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Figure.  Adjusted Absolute Risk Differences in Outcomes Among Predicted Risk Groups for Cesarean Delivery
Adjusted Absolute Risk Differences in Outcomes Among Predicted Risk Groups for Cesarean Delivery

Maternal morbidity and cesarean delivery are compared between the preimplementation and postimplementation periods.

Table 1.  Demographic and Clinical Characteristics of the Preimplementation and Postimplementation Periods
Demographic and Clinical Characteristics of the Preimplementation and Postimplementation Periods
Table 2.  Primary Composite Maternal Morbidity Outcome Compared Between Preimplementation and Postimplementation Periods
Primary Composite Maternal Morbidity Outcome Compared Between Preimplementation and Postimplementation Periods
Table 3.  Maternal and Neonatal Secondary Outcomes Compared Between Preimplementation and Postimplementation Periods
Maternal and Neonatal Secondary Outcomes Compared Between Preimplementation and Postimplementation Periods
Table 4.  Birth Satisfaction Scores as Determined by the BSS-R Compared Between Preimplementation and Postimplementation Periods
Birth Satisfaction Scores as Determined by the BSS-R Compared Between Preimplementation and Postimplementation Periods
1.
Osterman  MJ, Martin  JA.  Recent declines in induction of labor by gestational age.   NCHS Data Brief. 2014;(155):1-8.PubMedGoogle Scholar
2.
Grobman  WA.  Predictors of induction success.   Semin Perinatol. 2012;36(5):344-347. doi:10.1053/j.semperi.2012.04.017 PubMedGoogle ScholarCrossref
3.
Tolcher  MC.  Predicting cesarean delivery following induction.   J Womens Health (Larchmt). 2020;29(5):607. doi:10.1089/jwh.2019.8187PubMedGoogle ScholarCrossref
4.
Vahratian  A, Zhang  J, Troendle  JF, Sciscione  AC, Hoffman  MK.  Labor progression and risk of cesarean delivery in electively induced nulliparas.   Obstet Gynecol. 2005;105(4):698-704. doi:10.1097/01.AOG.0000157436.68847.3b PubMedGoogle ScholarCrossref
5.
Levine  LD, Downes  KL, Parry  S, Elovitz  MA, Sammel  MD, Srinivas  SK.  A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix.   Am J Obstet Gynecol. 2018;218(2):254.e1-254.e7. doi:10.1016/j.ajog.2017.11.603PubMedGoogle ScholarCrossref
6.
Hamm  RF, Downes  KL, Srinivas  SK, Levine  LD.  Using the probability of cesarean from a validated cesarean prediction calculator to predict labor length and morbidity.   Am J Perinatol. 2019;36(6):561-566. doi:10.1055/s-0038-1675625 PubMedGoogle ScholarCrossref
7.
Bell  AF, Andersson  E.  The birth experience and women’s postnatal depression: a systematic review.   Midwifery. 2016;39:112-123. doi:10.1016/j.midw.2016.04.014 PubMedGoogle ScholarCrossref
8.
Sadler  LC, Davison  T, McCowan  LM.  Maternal satisfaction with active management of labor: a randomized controlled trial.   Birth. 2001;28(4):225-235. doi:10.1046/j.1523-536X.2001.00225.x PubMedGoogle ScholarCrossref
9.
von Elm  E, Altman  DG, Egger  M, Pocock  SJ, Gøtzsche  PC, Vandenbroucke  JP; STROBE Initiative.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.   J Clin Epidemiol. 2008;61(4):344-349. doi:10.1016/j.jclinepi.2007.11.008 PubMedGoogle ScholarCrossref
10.
Hollins Martin  CJ, Martin  CR.  Development and psychometric properties of the Birth Satisfaction Scale−Revised (BSS-R).   Midwifery. 2014;30(6):610-619. doi:10.1016/j.midw.2013.10.006 PubMedGoogle ScholarCrossref
11.
Martin  CR, Hollins Martin  CJ, Burduli  E, Barbosa-Leiker  C, Donovan-Batson  C, Fleming  SE.  Measurement and structural invariance of the US version of the Birth Satisfaction Scale−Revised (BSS-R) in a large sample.   Women Birth. 2017;30(4):e172-e178. doi:10.1016/j.wombi.2016.11.006 PubMedGoogle ScholarCrossref
12.
Macones  GA, Hausman  N, Edelstein  R, Stamilio  DM, Marder  SJ.  Predicting outcomes of trials of labor in women attempting vaginal birth after cesarean delivery: a comparison of multivariate methods with neural networks.   Am J Obstet Gynecol. 2001;184(3):409-413. doi:10.1067/mob.2001.109386 PubMedGoogle ScholarCrossref
13.
Hashima  JN, Eden  KB, Osterweil  P, Nygren  P, Guise  JM.  Predicting vaginal birth after cesarean delivery: a review of prognostic factors and screening tools.   Am J Obstet Gynecol. 2004;190(2):547-555. doi:10.1016/j.ajog.2003.08.045 PubMedGoogle ScholarCrossref
14.
Costantine  MM, Fox  K, Byers  BD,  et al.  Validation of the prediction model for success of vaginal birth after cesarean delivery.   Obstet Gynecol. 2009;114(5):1029-1033. doi:10.1097/AOG.0b013e3181bb0dde PubMedGoogle ScholarCrossref
15.
