Abstract
Objective:
We sought to a) use the Robson 10-Group Classification System (TGCS), which classifies deliveries into ten mutually exclusive groups, to characterize the groups that are primary contributors to cesarean delivery frequencies, b) describe inter-hospital variations in cesarean delivery frequencies, and c) evaluate the contribution of patient characteristics by TGCS group to hospital variation in cesarean delivery frequencies.
Study Design:
This was a secondary analysis of an observational cohort of 115,502 deliveries from 25 hospitals between 2008 and 2011. The TGCS was applied to the cohort and each hospital. We identified and compared the TGCS groups with the greatest relative contributions to cohort and hospital cesarean delivery frequencies. We assessed variation in hospital cesarean deliveries attributable to patient characteristics within TGCS groups using hierarchical logistic regression.
Results:
A total of 115,211 patients were classifiable in the TGCS (99.7%). The cohort cesarean delivery frequency was 31.4% (hospital range 19.1–39.3%). Term singletons in vertex presentation with a prior cesarean delivery (group 5) were the greatest relative contributor to cohort (34.8%) and hospital cesarean delivery frequencies (median 33.6%; range 23.8–45.5%). Nulliparous term singletons in vertex presentation (groups 1 [spontaneous labor] and 2 [induced or absent labor] – 28.9%), term singletons in vertex presentation with a prior cesarean delivery (group 5 – 34.8%), and preterm singletons in vertex presentation (group 10 – 9.8%) contributed to 73.2% of the relative cesarean delivery frequency for the cohort and were correlated with hospital cesarean delivery frequencies (Spearman’s rho = 0.96). Differences in patient characteristics accounted for 34.1% of hospital-level cesarean delivery variation in group 2.
Conclusion:
The 10-Group Classification System highlights the contribution of nulliparous term singletons in vertex presentation to cesarean delivery frequencies and the impact of patient characteristics on hospital-level variation in cesarean deliveries among nulliparous patients with induced or absent labor.
Keywords: cesarean delivery, 10-Group Classification System, Robson, nulliparous term singleton vertex
INTRODUCTION
Cesarean delivery classification systems serve as a form of perinatal audit.1 By monitoring cesarean delivery frequencies, these systems can focus quality improvement efforts. Cesarean delivery has a complex influence on maternal and perinatal outcomes, wherein increased cesarean delivery frequencies are not always associated with improved maternal and perinatal outcomes.2 While this underscores the utility of monitoring cesarean delivery frequencies, there is no universally accepted classification scheme.1
The Joint Commission promotes the cesarean delivery frequency among nulliparous term singletons in vertex presentation (NTSV) as a quality metric, focusing on the first cesarean delivery in a low-risk population.3 By contrast, the World Health Organization (WHO) and International Federation of Gynecology and Obstetrics endorse the 10-Group Classification System (TGCS),4,5 which classifies all deliveries into ten mutually exclusive groups using obstetric characteristics (Table 1).6 Notable TGCS populations include groups 1 and 2, which are NTSV patients stratified by type of labor, and group 5, which consists of term singletons in vertex presentation with a prior cesarean delivery.
Table 1:
Robson 10-Group Classification System
| Group | Description |
|---|---|
| 1 | Nulliparous term (≥37 weeks), singleton, vertex, spontaneous labor |
| 2 | Nulliparous term (≥37 weeks), singleton, vertex, induced or absent labor |
| 3 | Multiparous term (≥37 weeks), singleton, vertex, spontaneous labor |
| 4 | Multiparous term (≥37 weeks), singleton, vertex, induced or absent labor |
| 5 | Term (≥37 weeks), singleton, vertex, prior cesarean delivery |
| 6 | Nulliparous, breech |
| 7 | Multiparous, breech (includes prior cesarean delivery) |
| 8 | Multiple gestation (includes prior cesarean delivery) |
| 9 | Singleton, oblique or transverse lie (includes prior cesarean delivery) |
| 10 | Preterm (<37 weeks), singleton, vertex (includes prior cesarean delivery) |
There is limited published U.S. data on the TGCS.7,8 Furthermore, there are conflicting data regarding the ability of the TGCS or similar classification schemes to adequately account for case-mix.9–12 We applied the TGCS to a multicenter U.S. cohort. Our first two objectives were descriptive as we sought to identify the TGCS groups that are the primary contributors to cesarean delivery frequencies and to describe inter-hospital variations in cesarean delivery frequencies. For our third objective, we sought to evaluate the contribution of patient characteristics by TGCS group to hospital variation in cesarean delivery frequencies. We hypothesized that patient characteristics would contribute most to variation in cesarean deliveries among low-risk nulliparous women (groups 1 and 2).
