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. 2023 Jun 8;18(6):e0286863. doi: 10.1371/journal.pone.0286863

Regional practice variation in induction of labor in the Netherlands: Does it matter? A multilevel analysis of the association between induction rates and perinatal and maternal outcomes

Pien Offerhaus 1,*, Tamar M van Haaren-Ten Haken 1, Judit K J Keulen 1, Judith D de Jong 2,3, Anne E M Brabers 2, Corine J M Verhoeven 4,5,6,7,8,9, Hubertina C J Scheepers 10, Marianne Nieuwenhuijze 1,11
Editor: David Desseauve12
PMCID: PMC10249899  PMID: 37289749

Abstract

Background

Practice variation in healthcare is a complex issue. We focused on practice variation in induction of labor between maternity care networks in the Netherlands. These collaborations of hospitals and midwifery practices are jointly responsible for providing high-quality maternity care. We explored the association between induction rates and maternal and perinatal outcomes.

Methods

In a retrospective population-based cohort study, we included records of 184,422 women who had a singleton, vertex birth of their first child after a gestation of at least 37 weeks in the years 2016–2018. We calculated induction rates for each maternity care network. We divided networks in induction rate categories: lowest (Q1), moderate (Q2-3) and highest quartile (Q4). We explored the association of these categories with unplanned caesarean sections, unfavorable maternal outcomes and adverse perinatal outcomes using descriptive statistics and multilevel logistic regression analysis corrected for population characteristics.

Findings

The induction rate ranged from 14.3% to 41.1% (mean 24.4%, SD 5.3). Women in Q1 had fewer unplanned caesarean sections (Q1: 10.2%, Q2-3: 12.1%; Q4: 12.8%), less unfavorable maternal outcomes (Q1: 33.8%; Q2-3: 35.7%; Q4: 36.3%) and less adverse perinatal outcomes (Q1: 1.0%; Q2-3: 1.1%; Q4: 1.3%). The multilevel analysis showed a lower unplanned caesarean section rate in Q1 in comparison with reference category Q2-3 (OR 0.83; p = .009). The unplanned caesarean section rate in Q4 was similar to the reference category. No significant associations with unfavorable maternal or adverse perinatal outcomes were observed.

Conclusion

Practice variation in labor induction is high in Dutch maternity care networks, with limited association with maternal outcomes and no association with perinatal outcomes. Networks with low induction rates had lower unplanned caesarean section rates compared to networks with moderate rates. Further in-depth research is necessary to understand the mechanisms that contribute to practice variation and the observed association with unplanned caesarean sections.

Introduction

Practice variation in healthcare is a complex issue. Although some variation can be expected in relation to population differences or patient preferences, it is clear that other factors such as institutional mechanisms within organizations [1], individual practice styles of professionals and scientific uncertainty [2, 3] also contribute to practice variations. Variations are unwarranted if they cannot be explained by type or severity of illness, patient risk factors or patient preferences [2, 4, 5]. Practice variation may indicate insufficient quality of care as a result of underuse or overuse of interventions.

In maternity care, large practice variations in childbirth interventions have been reported, both between countries [6–8] and within countries [9–12]. This indicates that maternity care interventions may be performed ‘too little, too late’ or ‘too much, too soon’ [13]. Factors such as insufficient accessibility of care on the one hand or over-medicalization of normal physiological childbirth on the other hand, can result in underuse or overuse of interventions in maternity care. Both underuse and overuse may cause harm for the mother or the baby [13]. Reducing unwarranted practice variation can be a strategy for enhancing quality of maternity care and realizing optimal maternal and perinatal outcomes.

Practice variation in maternity care is an issue that also needs attention and further exploration in the Netherlands [11]. In the research project VAriation in Labor InDuction (VALID) we focus on practice variation in one intervention, namely induction of labor (IOL) in the Netherlands. In the VALID project we explore the different mechanisms that influence decision-making on IOL, how these mechanisms contribute to practice variation, what variation in IOL is unwarranted and how unwarranted variation may be reduced. Our focus on IOL has several reasons. First, in the last decades the use of IOL has increased in the Netherlands—as in many high income countries—to 24.4% of all term singleton births, affecting almost 40,000 women in 2019 [14]. Second, in a relatively homogenous group of women, IOL rates varied from less than 10% to over 40% in Dutch hospitals in 2012 [15]. Third, IOL is a major intervention in the course of a pregnancy, which should be performed only when the expected benefits outweigh its potential harms. Although randomized controlled trials show some advantages for maternal or perinatal health in favor of IOL compared to expectant management in specific situations such as mild pre-eclampsia or a gestational age above 41 weeks [16, 17], in other situations the evidence supporting IOL is weak or conflicting [18–21]. In observational studies, IOL is associated with less favorable outcomes such as an increased need for epidural analgesia and more unplanned caesarean sections [22–26]. In short, risks and benefits of IOL in the term period are not always clear. Furthermore, a metasynthesis of qualitative research on women’s experiences indicated that decision-making on IOL as well as undergoing an IOL can be challenging experiences for women [27]. In the Netherlands, an IOL is often preceded by a referral from midwife-led primary care to obstetrician-led secondary care. Such a referral in itself may affect women’s experiences [28, 29].