Kawakita  T, Mokhtari  N, Huang  JC, Landy  HJ.  Evaluation of risk-assessment tools for severe postpartum hemorrhage in women undergoing cesarean delivery.   Obstet Gynecol. 2019;134(6):1308-1316. doi:10.1097/AOG.0000000000003574 PubMedGoogle ScholarCrossref
16.
Danilack  VA,  et al.  Development and validation of a risk prediction model for cesarean delivery after labor induction.   J Womens Health (Larchmt). 2020;29(5):656-669. doi:10.1089/jwh.2019.7822 PubMedGoogle ScholarCrossref
17.
Rossi  RM, Requarth  E, Warshak  CR, Dufendach  KR, Hall  ES, DeFranco  EA.  Risk calculator to predict cesarean delivery among women undergoing induction of labor.   Obstet Gynecol. 2020;135(3):559-568. doi:10.1097/AOG.0000000000003696 PubMedGoogle ScholarCrossref
18.
Beavers  JB, Bai  S, Perry  J, Simpson  J, Peeples  S.  Implementation and evaluation of the early-onset sepsis risk calculator in a high-risk university nursery.   Clin Pediatr (Phila). 2018;57(9):1080-1085. doi:10.1177/0009922817751337 PubMedGoogle ScholarCrossref
19.
Gievers  LL, Sedler  J, Phillipi  CA,  et al.  Implementation of the sepsis risk score for chorioamnionitis-exposed newborns.   J Perinatol. 2018;38(11):1581-1587. doi:10.1038/s41372-018-0207-7 PubMedGoogle ScholarCrossref
20.
Dhudasia  MB, Mukhopadhyay  S, Puopolo  KM.  Implementation of the sepsis risk calculator at an academic birth hospital.   Hosp Pediatr. 2018;8(5):243-250. doi:10.1542/hpeds.2017-0180 PubMedGoogle ScholarCrossref
1 Comment for this article
EXPAND ALL
Lack of Efficiency of Calculator to Prevent Cesarean Delivery and Maternal Morbidity
Souhail Alouini, M.D., Ph.D. | Department of Obstetrics and Gynecological Surgery. Centre Hospitalier Regional d'Orleans; France
Hamm et al. (1) proposed a calculator to manage better labor induction and deliveries.
In this calculator there is one parameter which was used two times: the height, and the height in the BMI (Weight/Height²). The authors propose a prognosis of the mode of delivery according to maternal parameters during pregnancy.
However, these parameters are very insufficient to predict the mode of delivery and potential postpartum complications.
Indeed, fetal parameters are absent in this calculator, e.g. macrosomia, fetal heart rate abnormalities during labor which are in most cases totally unexpected before it.
Premature rupture of membranes was not included
in the calculator, whereas it exposes to maternal - fetal infections.
Abnormalities of umbilical cord, umbilical cord prolapse were also omitted from the calculator, whereas they could change the mode of delivery (2). Indeed, in many situations, umbilical cord prolapse is completely unexpected, including in cephalic presentations (2).
Maternal pathologies such as premature labor, cardiovascular diseases like preeclampsia, gestational diabetes were not included in the calculator, even though they have major implications on the mode of delivery and postpartum complications.
All these situations are very frequent and are not always correlated with the BMI, the cervical examination, age or parity.
Placental implantation was also not included in the calculator, whereas low placental implantations increase the risk of postpartum hemorrhage (PPH) (3). Previous cesarean deliveries (CD) also increase the risk of PPH but this criterion was not in the calculator.
Why the amount of 1000 ml was chosen for PPH, whereas it is defined as > 500 ml in guidelines?
In this study, the method of labor induction was not precised. Was it induced by oxytocin and/or by prostaglandins? According to the choice of the method of labor induction, implications for the mode of delivery and its outcomes are not similar.
In this study fetal acidosis and hypoxia were not evaluated at birth. Indeed, Umbilical artery pH and lactates in the cord blood at birth were not reported, even though they are important to evaluate neonatal state and thus the quality of the management of the delivery.
Most women were black and affiliated to Medicaid. This misrepresentation introduced bias concerning maternal pathologies and deliveries’ complications.
Why more elective inductions occurred at 39 weeks, whereas many pathologies were excluded from the study, e.g. intrauterine growth restriction?
In addition, to predict a high risk of CD could have negative impact on the psychological motivation of mothers to deliver vaginally.
This calculator did not change the rates of CD and maternal morbidity.
Finally, this calculator had little impact on the rate of cesarean delivery and maternal morbidity as fetal and placental information and maternal pathologies were missing. However, this calculator could help young obstetricians to make a more quickly a decision.