MATERIALS AND METHODS
This is a secondary analysis of the Assessment of Perinatal Excellence (APEX) Study, which was an observational cohort consisting of 115,502 mother and infant pairs who delivered at any of 25 hospitals in the Eunice Kennedy Shriver National Institute of Child Health and Human Development Maternal-Fetal Medicine Units Network in the U.S. between March 2008 and February 2011. Institutional review board approval was obtained from all study sites. A complete description of the study design and methodology was previously published.13 Briefly, patients met inclusion criteria for APEX if they delivered on randomly selected days after being admitted with a living fetus at or beyond 23 weeks’ gestation. Trained and certified research personnel abstracted data from the medical records of study participants including patient demographics, maternal and neonatal outcomes, characteristics of the providers and hospitals involved in patient care, and obstetric care measures.
Patients met inclusion criteria for this analysis if they had sufficient data to permit TGCS classification. The TGCS was first applied to the entire cohort and then to each of the 25 study hospitals. The percentage of patients who were unable to be classified was utilized to assess the quality of the cohort for TGCS application.
The first two objectives of our study represented descriptive analyses. We examined the baseline characteristics of the study cohort including patients who underwent cesarean delivery. We then evaluated the cesarean frequencies and relative sizes of the various TGCS groups. After identifying the TGCS groups that represented the primary determinants of cesarean delivery in the APEX cohort, we assessed the contribution of these groups to individual hospital cesarean delivery frequencies. Specifically, we examined the correlation between each hospital’s cumulative cesarean delivery frequency for the groups identified as the primary determinants of cesarean delivery at the APEX cohort level and the hospital’s overall cesarean delivery frequency. Correlations were assessed using Spearman’s rank correlation.
We then quantified the reduction in variance in the hospital frequency of cesarean deliveries that was attributable to select patient characteristics within each TGCS grouping using hierarchical logistic regression. The first logistic regression equation incorporated only the hospitals as random-effect terms. The second level of the model incorporated select maternal and neonatal characteristics. Characteristics were chosen a priori based on their potential to contribute to cesarean delivery frequencies. Analyzed characteristics included maternal age, body mass index, hypertensive disorders, diabetes mellitus, smoking, amniotic fluid abnormalities, premature rupture of membranes, gestational age, size for gestational age, presence of suspected fetal anomalies, and disorders of placentation including abruption, placenta previa, or placenta accreta. Race-ethnicity and insurance status were not included as these adjustments reinforce health disparities. Per the methods used by Synnes et al.,14 each hierarchical logistic regression equation contained a random effects term (bo), and it is the standard deviation (σ) of this term that serves to quantify the overall variation in outcome frequency across the hospitals. The difference in the value of σ after the maternal and neonatal characteristics are added to the model quantifies the reduction in variance between hospitals explained by the additional characteristics.
SAS software (SAS Institute, Cary, NC) was used for the statistical analyses. Statistical significance was defined as P < 0.05 and 95% confidence intervals were calculated for multivariable models. No imputation for missing data was performed.
