.001
2017 1.12 (0.96 to 1.31)
2018 0.99 (0.85 to 1.16)
2019 1.07 (0.91 to 1.25)
2020 0.78 (0.66 to 0.92)
Prior CD 0.79 (0.69 to 0.91) <0.001
Chronic hypertension 1.03 (0.79 to 1.34) 0.83
Diabetes mellitus 0.77 (0.58 to 1.01) 0.06
Pre-eclampsia 1.33 (1.15 to 1.54) <0.001
Admission APR severity of illness
Mild Ref <0.001
Moderate 1.81 (1.61 to 2.04)
Severe 4.55 (3.98 to 5.20)
Extreme 21.60 (17.09 to 27.31)
Pre-term delivery 0.92 (0.74 to 1.13) 0.42
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Lankfordetal. BMC Pregnancy and Childbirth (2022) 22:494
of study data, drafted the manuscript, provided critical revisions to the manu-
script, agreed to be accountable for all aspects of the work, and approved the
final manuscript. CJ This author made substantial contributions to the concep-
tion, design, acquisition, analysis, and interpretation of study data, drafted
the manuscript, provided critical revisions to the manuscript, agreed to be
accountable for all aspects of the work, and approved the final manuscript.
JC This author made substantial contributions to the conception, design,
acquisition, analysis, and interpretation of study data, drafted the manuscript,
provided critical revisions to the manuscript, agreed to be accountable for all
aspects of the work, and approved the final manuscript. RK This author made
substantial contributions to the conception, design, acquisition, analysis, and
interpretation of study data, drafted the manuscript, provided critical revisions
to the manuscript, agreed to be accountable for all aspects of the work, and
approved the final manuscript. AJ This author made substantial contributions
to the conception, design, acquisition, analysis, and interpretation of study
data, drafted the manuscript, provided critical revisions to the manuscript,
agreed to be accountable for all aspects of the work, and approved the final
manuscript. RD This author made substantial contributions to the concep-
tion, design, acquisition, analysis, and interpretation of study data, drafted
the manuscript, provided critical revisions to the manuscript, agreed to be
accountable for all aspects of the work, and approved the final manuscript.
JB This author made substantial contributions to the conception, design,
acquisition, analysis, and interpretation of study data, drafted the manuscript,
provided critical revisions to the manuscript, agreed to be accountable for all
aspects of the work, and approved the final manuscript. MM This author made
substantial contributions to the conception, design, acquisition, analysis, and
interpretation of study data, drafted the manuscript, provided critical revisions
to the manuscript, agreed to be accountable for all aspects of the work,
approved the final manuscript, and is the author responsible for archiving the
study files.
Funding
None to declare.
Availability of data and materials
The datasets generated and/or analyzed during the current study are not
publicly available because of the data use agreement that was signed to
use the HSCRC data. However, the data can be obtained through a formal
request and data use agreement with the HSCRC https:// hscrc. maryl and.
gov/ Pages/ hsp- data- reque st. aspx. Information on how to obtain the data
from the HSCRC can be obtained from Dr. Michael Mazzeffi (mimaz zeffi@
mfa. gwu. edu).
Declarations
Ethics approval and consent to participate
The George Washington University institutional review board approved the
study, exempted it as non-human subjects research, and waived the require-
ment for written informed consent from subjects who were included/partici-
pated. All methods were carried out in accordance with relevant guidelines
and regulations.
Consent for publication
The George Washington University institutional review board waived the
requirement for written informed consent from subjects to publish the study’s
results.
Competing interests
None to declare.
Author details
1 Department of Obstetrics and Gynecology, University of Maryland School
of Medicine, Baltimore, MD, USA. 2 Department of Anesthesiology and Critical
Care Medicine, George Washington University School of Medicine and Health
Sciences, Washington DC 20037, USA. 3 Department of Obstetrics and Gyne-
cology, Walter Reed National Medical Center, Bethesda, MD, USA. 4 George
Washington University Milken Institute School of Public Health, Washington
DC, USA.
Received: 8 April 2022 Accepted: 7 June 2022
References
1. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK. Births: Final Data for
2019. Natl Vital Stat Rep. 2021;70(2):1–51.
2. Hager RM, Daltveit AK, Hofoss D, Nilsen ST, Kolaas T, Oian P, et al. Compli-
cations of cesarean deliveries: rates and risk factors. Am J Obstet Gynecol.
2004;190(2):428–34.
3. Kawakita T, Landy HJ. Surgical site infections after cesarean delivery: epi-
demiology, prevention and treatment. Matern Health Neonatol Perinatol.