References
1. Hamm RF, McCoy J, Oladuja A, et al. Maternal Morbidity and Birth Satisfaction After Implementation of a Validated Calculator to Predict Cesarean Delivery During Labor Induction. JAMA Netw Open. 2020;3:e2025582.
2. Alouini S, Mesnard L, Megier P, et al. A. Management of umbilical cord prolapse and neonatal outcomes. J Gynecol Obstet Biol Reprod. 2010;39:471-7.
3. Alouini S, Megier P, Fauconnier A, et al.. Diagnosis and management of placenta previa and low placental implantation. J Matern Fetal Neonatal Med. 2020 ;33:3221-3226.
CONFLICT OF INTEREST: None Reported
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Original Investigation
Obstetrics and Gynecology
November 13, 2020

Maternal Morbidity and Birth Satisfaction After Implementation of a Validated Calculator to Predict Cesarean Delivery During Labor Induction

Author Affiliations
  • 1Maternal and Child Health Research Center, Department of Obstetrics and Gynecology, University of Pennsylvania Perelman School of Medicine, Philadelphia
  • 2Department of Family Medicine and Community Health, University of Pennsylvania Perelman School of Medicine, Philadelphia
  • 3Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia
JAMA Netw Open. 2020;3(11):e2025582. doi:10.1001/jamanetworkopen.2020.25582
Key Points

Question  Is implementation of a validated calculator to predict cesarean delivery after labor induction associated with maternal morbidity and birth satisfaction?

Findings  In this cohort study of 1610 women admitted for labor induction, use of a cesarean delivery risk calculator was associated with a 6% absolute risk reduction in maternal morbidity, as well as an 8% absolute risk reduction in cesarean delivery. Calculator implementation was associated with improvements in women’s perception of quality of care received.

Meaning  These findings suggest that implementation of a validated calculator to predict risk of cesarean delivery in clinical care is associated with reduced obstetric morbidity and improved the patient birth experience.

Abstract

Importance  A previously created and validated calculator provides an individualized cesarean delivery risk score for women undergoing labor induction. A higher predicted risk of cesarean delivery on the calculator has been associated with increased maternal and neonatal morbidity regardless of ultimate delivery mode. The effect of this calculator when implemented in clinical care has yet to be evaluated.

Objective  To determine whether implementation of a validated calculator that predicts the likelihood of cesarean delivery at the time of labor induction is associated with maternal morbidity and birth satisfaction.

Design, Setting, and Participants  This prospective cohort study used medical record review to compare the 1 year before calculator implementation (July 1, 2017, to June 30, 2018) with the 1 year after implementation (July 1, 2018, to June 30, 2019) at a US urban, university labor unit. Women admitted for labor induction with singleton gestation in cephalic presentation, intact membranes, and an unfavorable cervix were included. Data were analyzed from August 1, 2019, to September 13, 2020.

Exposures  Patient and clinician knowledge of the calculated cesarean delivery risk score based on the validated calculator.

Main Outcomes and Measures  The primary outcomes were (1) composite maternal morbidity defined by at least 1 of the following within 30 days of delivery: endometritis, postpartum hemorrhage (estimated or quantitative blood loss >1000 mL), blood transfusion, wound infection, venous thromboembolism, hysterectomy, intensive care unit admission, and readmission and (2) patient satisfaction assessed via Birth Satisfaction Scale–Revised (BSS-R) scores. Secondary outcomes included rate of cesarean delivery and neonatal morbidity.

Results  A total of 1610 women were included in the analysis (788 in the preimplementation and 822 in the postimplementation periods) with a median age of 29 (interquartile range [IQR], 24-34) years. There were no significant baseline differences between groups except fewer inductions at a gestational age of 40 weeks or later in the postimplementation period (256 [31.1%] vs 298 [37.8%]). Calculator implementation was associated with decreased maternal morbidity overall, even when adjusting for confounders (141 [17.9%] vs 95 [11.6%]; adjusted absolute risk difference [aARD], −6.3%; 95% CI, −9.7% to −2.8%). Although there was no difference in birth satisfaction overall, calculator implementation was associated with improvements on items pertaining to quality of care provision (median BSS-R score, 19 [IQR, 16-20] vs 19 [IQR, 17-20]; P = .006). Calculator implementation was also associated with a decrease in cesarean delivery rate (228 [28.9%] vs 167 [20.3%]; aARD, −8.5% [95% CI, −12.6% to −4.5%]). There were no significant differences in neonatal morbidity.

Conclusions and Relevance  These findings suggest that implementation of a validated calculator to predict risk of cesarean delivery in clinical care is associated with reduced maternal morbidity. Implementation should occur broadly to determine whether calculator use improves national maternal outcomes.

Introduction

Labor induction is the process of stimulating uterine contractions during pregnancy before labor begins on its own, with the goal of a vaginal birth. In the US, more than 4 million women give birth annually, with more than 20% undergoing an induction.1 Despite the fact that approximately one-third of inductions will end in a cesarean delivery, our ability to predict who will have a successful induction resulting in a vaginal birth is limited.2-4 In answer, Levine et al5 created a risk prediction model for cesarean delivery among women undergoing an induction that was both internally and externally validated in a database of more than 200 000 deliveries across 19 diverse hospitals with an area under the curve of 0.73. The risk prediction model was developed into a user-friendly online calculator (hereinafter referred to as the cesarean risk calculator) requiring only 5 pieces of data: height (in centimeters), body mass index (calculated as weight in kilograms divided by height in meters squared), parity, gestational age at the time of induction, and cervical examination findings. These items are input directly into the calculator at induction start, producing an individualized percentage risk of cesarean delivery for a patient’s induction.