RESULTS
Of the 115,502 patients in the APEX study, 115,211 (99.7%) were able to be classified using the TGCS. The overall cohort cesarean delivery frequency was 31.4% with a range across hospitals from 19.1% to 39.3%. The baseline characteristics of patients in the cohort and those undergoing cesarean delivery are outlined in Table 2. The cesarean delivery frequency among the 291 patients who were unable to be classified was 63.6%. The majority of these patients were unable to be classified due to missing data regarding fetal presentation.
Table 2:
Baseline patient characteristics
| Baseline characteristics | Cohort (n=115,211) | Cesarean delivery (n=36,091) |
|---|---|---|
| Age, years | 28.2 ± 6.2 | 29.5 ± 6.2 |
| <20 | 10,167 (8.8) | 2,073 (5.7) |
| 20–24.9 | 24,256 (21.1) | 6,377 (17.7) |
| 25–29.9 | 30,997 (26.9) | 9,218 (25.5) |
| 30–34.9 | 30,486 (26.5) | 10,293 (28.5) |
| ≥35 | 19,305 (16.8) | 8,130 (22.5) |
| Race-ethnicity | ||
| Non-Hispanic White | 51,883 (45.0) | 16,310 (45.2) |
| Non-Hispanic Black | 23,821 (20.7) | 7,763 (21.5) |
| Non-Hispanic Asian | 5,983 (5.2) | 1,996 (5.5) |
| Hispanic | 27,238 (23.6) | 8,026 (22.2) |
| Other | 5,080 (4.4) | 1,601 (4.4) |
| Not documented | 1,206 (1.0) | 395 (1.1) |
| BMI at delivery, kg/m2 | 31.3 ± 6.4 | 33.0 ± 7.0 |
| <25 | 14,211 (12.6) | 2,996 (8.4) |
| 25–29.9 | 41,177 (36.5) | 10,652 (30.0) |
| 30–34.9 | 32,013 (28.4) | 10,739 (30.2) |
| 35–39.9 | 15,045 (13.3) | 5,958 (16.8) |
| ≥40 | 10,442 (9.2) | 5,184 (14.6) |
| Insurance status | ||
| Private | 57,295 (50.1) | 18,977 (52.9) |
| Government assisted | 45,021 (39.4) | 13,623 (38.0) |
| Uninsured | 11,971 (10.5) | 3,240 (9.0) |
| Tobacco use | 11,341 (9.9) | 3,721 (10.3) |
| Any hypertension | 13,243 (11.5) | 5,955 (16.5) |
| Diabetes mellitus | ||
| None | 106,446 (92.4) | 31,947 (88.6) |
| Gestational | 1,725 (1.5) | 1,019 (2.8) |
| Pregestational | 6,978 (6.1) | 3,107 (8.6) |
| Amniotic fluid abnormality | ||
| Normal | 109,598 (95.1) | 33,653 (93.2) |
| Oligohydramnios | 4,693 (4.1) | 1,895 (5.3) |
| Polyhydramnios | 920 (0.8) | 543 (1.5) |
| Chorioamnionitis | 4,058 (3.5) | 1,582 (4.4) |
| Disorder of placentation | ||
| Abruption | 924 (0.8) | 632 (1.8) |
| Placenta accreta | 158 (0.1) | 130 (0.4) |
| Placenta previa | 461 (0.4) | 460 (1.3) |
| EGA at delivery, weeks | 38.4 ± 2.3 | 37.8 ± 2.9 |
| 230–276 | 1,080 (0.9) | 681 (1.9) |
| 280–336 | 3,554 (3.1) | 2,066 (5.7) |
| 340–366 | 8,939 (7.8) | 3,724 (10.3) |
| 370–376 | 10,397 (9.0) | 3,408 (9.4) |
| 380–386 | 20,280 (17.6) | 5,997 (16.6) |
| 390–396 | 37,496 (32.5) | 12,501 (34.6) |
| 400–406 | 23,821 (20.7) | 5,070 (14.0) |
| 410–416 | 8,992 (7.8) | 2,427 (6.7) |
| ≥420 | 652 (0.6) | 217 (0.6) |
| Size for gestational age | ||
| Small | 10,660 (9.3) | 3,695 (10.2) |
| Appropriate | 95,487 (82.9) | 28,494 (79.0) |
| Large | 9,045 (7.9) | 3,892 (10.8) |
| Fetal anomaly | 3,575 (3.1) | 1,656 (4.6) |
All values presented as n (%), mean ± standard deviation, or median (interquartile range).