2017;3:12.
4. Zuarez-Easton S, Zafran N, Garmi G, Salim R. Postcesarean wound infec-
tion: prevalence, impact, prevention, and management challenges. Int J
Womens Health. 2017;9:81–8.
5. Fiscella K, Franks P, Meldrum S, Barnett S. Racial disparity in surgical com-
plications in New York State. Ann Surg. 2005;242(2):151–5.
6. Nafiu OO, Mpody C, Michalsky MP, Tobias JD. Unequal rates of postopera-
tive complications in relatively healthy bariatric surgical patients of white
and black race. Surg Obes Relat Dis. 2021;17(7):1249–55.
7. Kandilov AM, Coomer NM, Dalton K. The impact of hospital-acquired
conditions on Medicare program payments. Medicare Medicaid Res Rev.
2014;4(4).
8. Larsson C, Matsson A, Mooe T, Soderstrom L, Tunon K , Nordin P. Cardio-
vascular complications following cesarean section and vaginal delivery: a
national population-based study. J Matern Fetal Neonatal Med. 2021:1–8.
https:// doi. org/ 10. 1080/ 14767 058. 2021. 19418 51.
9. Gomaa K, Abdelraheim AR, El Gelany S, Khalifa EM, Yousef AM, Hassan H.
Incidence, risk factors and management of post cesarean section surgical
site infection (SSI) in a tertiary hospital in Egypt: a five year retrospective
study. BMC Pregnancy Childbirth. 2021;21(1):634.
10. Wloch C, Wilson J, Lamagni T, Harrington P, Charlett A, Sheridan E. Risk
factors for surgical site infection following caesarean section in England:
results from a multicentre cohort study. BJOG. 2012;119(11):1324–33.
11. Tita AT, Szychowski JM, Boggess K, Saade G, Longo S, Clark E, et al.
Adjunctive Azithromycin Prophylaxis for Cesarean Delivery. N Engl J Med.
2016;375(13):1231–41.
12. Blondon M, Casini A, Hoppe KK, Boehlen F, Righini M, Smith NL. Risks of
Venous Thromboembolism After Cesarean Sections: A Meta-Analysis.
Chest. 2016;150(3):572–96.
13. Braveman P, Egerter S, Edmonston F, Verdon M. Racial/ethnic differences
in the likelihood of cesarean delivery, California. Am J Public Health.
1995;85(5):625–30.
14. Getahun D, Strickland D, Lawrence JM, Fassett MJ, Koebnick C, Jacobsen
SJ. Racial and ethnic disparities in the trends in primary cesarean delivery
based on indications. Am J Obstet Gynecol. 2009;201(4):422 e421–7.
15. Edmonds JK, Yehezkel R, Liao X, Moore Simas TA. Racial and ethnic dif-
ferences in primary, unscheduled cesarean deliveries among low-risk
primiparous women at an academic medical center: a retrospective
cohort study. BMC Pregnancy Childbirth. 2013;13:168.
16. Braveman PA, Heck K, Egerter S, Marchi KS, Dominguez TP, Cubbin C, et al.
The role of socioeconomic factors in Black-White disparities in preterm
birth. Am J Public Health. 2015;105(4):694–702.
17. Braveman P, Heck K, Eger ter S, Dominguez TP, Rinki C, Marchi KS, et al.
Worry about racial discrimination: A missing piece of the puzzle of Black-
White disparities in preterm birth? PLoS One. 2017;12(10):e0186151.
18. Burris HH, Hacker MR. Birth outcome racial disparities: A result of
intersecting social and environmental factors. Semin Perinatol.
2017;41(6):360–6.
19. Alhusen JL, Bower KM, Epstein E, Sharps P. Racial Discrimination and
Adverse Birth Outcomes: An Integrative Review. J Midwifery Womens
Health. 2016;61(6):707–20.
20. Hasnain-Wynia R, Kang R, Landrum MB, Vogeli C, Baker DW, Weissman JS.
Racial and ethnic disparities within and between hospitals for inpatient
quality of care: an examination of patient-level Hospital Quality Alliance
measures. J Health Care Poor Underserved. 2010;21(2):629–48.
21. Rangrass G, Ghaferi AA, Dimick JB. Explaining racial disparities in
outcomes after cardiac surgery: the role of hospital quality. JAMA Surg.
2014;149(3):223–7.
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23. Wahl TS, Goss LE, Morris MS, Gullick AA, Richman JS, Kennedy GD, et al.
Enhanced Recovery After Surgery (ERAS) Eliminates Racial Disparities
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