When stratified into categories of cesarean delivery risk (<20.0%, 20.0%-39.9%, 40.0%-59.9%, and ≥60.0%), a higher predicted probability of cesarean delivery on this calculator is also associated with longer labor, as well as increased maternal morbidity (<20.0% risk, 2.6% probability; 20.0%-39.9% risk, 4.7% probability; 40.0%-59.9% risk, 5.1% probability; and ≥60.0% risk, 6.1% probability; P = .001) and neonatal morbidity (<20.0% risk, 0.9% probability; 20.0%-39.9% risk, 1.5% probability; 40.0%-59.9% risk, 2.0% probability; and ≥60.0% risk, 2.2% probability; P = .002).6 Thus, the higher the calculated risk of cesarean delivery, regardless of the actual mode of delivery, the higher the risk of an adverse outcome.

In addition, before development of this calculator, women and their clinicians began an induction without the knowledge of how likely the patient was to have a cesarean delivery. Improved prediction of cesarean delivery has the potential to improve patient satisfaction by clarifying patient expectations. Patient satisfaction during labor is directly linked to mother-infant bonding, breastfeeding rates, and decreased risk for postpartum depression.7,8

Whether implementation of this calculator into clinical care will affect perinatal outcomes is unknown. This study aimed to evaluate (1) maternal morbidity and (2) patient satisfaction before and after implementation of the cesarean risk calculator. We hypothesized that if a clinician is aware of a patient’s individualized risk of cesarean delivery, this knowledge will influence labor induction management, leading to a decrease in maternal morbidity without increasing the rate of cesarean delivery. In addition, we hypothesized that providing patients with the knowledge of their risk of cesarean delivery at the start of induction will improve satisfaction with the birth experience.

Methods

We performed a prospective cohort study of women undergoing labor induction at the Hospital of the University of Pennsylvania, Philadelphia, before and after implementation of the cesarean risk calculator into usual clinical care. The preimplementation period was from July 1, 2017, to June 30, 2018. The calculator was implemented as standard of care on July 1, 2018, and the postimplementation period was from July 1, 2018, to June 30, 2019. The project was approved by the University of Pennsylvania institutional review board as quality improvement with a waiver of informed consent due to its nature as quality improvement. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines were followed in the writing of this report.9

Study Population

Women were included in this study if they were undergoing a term (≥37 weeks) labor induction for any indication and met the following inclusion criteria: 18 years or older, singleton gestation in cephalic presentation, intact membranes, and an unfavorable cervix (Bishop score of ≤6 [range, 0-13, with higher scores indicating favorable cervical examination results] and cervical dilation ≤2 cm). Women were excluded from the study if they had a prior cesarean delivery; had a contraindication to vaginal delivery; had a major fetal anomaly; did not speak English; had HIV, hemolysis, elevated liver enzyme levels, and low platelet count (HELLP syndrome); had eclampsia; or had intrauterine growth restriction with abnormal umbilical artery Doppler findings.5 These were the same criteria used to derive and validate the calculator.

Implementation of the Calculator

On July 1, 2018, the calculator was implemented as standard of care for women undergoing induction on our labor unit who met inclusion criteria. After the start of the postimplementation period, the admitting clinician obtained the calculator result and placed a sticker with the predicted likelihood of cesarean delivery next to the patient’s information on the central labor and delivery board, visible to all clinicians and nurses. The clinician then counseled the patient on their range of cesarean delivery risk (<20.0%, 20.0%-39.9%, 40.0%-59.9%, or ≥60%) with the assistance of premade, standardized scripts. Documentation of this counseling was placed in the electronic medical record. Clinical care occurred at the discretion of the covering labor floor clinicians with no dictated changes in labor management based on the calculator score. Implementation strategies to incorporate the induction calculator into care included (1) multidisciplinary stakeholder buy-in, (2) education and training sessions, and (3) daily, clinician-specific audit and feedback on appropriate calculator use.

Outcomes

The first primary outcome was a composite maternal morbidity defined by 1 or more of the following within 30 days of delivery: endometritis, postpartum hemorrhage (estimated or quantitative blood loss >1000 mL), blood transfusion, wound infection, venous thromboembolism, hysterectomy, intensive care unit admission, and readmission. Our second primary outcome was patient satisfaction using the validated Birth Satisfaction Scale–Revised (BSS-R), administered to patients during their inpatient postpartum stay. The BSS-R has been demonstrated to be a robust, valid, and reliable multidimensional psychometric instrument for measuring postpartum women’s birth satisfaction in diverse populations (Cronbach α = 0.79).10,11 The BSS-R asks women to report agreement or disagreement with 10 statements using a 5-point Likert scale. The total BSS-R ranges from 10 to 50, with higher scores indicating increased satisfaction. The BSS-R is subdivided into 3 domains: (1) quality of care provision, (2) stress experienced during labor, and (3) women’s personal attributes.

Our secondary maternal outcomes included rate of cesarean delivery, time from induction to delivery, indication for cesarean delivery, chorioamnionitis, and maternal length of stay. Secondary neonatal outcomes included composite neonatal morbidity (defined by ≥1 of the following: supplemental oxygen for ≥12 hours, and culture-proven or presumed neonatal sepsis), neonatal intensive care unit admissions, and neonatal length of stay.