Abbreviations: BMI, body mass index; HIV, human immunodeficiency virus; EGA, estimated gestational age
The TGCS breakdown for the APEX cohort is provided in Supplemental Table 1. Groups 1–4 consist of nulliparous and multiparous patients with term singleton gestations in vertex presentation and no history of prior cesarean deliveries. These groups constituted 71.2% of the study population (Table 3). Cesarean delivery frequencies were higher among nulliparous term singletons in vertex presentation (groups 1 and 2), particularly those with induced or absent labor (group 2). The 14,374 patients in group 2 with induced labor had a 35.2% cesarean delivery frequency. The cesarean delivery frequency for patients undergoing elective induction of labor was 28.5% as compared to 36.2% for those undergoing induction of labor for a non-elective indication. In total, nulliparous patients from groups 1 and 2, which approximate the NTSV population, represented 28.9% of the relative contribution to the overall cesarean delivery frequency for the APEX cohort. By comparison, multiparous term singletons in vertex presentation (groups 3 [spontaneous labor] and 4 [induced or absent labor]) only represented 7.9% of the relative contribution to the overall cesarean delivery frequency for the APEX cohort. This is a result of the relatively low cesarean delivery frequency (6.6%) among the 13,778 multiparous patients in group 4 with induced labor.
Table 3:
Robson 10-Group Classification System cohort values for groups 1 – 4
| Group | Number of patients in each group | Relative size of group, % | Number of cesarean deliveries in group | Group cesarean delivery frequency, % | Absolute contribution to cohort cesarean delivery frequency, %a | Relative contribution to cohort cesarean delivery frequency, %b |
|---|---|---|---|---|---|---|
| Group 1: Nulliparous term (≥37 weeks), singleton, vertex, spontaneous labor | 23,613 | 20.4 | 4,197 | 17.8 | 3.6 | 11.6 |
| Group 2: Nulliparous term (≥37 weeks), singleton, vertex, induced or absent labor | 15,571 | 13.5 | 6,263 | 40.2 | 5.4 | 17.3 |
| Group 3: Multiparous term (≥37 weeks), singleton, vertex, spontaneous labor | 28,442 | 24.6 | 1,131 | 4.0 | 1.0 | 3.1 |
| Group 4: Multiparous term (≥37 weeks), singleton, vertex, induced or absent labor | 14,622 | 12.7 | 1,752 | 12.0 | 1.5 | 4.8 |
Absolute contribution (%) = (number of cesarean deliveries in the group / total number of patients delivered) * 100
Relative contribution (%) = (number of cesarean deliveries in the group / total number of cesarean deliveries) *100
Patients with a term singleton gestation in vertex presentation and a history of a prior cesarean delivery (group 5) represented the greatest relative contribution to the cohort cesarean delivery frequency (34.8%). The mean cohort cesarean delivery frequency for group 5 was 82.4%. Of the 15,295 patients in group 5, there were 3,955 (25.9%) with a history of greater than one prior cesarean delivery. The group cesarean delivery frequency for patients with one prior cesarean delivery was 77.0% compared to 97.9% among women with greater than one prior cesarean delivery (Table 4).