It is unclear what impact practice variation in IOL rates has on maternal and perinatal outcomes. The objective of this substudy of the VALID project therefore is to explore the potential impact of this variation on maternal and perinatal outcomes. The results of the study can contribute to the reflection on the use of IOL in the Netherlands and internationally.

Methods

We performed a population-based retrospective cohort study in the Netherlands using the Dutch national perinatal database Perined.

Setting

In the Netherlands, almost 90% of all women start antenatal care in midwife-led primary care in the community [14]. As long as pregnancy and birth develop normally, women continue to receive midwife-led primary care and can opt for a birth at home, in a hospital or birth center, attended by their own midwife. In case of pregnancy or birth complications or increased risks, women are referred to obstetrician-led secondary care and the birth will take place in the hospital. Obstetrical interventions such as IOL are only available in obstetrician-led secondary care in the hospital, and require a referral to obstetrician-led care if a woman is still in midwife-led primary care [30]. This implies that in most cases both primary care midwives and secondary care staff members (obstetricians, residents and hospital-based midwives) are involved in the chain of decisions that leads to an advice for an IOL to individual women.

Midwifery practices and hospitals are organized regionally in maternity care networks (MCN). Next to midwives and obstetricians, these networks often other disciplines such as nurses, maternity care assistants and pediatricians [31]. In 2018, there were 77 MCNs in the Netherlands. Most MCNs are organized around one hospital and the midwifery practices in the same region. Usually, this hospital provides secondary obstetric and neonatal care with a Neonatal Intensive Care Unit (NICU) level 1 and 2. If the hospital is a tertiary (university) center, a NICU up to level 4 is available. Only ten MCNs have a tertiary center in their network, the other MCNs refer to these tertiary centers if necessary. The size of MCNs in terms of the number of midwives and obstetricians involved, varies from around 30 to 120 professionals and depends on the number of births in that region. An MCN is jointly responsible for providing high-quality maternity care in the region [32]. Within these MCNs, collaboration and reasons for referral are established between primary and secondary care, usually based on national guidelines and/or the national referral list for obstetric care [33]. Qualitative research shows that mechanisms within MCNs such as the interdisciplinary collaboration, local protocols, beliefs and attitudes towards childbirth, and women’s involvement, influence decisions in maternity care [34, 35]. Therefore, MCNs are the appropriate unit of analysis for investigating regional practice variation in IOL in Dutch maternity care.

Database and variables

The Perined database includes data from medical records of almost all births in the Netherlands, routinely collected in separate registers per maternity care professionals (midwives, general practitioners, obstetricians and pediatricians) and combined into one national database [14, 36]. For our study, we included a group of women with a relatively low risk for severe pregnancy complications. We selected all records in the years 2016–2018 of women who had a singleton, vertex birth of their first child (nulliparous) at a gestational age of at least 37 weeks (term): the so-called NTSV group. This NTSV group may be considered a relatively homogeneous study population and is therefore suitable to investigate regional practice variation [15]. Records with missing data on gestational age, parity, or vertex/non-vertex presentation at birth were not included.

For every record in the Perined database, the identity of the MCN is anonymously available for analysis. For each MCN, the presence of a NICU (level 4) in its own hospital or not is also registered (NICU availability). Perined assigns a record to a MCN based on the hospital of birth or, in case of a homebirth, based on the collaboration with local hospitals of the midwifery practice that attended the birth. Records in the Perined database with a missing MCN code were not included.

We collected information on the start of labor (spontaneous, induction of labor, caesarean section planned before the onset of labor) and the various obstetrical techniques used to induce labor (amniotomy, Foley or balloon catheter, prostaglandins or oxytocin). Membrane sweeping was not considered a method of induction of labor in this study.