Data Collection

Baseline demographic data, medical and obstetrical history, and labor and delivery data were collected on all patients meeting inclusion criteria. Self-reported race/ethnicity was collected, because significant racial/ethnic disparities exist in rates of our primary and secondary outcomes. The BSS-R surveys were administered for the latter 6 months of the preimplementation period and the full 12 months of the postimplementation period. In addition, frequency of documentation regarding counseling around the calculator result in the postimplementation period was collected.

Sample Size

In prior work at our institution, approximately 750 women per year met our inclusion criteria,5 with a baseline maternal morbidity rate of 15%. To have greater than 80% power with α = .05 to detect a 35% reduction in maternal morbidity, this required a sample size of 1 year before and 1 year after implementation. In addition, using data from a 2016 study of 2229 US women surveyed using the 10-question BSS-R, the mean (SD) score was 31.94 (6.75).5,10 We therefore had greater than 90% power to detect a 10% increase in patient satisfaction with our proposed sample size.

Statistical Analyses

Data were analyzed from August 1, 2019, to September 13, 2020. Bivariate comparisons of demographic and preinduction clinical characteristics by preimplementation and postimplementation groups, as well as labor and delivery outcomes, were performed with Fisher exact tests and χ2 tests for categorical variables and unpaired, 2-tailed t tests or Wilcoxon rank sum tests for continuous variables, where appropriate. For the outcomes of composite maternal morbidity and cesarean delivery rate, directed acyclic graphs were used to determine potential confounders. Although only gestational age at delivery and indication for induction differed by exposure (calculator implementation), other covariates that could affect both the decision to use the calculator outside of our setting, as well as the outcomes, were included (parity and maternal age). Multivariable logistic regression modeling was used to adjust for all confounders and calculate adjusted absolute risk difference (aARD). Of note, gestational age at delivery and indication for induction were collinear and, of the two, only gestational age was included in final models. Sensitivity analysis was performed evaluating only those women with documented calculator result counseling.

In addition, the association between exposure and outcome was stratified by 4 risk groups for cesarean delivery based on calculator results (<20.0%, 20.0%-39.9%, 40.0%-59.9%, and ≥60.0%). Calculations of cesarean delivery risk were made retrospectively for the preimplementation group and not available in real time. To examine the association of the cesarean risk calculator in individual predicted risk strata, the interaction between preimplementation and postimplementation periods and the predicted group for cesarean delivery risk was added to the above models. Strata-specific aARDs were then determined using the appropriate contrast of coefficients.

To evaluate birth satisfaction, total and individual domain BSS-R scores were compared using the Wilcoxon rank sum test. Linear regression compared BSS-R scores, including possible confounders as described above. Statistical analyses were performed with Stata, version 15 (StataCorp LLC). All tests were 2 tailed, and P < .05 was considered statistically significant.

Results

A total of 1610 women during the study period from July 1, 2017, to June 30, 2019, met inclusion criteria. Our population had a median age of 29 (interquartile range [IQR], 24-34) years; 1045 were Black (64.9%); and 871 (54.1%) were insured through Medicaid. Seven hundred and eighty-eight were included in the preimplementation group; 822, in the postimplementation group. In the postimplementation group, patient counseling regarding the induction calculator result was documented in the electronic medical record in 676 of 822 women (82.2%).

Demographic and clinical characteristics are detailed in Table 1. There were no significant differences in age, race/ethnicity, insurance, body mass index, parity, or medical comorbidities between groups. Fewer inductions occurred at a gestational age of 40 weeks or more in the postimplementation group (298 [37.8%] vs 256 [31.1%]; P = .005). This finding was also reflected in the indication for induction, with more elective inductions at 39 weeks in the postimplementation period (129 [16.4%] vs 182 [22.1%]; P = .003) and fewer postdate inductions (90 [11.4%] vs 60 [7.3%]; P = .004). However, although gestational age was one of the calculator inputs, overall calculated cesarean delivery risk did not differ between groups.

For our primary outcome, calculator implementation was associated with overall decreased composite maternal morbidity from 141 of 788 (17.9%) to 95 of 822 (11.6%; P < .001) (Table 2). This risk difference held true when adjusting for gestational age at delivery, parity, and maternal age (aARD, −6.3%; 95% CI, −9.7% to −2.8%). Of the individual components of the maternal morbidity composite outcome, significant associated reductions were noted from the preimplementation to the postimplementation periods in the rates of postpartum hemorrhage (67 [8.5%] vs 43 [5.2%]; P = .009) and wound separation/infection (37 [4.7%] vs 11 [1.3%]; P < .001). In the secondary analysis, calculator implementation was also associated with decreased overall cesarean delivery rate, from 228 of 788 (28.9%) to 167 of 822 (20.3%; P < .001) (Table 3). Calculator implementation was associated with a more than 8% lower risk in cesarean delivery rate when adjusted for gestational age at delivery, parity, and maternal age (aARD, −8.5%; 95% CI, −12.6% to −4.5%). Sensitivity analysis including only those with documented counseling of cesarean delivery risk did not differ significantly from the primary analysis.