Table 4:
Robson 10-Group Classification System cohort values for group 5 and stratified by prior cesarean deliveries
| Group | Number of patients in each group | Relative size of group, % | Number of cesarean deliveries in group | Group cesarean delivery frequency, % | Absolute contribution to cohort cesarean delivery frequency, %a | Relative contribution to cohort cesarean delivery frequency, %b |
|---|---|---|---|---|---|---|
| Group 5: Term (≥37 weeks), singleton, vertex, any prior cesarean delivery | 15,295 | 13.2 | 12,606 | 82.4 | 10.9 | 34.9 |
| 1 prior cesarean delivery | 11,340 | 74.1 | 8,733 | 77.0 | 7.6 | 24.2 |
| >1 prior cesarean delivery | 3,955 | 25.9 | 3,873 | 97.9 | 3.4 | 10.7 |
Absolute contribution (%) = (number of cesarean deliveries in the group / total number of patients delivered) * 100
Relative contribution (%) = (number of cesarean deliveries in the group / total number of cesarean deliveries) *100
Although patients with preterm singletons in vertex presentation (group 10) constituted a smaller percentage of the cohort population (n=10,110, 8.8%), the cesarean delivery frequency for this group was 35.1%. This combination resulted in a 9.8% relative contribution to the overall cesarean delivery frequency. The addition of group 10 to term singleton gestations in vertex presentation with a history of a prior cesarean delivery (group 5) and nulliparous term singletons in vertex presentation (groups 1 and 2) represented 55.9% of the APEX cohort and accounted for 73.5% of the relative contribution to the cohort cesarean delivery frequency.
The remaining TGCS groups varied with respect to their size or cesarean delivery frequencies. The patients in these groups generally represented either small subsets of the cohort with high associated cesarean delivery frequencies or large subsets of the cohort with low associated cesarean delivery frequencies. As a result, these groups represented lower relative contributions to cohort cesarean deliveries (Figure 1).
Figure 1:
Relative contribution of Robson 10-Group Classification System groups to cohort cesarean deliveries
The range of TGCS values for all APEX hospitals is provided in Supplemental Table 2. Individual hospital level data is not reported due to concerns for potential unmasking of study hospitals. At the hospital level, there was a greater than two-fold difference in overall cesarean delivery frequencies (median 29.8, range 19.1–39.3%). Term singletons in vertex presentation with a prior cesarean delivery (group 5) continued to represent the greatest relative contribution to cesarean delivery frequencies (range 23.8–45.5%) with the majority of group 5 patients undergoing repeat cesarean delivery regardless of delivery institution (range 58.8–92.6%). The remaining groups’ relative sizes, cesarean frequencies, and resultant contribution to each hospital’s overall cesarean frequency varied by center; however, the combination of nulliparous term singletons in vertex presentation (group 1 [spontaneous labor] and group 2 [induced or absent labor]), term singletons in vertex presentation with a prior cesarean delivery (group 5) and preterm singletons in vertex presentation (group 10) continued to account for the majority of the relative contribution to hospital cesarean delivery frequencies (median 73.8%, range 66.0–78.5%). The median hospital cesarean delivery frequencies for these groups were similar to those reported for the cohort in Supplemental Table 1. Hospital cesarean delivery frequencies were highly correlated with the combined cesarean delivery frequencies of TGCS groups 1, 2, 5, and 10 (Spearman’s rho = 0.96, p <0. 001).
In the hierarchical logistic regression models, accounting for patient characteristics in groups 1, 2, 3, 4, 5, and 10 (nulliparous term singletons in vertex presentation with spontaneous labor; nulliparous term singletons in vertex presentation with induced or absent labor; multiparous term singletons in vertex presentation with spontaneous labor; multiparous term singletons in vertex presentation with induced or absent labor; term singletons in vertex presentation with a prior cesarean delivery; and preterm singletons in vertex presentation) explained 0%, 34.1%, 22.9%, 0%, 10.4%, and 25.1% of the variation in hospitals’ cesarean delivery frequencies, respectively. We were unable to evaluate the contribution of patient characteristics to groups 6, 7, 8, and 9 (nulliparous breech singletons; multiparous breech singletons; multiple gestations; and abnormal fetal lies) due to small sample sizes. The σ and standard error for the crude and patient-adjusted hierarchical models are provided in Table 5.