When stratified by calculated cesarean risk, calculator implementation was associated with a 6% absolute risk reduction in maternal morbidity in the group with predicted risk of cesarean delivery of less than 20.0% (35 [12.8%] vs 18 [6.8%]; aARD, −6.0% [95% CI, −11.0% to −1.0%]; P = .02) (Figure, A). Within this risk group, calculator implementation was also associated with a 6% absolute risk reduction in cesarean delivery (35 [12.8%] vs 17 [6.4%]; aARD, −6.4% [95% CI, −11.3% to −1.5%]; P = .01) (Figure, B). Notably, calculator implementation was associated with an elimination of cesarean deliveries for failed induction in this risk group (8 [2.9%] in the preimplementation group vs 0 in the postimplementation group).

No association of calculator implementation with absolute risk reduction was found in the group with predicted risk of cesarean delivery of 20.0% to 39.9% for maternal morbidity (46 [16.1%] vs 36 [11.4%]; aARD, −4.7% [95% CI, −10.2% to 0.8%]; P = .10) or cesarean delivery (70 [24.5%] vs 60 [18.9%]; aARD, −5.4% [95% CI, −12.0% to 1.2%]; P = .11). Within the group with predicted risk of cesarean delivery of 40.0% to 59.9%, calculator implementation was also associated with absolute risk reduction of 19% for cesarean delivery (90 [51.7%] vs 60 [33.0%]; aARD, −19.4% [95% CI, −29.4% to −9.3%]; P < .001) (Figure, B). A decrease in maternal morbidity was found, but it was not statistically significant (45 [25.9%] vs 33 [18.1%]; aARD, −7.8% [95% CI, −16.4% to 0.8%]; P = .07) (Figure, A).

In the group with predicted risk of cesarean delivery of 60.0% or greater, actual cesarean delivery rate after implementation did not change significantly (33 [61.1%] vs 30 [52.6%]; aARD, −9.6% [95% CI, −27.8% to 8.6%]; P = .30) (Figure, B). There was a decrease in maternal morbidity, but this finding was not statistically significant (15 [27.8%] vs 8 [14.0%]; aARD, −14.0% [95% CI, −28.9% to 1.0%]; P = .07) (Figure, A). A decrease in time to cesarean by more than 5 hours in this predicted cesarean delivery risk group also did not reach statistical significance (26.2 [IQR, 19.1-29.4] vs 21.1 [IQR, 16.3-25.1] hours; P = .05) (Table 3).

When comparing other secondary outcomes (Table 3), calculator implementation was associated with decreased median maternal length of stay (3 [IQR, 3-4] vs 3 [IQR, 3-3] days; P < .001). There were no differences in neonatal outcomes, although median neonatal length of stay was also shorter after implementation (2 [IQR, 2-3] vs 2 [IQR, 2-2] days; P < .001).

Three hundred and thirty of 414 eligible women (79.7%) completed the BSS-R in the 6 months before calculator implementation, and 678 of 822 (82.5%) completed it in the 1 year after implementation. Total and individual domain birth satisfaction scores are shown in Table 4. Although calculator implementation was associated with improved total birth satisfaction scores (39 [IQR, 34-42] vs 40 [IQR, 35-43]; P = .04) in bivariate analyses, there was no significant difference in total satisfaction scores in multivariable modeling (F2,1005 = 8.4; R2 = 0.02; P = .05). When analyzing the 3 BSS-R domains, calculator implementation was associated with improvement in quality of care provision (domain 2) (19 [IQR, 16-20] vs 19 [IQR, 17-20]; P = .006), even when controlling for possible confounders.

Discussion

When implemented into standard of care, use of a validated cesarean risk calculator after labor induction was associated with a substantial change in obstetric outcomes. Use of the cesarean risk calculator was associated with a 6% absolute risk reduction in maternal morbidity and improved perception of quality of care. In secondary outcomes, use of the cesarean risk calculator was also associated with a more than 8% absolute risk reduction in cesarean delivery rate.

Data from this prospective cohort study suggest that our improved maternal outcomes may have been secondary to alterations in labor management at the extremes of cesarean delivery risk. With implementation of the calculator into usual care, we demonstrated an associated decrease in actual cesarean delivery rate and complete elimination of cesarean delivery for failed induction in the group with predicted cesarean deliver risk of less than <20.0%. These findings support that, for women at low risk of cesarean delivery using the calculator, patients and clinicians may have been more empowered to achieve a vaginal delivery, thereby avoiding the morbidity associated with a cesarean delivery.

In the group with predicted cesarean delivery risk of 40.0% to 59.9%, although the difference in maternal morbidity was not statistically significant, calculator implementation was associated with a substantial reduction in cesarean delivery rate, which may have contributed to the observed overall associated reduction in maternal morbidity. In the group with predicted cesarean delivery risk of 60.0% or greater, there was no change in cesarean delivery rate. Instead, calculator implementation was associated with a 5-hour shorter time to delivery. These findings support that clinicians may have made the decision for cesarean delivery sooner in women at high risk for cesarean delivery, avoiding the morbidity of a prolonged and ultimately failed induction. Although the reduction in morbidity was not statistically significant, this was likely owing to the small number of women at such high risk for cesarean.

Importantly, use of the calculator and the observed improved maternal outcomes were not associated with increased risk of cesarean delivery or neonatal morbidity, which were of concern to some clinicians at our institution when the calculator was first presented. In fact, calculator implementation was associated with decreased cesarean deliveries. Calculator implementation was also associated with decreased maternal and neonatal length of stay, likely secondary to the decreased cesarean delivery rate.

Numerous prior studies have sought to develop risk prediction calculators in obstetrics for outcomes such as successful trial of labor after cesarean delivery and peripartum hemorrhage.12-15 Other groups have even developed similar calculators to ours for risk of cesarean delivery after labor induction.16,17 Such calculators are designed to be used clinically and to have an effect on quality of care. However, work evaluating the effects of implementing such calculators into routine care is scarce. In neonatology, a sepsis risk calculator predicts the likelihood of severe neonatal infection based on factors present at birth. Studies evaluating implementation of the sepsis risk calculator into care have successfully demonstrated that the results alter clinician practice and thereby reduce neonatal antibiotic administration and intensive care unit admissions.18-20 Here, we demonstrate that a risk prediction calculator within obstetrics is associated with improvements in meaningful perinatal outcomes.

Strengths and Limitations

Strengths of this study include the prospective evaluation of more than 1500 women. Our high rate of use of the calculator for eligible patients throughout the study period (>80%) likely reflects the success of our multipronged implementation strategy.

Our study was performed at 1 urban academic hospital with exclusion criteria reflecting those used in the calculator’s creation, which may limit generalizability. However, our diverse population is a great advantage to a study focusing on maternal morbidity. In addition, the fact that our institution has a limited number of clinicians with similar practice patterns, and yet the calculator result was still able to have such a significant association, indicates that results might be even stronger in practice models with increased practice variation. An additional limitation is the preimplementation and postimplementation design, susceptible to unmeasured bias. However, no other institutional process changes designed to improve maternal morbidity occurred during the study. Although the results of a large multicenter randomized clinical trial supporting elective induction at a gestational age of 39 weeks may have affected gestational age at induction during our study period,11 we were able to control for this difference in our models. Our stratified analysis by predicted cesarean delivery risk is limited by the small sample size at highest risk of cesarean delivery. Finally, although we were able to examine measurable differences in the induction process, such as time to cesarean, the association of knowledge of cesarean delivery risk with decision-making during induction was not evaluated. Such data may provide a deeper understanding of factors mediating the association between implementation of the cesarean risk calculator and reduced obstetric morbidity.

Conclusions

Clinical use of this validated calculator is a simple intervention. With it, we have the potential to reduce maternal morbidity and cesarean rate broadly, without compromising neonatal outcomes. It is important to note, however, that not every patient with a predicted risk of 60.0% or greater should will require a cesarean delivery. Conversely, even with predicted risk of less than 20.0%, some women will require cesarean delivery. In addition, a result on this validated calculator should never be used to delay a medically indicated induction. The calculator result should always be used in clinical context. Future work should quantitatively and qualitatively evaluate the effect of this intervention on patient and clinician decision-making, as well as examine the effect of the cesarean risk calculator when implemented at diverse sites.

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Article Information

Accepted for Publication: September 15, 2020.

Published: November 13, 2020. doi:10.1001/jamanetworkopen.2020.25582

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Hamm RF et al. JAMA Network Open.

Corresponding Author: Rebecca F. Hamm, MD, MSCE, Maternal and Child Health Research Center, Department of Obstetrics and Gynecology, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St, Two Silverstein, Philadelphia, PA 19104 (rebecca.feldmanhamm@uphs.upenn.edu).

Author Contributions: Drs Hamm and Levine had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Hamm, Bogner, Srinivas, Levine.

Acquisition, analysis, or interpretation of data: Hamm, McCoy, Oladuja, Bogner, Elovitz, Morales, Levine.

Drafting of the manuscript: Hamm, Morales, Levine.

Critical revision of the manuscript for important intellectual content: Hamm, McCoy, Oladuja, Bogner, Elovitz, Srinivas, Levine.

Statistical analysis: Hamm, Morales, Levine.

Obtained funding: Hamm.

Administrative, technical, or material support: McCoy, Elovitz, Levine.

Supervision: McCoy, Bogner, Elovitz, Srinivas, Levine.

Conflict of Interest Disclosures: Dr Hamm reported receiving grants from Eunice Kennedy Shriver National Institute of Child Health and Human Development during the conduct of the study. Dr Srinivas reported providing expert testimony for Post & Schell, PC. No other disclosures were reported.

Funding/Support: This study was supported by The Penn Presbyterian George and Emily McMichael Harrison Fund for Research in ObGyn and a T32 training grant in reproductive epidemiology from the National Institutes of Health.

Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Meeting Presentation: These data were presented at the 40th Annual Meeting of the Society for Maternal-Fetal Medicine Pregnancy; February 2, 2020; Grapevine, Texas.