Table 5:
Hospital variation (σ) in cesarean delivery frequency in each Robson 10-Group Classification System group explained by select patient characteristics
| Group | N | Percent delivered by cesarean | Hospital variation (σ) in crude hierarchical regressiona | Hospital variation (σ) in hierarchical regression with patient characteristicsa, b | Percent of hospital variation explained by patient characteristics b |
|---|---|---|---|---|---|
| 1 | 23,613 | 17.8 | 0.0534 (0.01847) | 0.0569 (0.01988) | 0 |
| 2 | 15,571 | 40.2 | 0.1028 (0.03259) | 0.0835 (0.02732) | 34.1 |
| 3 | 28,442 | 4.0 | 0.1461 (0.05232) | 0.1283 (0.04792) | 22.9 |
| 4 | 14,622 | 12.0 | 0.2869 (0.09136) | 0.2964 (0.09484) | 0 |
| 5 | 15,295 | 82.4 | 0.3209 (0.09696) | 0.3039 (0.09243) | 10.4 |
| 6 | 2,288 | 98.3 | 0.3944 (0.2739) | - | - |
| 7 | 2,557 | 96.4 | 0.0841 (0.1046) | - | - |
| 8 | 2,117 | 63.9 | 0.2828 (0.1042) | - | - |
| 9 | 596 | 87.9 | 1.2292 (0.5510) | - | - |
| 10 | 10,110 | 35.1 | 0.05989 (0.02185) | 0.0519 (0.01972) | 25.1 |
Data presented as σ (standard error).
Empty cells reflect an inability to compute due to small sample sizes.
DISCUSSION
We applied the TGCS to a large, multicenter U.S. cohort. Term singleton gestations in vertex presentation with a history of a prior cesarean delivery (group 5) represented the greatest relative contribution to cesarean delivery frequencies. Nulliparous term singleton gestations in vertex presentation (group 1 [labor] and group 2 [induced or absent labor]), term singleton gestations in vertex presentation with a history of a prior cesarean delivery (group 5), and preterm singleton gestations in vertex presentation (group 10) were the primary determinants of cohort cesarean delivery frequencies. Patient characteristics accounted for approximately one-third of the hospital-level variation in cesarean deliveries among nulliparous term singleton gestations in vertex presentation with induced or absent labor (group 2).
The WHO endorses the TGCS as the global standard for classification and comparison of hospital cesarean delivery frequencies.4 While a recent publication by Hehir et al. demonstrated the potential utility of applying the TGCS to a large U.S. population, use of the NTSV metric continues to be emphasized by The Joint Commission and others.3,15 Proponents of the NTSV metric highlight the potential to prevent primary cesarean deliveries in a low-risk population. Furthermore, Main et al recently demonstrated that adoption of a quality improvement program in California could safely reduce NTSV cesarean delivery frequencies without increasing maternal or neonatal morbidity.16
One advantage offered by the TGCS is its stratification of NTSV deliveries by type of labor. Recent data from the California Maternal Quality Care Collaborative (CMQCC) revealed five-fold variation in the frequency of cesarean delivery among induced NTSV gestations across 238 California hospitals (cesarean delivery frequency range 18.5–84.6%).17 Main et al. did not find that risk-adjustment reduced the variation across hospitals; however, we noted that the greatest contribution of patient characteristics to hospital variation in cesarean deliveries was among NTSV gestations with induced or absent labor. The majority of variation in cesarean delivery frequencies remains attributable to unexplained factors such as provider characteristics, hospitals characteristics, or random variation. Despite this, the hospital variation in cesarean delivery frequencies for NTSV gestations with induced or absent labor in our study and NTSV gestations with induced labor in the CMQCC population underscores the potential value of stratifying NTSV gestations by type of labor.