References
1.
Osterman  MJ, Martin  JA.  Recent declines in induction of labor by gestational age.   NCHS Data Brief. 2014;(155):1-8.PubMedGoogle Scholar
2.
Grobman  WA.  Predictors of induction success.   Semin Perinatol. 2012;36(5):344-347. doi:10.1053/j.semperi.2012.04.017 PubMedGoogle ScholarCrossref
3.
Tolcher  MC.  Predicting cesarean delivery following induction.   J Womens Health (Larchmt). 2020;29(5):607. doi:10.1089/jwh.2019.8187PubMedGoogle ScholarCrossref
4.
Vahratian  A, Zhang  J, Troendle  JF, Sciscione  AC, Hoffman  MK.  Labor progression and risk of cesarean delivery in electively induced nulliparas.   Obstet Gynecol. 2005;105(4):698-704. doi:10.1097/01.AOG.0000157436.68847.3b PubMedGoogle ScholarCrossref
5.
Levine  LD, Downes  KL, Parry  S, Elovitz  MA, Sammel  MD, Srinivas  SK.  A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix.   Am J Obstet Gynecol. 2018;218(2):254.e1-254.e7. doi:10.1016/j.ajog.2017.11.603PubMedGoogle ScholarCrossref
6.
Hamm  RF, Downes  KL, Srinivas  SK, Levine  LD.  Using the probability of cesarean from a validated cesarean prediction calculator to predict labor length and morbidity.   Am J Perinatol. 2019;36(6):561-566. doi:10.1055/s-0038-1675625 PubMedGoogle ScholarCrossref
7.
Bell  AF, Andersson  E.  The birth experience and women’s postnatal depression: a systematic review.   Midwifery. 2016;39:112-123. doi:10.1016/j.midw.2016.04.014 PubMedGoogle ScholarCrossref
8.
Sadler  LC, Davison  T, McCowan  LM.  Maternal satisfaction with active management of labor: a randomized controlled trial.   Birth. 2001;28(4):225-235. doi:10.1046/j.1523-536X.2001.00225.x PubMedGoogle ScholarCrossref
9.
von Elm  E, Altman  DG, Egger  M, Pocock  SJ, Gøtzsche  PC, Vandenbroucke  JP; STROBE Initiative.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.   J Clin Epidemiol. 2008;61(4):344-349. doi:10.1016/j.jclinepi.2007.11.008 PubMedGoogle ScholarCrossref
10.
Hollins Martin  CJ, Martin  CR.  Development and psychometric properties of the Birth Satisfaction Scale−Revised (BSS-R).   Midwifery. 2014;30(6):610-619. doi:10.1016/j.midw.2013.10.006 PubMedGoogle ScholarCrossref
11.
Martin  CR, Hollins Martin  CJ, Burduli  E, Barbosa-Leiker  C, Donovan-Batson  C, Fleming  SE.  Measurement and structural invariance of the US version of the Birth Satisfaction Scale−Revised (BSS-R) in a large sample.   Women Birth. 2017;30(4):e172-e178. doi:10.1016/j.wombi.2016.11.006 PubMedGoogle ScholarCrossref
12.
Macones  GA, Hausman  N, Edelstein  R, Stamilio  DM, Marder  SJ.  Predicting outcomes of trials of labor in women attempting vaginal birth after cesarean delivery: a comparison of multivariate methods with neural networks.   Am J Obstet Gynecol. 2001;184(3):409-413. doi:10.1067/mob.2001.109386 PubMedGoogle ScholarCrossref
13.
Hashima  JN, Eden  KB, Osterweil  P, Nygren  P, Guise  JM.  Predicting vaginal birth after cesarean delivery: a review of prognostic factors and screening tools.   Am J Obstet Gynecol. 2004;190(2):547-555. doi:10.1016/j.ajog.2003.08.045 PubMedGoogle ScholarCrossref
14.
Costantine  MM, Fox  K, Byers  BD,  et al.  Validation of the prediction model for success of vaginal birth after cesarean delivery.   Obstet Gynecol. 2009;114(5):1029-1033. doi:10.1097/AOG.0b013e3181bb0dde PubMedGoogle ScholarCrossref
15.
Kawakita  T, Mokhtari  N, Huang  JC, Landy  HJ.  Evaluation of risk-assessment tools for severe postpartum hemorrhage in women undergoing cesarean delivery.   Obstet Gynecol. 2019;134(6):1308-1316. doi:10.1097/AOG.0000000000003574 PubMedGoogle ScholarCrossref
16.
Danilack  VA,  et al.  Development and validation of a risk prediction model for cesarean delivery after labor induction.   J Womens Health (Larchmt). 2020;29(5):656-669. doi:10.1089/jwh.2019.7822 PubMedGoogle ScholarCrossref
17.
Rossi  RM, Requarth  E, Warshak  CR, Dufendach  KR, Hall  ES, DeFranco  EA.  Risk calculator to predict cesarean delivery among women undergoing induction of labor.   Obstet Gynecol. 2020;135(3):559-568. doi:10.1097/AOG.0000000000003696 PubMedGoogle ScholarCrossref
18.
Beavers  JB, Bai  S, Perry  J, Simpson  J, Peeples  S.  Implementation and evaluation of the early-onset sepsis risk calculator in a high-risk university nursery.   Clin Pediatr (Phila). 2018;57(9):1080-1085. doi:10.1177/0009922817751337 PubMedGoogle ScholarCrossref
19.
Gievers  LL, Sedler  J, Phillipi  CA,  et al.  Implementation of the sepsis risk score for chorioamnionitis-exposed newborns.   J Perinatol. 2018;38(11):1581-1587. doi:10.1038/s41372-018-0207-7 PubMedGoogle ScholarCrossref
20.
Dhudasia  MB, Mukhopadhyay  S, Puopolo  KM.  Implementation of the sepsis risk calculator at an academic birth hospital.   Hosp Pediatr. 2018;8(5):243-250. doi:10.1542/hpeds.2017-0180 PubMedGoogle ScholarCrossref
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