The utility of the TGCS extends beyond NTSV gestations. This is best exemplified by our findings for the term singletons in vertex presentation with a history of prior cesarean delivery (group 5) and preterm singletons in vertex presentation (group 10). Group 5 was the greatest relative contributor to cesarean delivery frequencies. The cesarean delivery frequency for group 5 was 82.4% despite approximately three-fourths of the patients in group 5 having only one prior cesarean delivery and the studied hospitals arguably representing perinatal centers that are more likely to permit a trial of labor after cesarean delivery. Group 10 represented 8.8% of cohort deliveries. The contribution of cesarean deliveries in this group to overall frequencies is reflective of the high rates of spontaneous and indicated preterm birth in our country and emphasizes the importance of optimizing labor management for patients delivering prematurely.
Application of the TGCS to the APEX cohort provides additional insights when the data are compared to the 2014 U.S. population studied by Hehir et al and to data derived from the WHO Multicountry Survey (MCS) on Maternal and Newborn Health.8,18 The APEX cohort cesarean delivery frequency mirrored the frequencies for the U.S. and MCS populations (31.3% and 30.0%, respectively). The ratio of nulliparous term singletons in vertex presentation with spontaneous labor (group 1) to those with induced or absent labor (group 2) was 1.5 in the APEX cohort as compared with 1.6 for the U.S. population and 3.3 for the MCS population. Although a low ratio can occur due to misclassification, the APEX ratio likely reflects a higher case-mix with associated prelabor induction or aspects of the care delivery systems (e.g., twenty-four hour in-house coverage). Finally, preterm singletons in vertex presentation (group 10) comprised 8.8% of the APEX study population with a cesarean delivery frequency of 35.1%. This exceeds the group sizes for the U.S. and MCS populations (6.6% and 4.2%, respectively) and highlights the ability of the TGCS to identify unique contributions of specific obstetric populations to hospital deliveries.
Our study has multiple strengths. We utilized data from a large and diverse observational cohort obtained via standardized medical record abstraction. Patients with abnormal lies (group 9) represented 0.5% of the cohort, which is below the 1% threshold recommended by the WHO. We also recognize several imitations. Our findings may not be relevant to all hospital settings, and the APEX study occurred from 2008–2011, which may not reflect contemporary labor management. All births occurring across all hospitals were not evaluated due to the design of the APEX study; however, the data utilized was collected from randomly selected days during the study period with methods to avoid overrepresentation of larger hospitals. Additionally, we did not analyze the contribution of hospital or provider characteristics to cesarean delivery variation. Finally, complete details of hospital cesarean delivery frequencies could not be provided due to potential unmasking of APEX study hospitals.
Application of the TGCS to a diverse, multicenter cohort provided a comprehensive assessment of cesarean deliveries and insight into the varying contribution of patient characteristics to cesarean delivery frequencies. Adoption of the TGCS offers the potential to monitor cesarean delivery frequencies by parity and labor type and to better understand which populations warrant further investigation of practices that influence cesarean deliveries within a hospital or health system.
Supplementary Material
KEY POINTS.
We report on the cesarean delivery frequencies in a multicenter U.S cohort.
NTSV gestations (groups 1 and 2) are a primary driver of cesarean deliveries.
Patient characteristics contributed most to hospital variation in cesarean deliveries in group 2.
Acknowledgements:
The authors thank Dr. Alan T. N. Tita, M.D., Ph.D. for guidance in study design and manuscript preparation and Elizabeth Thom, Ph.D., Madeline M. Rice, Ph.D., Brian M. Mercer, M.D. and Catherine Y. Spong, M.D. for protocol development and oversight.
Financial Disclosure:
The authors do not report any potential conflicts of interest. Each author has indicated that they meet the journal’s requirement for authorship.
The project described was supported by grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) [HD21410, HD27869, HD27915, HD27917, HD34116, HD34208, HD36801, HD40500, HD40512, HD40544, HD40545, HD40560, HD40485, HD53097, HD53118] and the National Center for Research Resources [UL1 RR024989; 5UL1 RR025764]. Comments and views of the authors do not necessarily represent views of the NIH.
Appendix
In addition to the authors, other members of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Maternal-Fetal Medicine Units Network are as follows:
University of Alabama at Birmingham, Birmingham, AL – A. Tita, M. Wallace, A. Northen, J. Grant, C. Colquitt, D. Rouse, W. Andrews
Columbia University, New York, NY – M. Talucci, M. Zylfijaj, Z. Reid (Drexel U.), R. Leed (Drexel U.), J. Benson (Christiana H.), S. Forester (Christiana H.), C. Kitto (Christiana H.), S. Davis (St. Peter’s UH.), M. Falk (St. Peter’s UH.), C. Perez (St. Peter’s UH.)
University of Utah Health Sciences Center, Salt Lake City, UT – K. Hill, A. Sowles, J. Postma (LDS Hospital), S. Alexander (LDS Hospital), G. Andersen (LDS Hospital), V. Scott (McKay-Dee), V. Morby (McKay-Dee), K. Jolley (UVRMC), J. Miller (UVRMC), B. Berg (UVRMC)
University of North Carolina at Chapel Hill, Chapel Hill, NC – K. Dorman, J. Mitchell, E. Kaluta, K. Clark (WakeMed), K. Spicer (WakeMed), S. Timlin (Rex), K. Wilson (Rex)
University of Texas Southwestern Medical Center, Dallas, TX – L. Moseley, K. Leveno (deceased), M. Santillan, J. Price, K. Buentipo, V. Bludau, T. Thomas, L. Fay, C. Melton, J. Kingsbery, R. Benezue
University of Pittsburgh, Pittsburgh, PA – H. Simhan, M. Bickus, D. Fischer, T. Kamon (deceased), D. DeAngelis
MetroHealth Medical Center-Case Western Reserve University, Cleveland, OH – B. Mercer, C. Milluzzi, W. Dalton, T. Dotson, P. McDonald, C. Brezine, A. McGrail
The Ohio State University, Columbus, OH – C. Latimer, L. Guzzo (St. Ann’s), F. Johnson, L. Gerwig (St. Ann’s), S. Fyffe, D. Loux (St. Ann’s), S. Frantz, D. Cline, S. Wylie, J. Iams
Northwestern University, Chicago, IL – G. Mallett, M. Ramos-Brinson, A. Roy, L. Stein, P. Campbell, C. Collins, N. Jackson, M. Dinsmoor (NorthShore University HealthSystem), J. Senka (NorthShore University HealthSystem), K. Paychek (NorthShore University HealthSystem), A. Peaceman
University of Texas Medical Branch, Galveston, TX – J. Moss, A. Salazar, A. Acosta, G. Hankins
Wayne State University, Detroit, MI – N. Hauff, L. Palmer, P. Lockhart, D. Driscoll, L. Wynn, C. Sudz, D. Dengate, C. Girard, S. Field
Brown University, Providence, RI – P. Breault, F. Smith, N. Annunziata, D. Allard, J. Silva, M. Gamage, J. Hunt, J. Tillinghast, N. Corcoran, M. Jimenez
The University of Texas Health Science Center at Houston, McGovern Medical School-Children’s Memorial Hermann Hospital, Houston, TX– F. Ortiz, S. Blackwell, P. Givens, B. Rech, C. Moran, M. Hutchinson, Z. Spears, C. Carreno, B. Heaps, G. Zamora
Oregon Health & Science University, Portland, OR – J. Seguin, M. Rincon, J. Snyder, C. Farrar, E. Lairson, C. Bonino, W. Smith (Kaiser Permanente), K. Beach (Kaiser Permanente), S. Van Dyke (Kaiser Permanente), S. Butcher (Kaiser Permanente)
The George Washington University Biostatistics Center, Washington, D.C. – E. Thom, M. Rice, Y. Zhao, P. McGee, V. Momirova, R. Palugod, B. Reamer, M. Larsen
Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD – C. Spong, S. Tolivaisa
MFMU Network Steering Committee Chair (Medical University of South Carolina, Charleston, SC) – J. P. VanDorsten, M.D.
Footnotes
See Appendix for a list of other members of the NICHD MFMU Network
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