Furthermore, we collected maternal, pregnancy, birth and perinatal characteristics as available in the Perined database. We collected information on maternal age, social economic status (SES) based on the four digits of the postal code and ethnic background (Dutch or non-Dutch). We also collected information on pregnancy complications (diabetes; suspected abnormal fetal growth: small for gestational age or large for gestational age; reduced fetal movements; hypertensive disorders) and on referrals from midwife-led primary care to obstetrician-led secondary care during antenatal care and during labor. Birth characteristics were: planned and actual place of birth, augmentation of labor with oxytocin, methods of pain relief (opioids or epidural anesthesia), birth mode (spontaneous vaginal, assisted vaginal, planned caesarean section before the onset of labor, unplanned caesarean section), postpartum blood loss > 1000 ml, and perineal trauma (3rd or 4th degree perineal tear; episiotomy). Perinatal characteristics were birthweight, Apgar score at 5 minutes, admission to a NICU in a tertiary center, perinatal mortality up to the 7th day after birth, and serious or lethal congenital malformations. A birthweight under the 3rd percentile was considered as small for gestational age, and above the 97th percentile as large for gestational age. Macrosomia was defined as a birthweight above 4500g.

Analysis

Practice variation

IOL rates in the NTSV group were calculated per MCN, with the total number of women in the NTSV group per MCN as denominator. Mean IOL rate and the range in IOL rates in MCNs were calculated. We performed case-mix correction for available socio-demographic factors that are associated with maternal health and therefore may have impact on the IOL rate in MCNs based on population characteristics: women’s social economic status (SES) and ethnic background. Lifestyle factors such as BMI and smoking were not available. Factors that may have variable impact per MCN on IOL decision are not included in the case-mix correction, since controlling for these factors might mask the practice variation that we aim to explore in this project. Therefore, we did not include maternal age, birthweight, planned place of birth and NICU availability. We categorized MCNs, based on their ranking after case-mix correction. MCNs with a ranking in the lowest quartile (Q1) were categorized as having a low IOL rate and in the highest quartile (Q4) as having a high IOL rate. The other MCNs (Q2 and Q3) were categorized as having a moderate IOL rate.

Association with outcomes

Our aim was to explore the association of a low or high IOL rate in MCNs with maternal and perinatal outcomes. Outcomes of interest were mode of birth (spontaneous vaginal birth, assisted vaginal birth or unplanned caesarean section), blood loss >1000 ml, 3rd/4th perineum tear or episiotomy, and adverse perinatal outcomes (perinatal mortality, low 5 minute Apgar score <4 and <7, and NICU admission within 24 hours). We defined a dichotomous maternal composite outcome describing unfavorable maternal outcomes, combining assisted vaginal birth or caesarean section, blood loss > 1000 ml, 3rd or 4th degree sphincter lesion. Adverse perinatal outcomes were combined in a composite, including perinatal mortality < 7 days, 5 minute Apgar score <4 and NICU admission.

We excluded records of the small group of women with a caesarean section planned before onset of labor (1.2%). Records in which Perined registered the birth of a child born with severe or lethal congenital anomalies were excluded as well (see Fig 1 for a flowchart).

Fig 1. Flowchart of the study population.

Fig 1

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We explored the associations between IOL categories and the outcomes of interest with descriptive statistics (Chi Square). We further explored these associations with multilevel logistic regression analysis to control for possible confounding by population characteristics that may explain variation in outcomes. We analyzed unplanned caesarean sections, the maternal composite outcome and the perinatal composite outcome in separate models. The independent variable in each model was the MCN category for IOL rates (Q1: low, Q2/Q3: moderate, Q4: high). The moderate IOL rate group was the reference category. We used multilevel fixed effects models to take into account clustering of women within MCNs. In the maternal models, we controlled forward stepwise for sociodemographic confounders (SES and ethnic background, maternal age) and pregnancy characteristics (presence of pregnancy complications, macrosomia >4500g). Presence of pregnancy complications (diabetes; suspected abnormal fetal growth: small for gestational age or large for gestational age; reduced fetal movements; hypertensive disorders) were combined in a dichotomous composite confounding variable. In the perinatal model we controlled forward stepwise for sociodemographic confounders (SES and ethnic background; maternal age), NICU availability in the MCN, and pregnancy characteristics (presence of pregnancy complications, SGA). In none of the models we controlled for gestational age, since we consider this as an outcome of IOL rather than a characteristic in this study and therefore not as a confounding factor. We also did not control for level of care (midwife-led primary or obstetrician-led secondary care) at start of labor or place of birth, as we considered this partly an outcome of the maternity care process within the MCNs that might be related to their IOL rate [37]. Descriptive analysis was performed in SPSS version 25 and multilevel regression analysis using R version 4.0.1. (www.R-project.org).

Ethical approval

The Medical Ethical Committee of Zuyderland-Zuyd University confirmed that ethical approval was not required for his study according to the Dutch legislation and regulations (reference METCCZ20210008). Consent was given by Perined for anonymous data analysis at MCN level.

Results

Description of the current variation

In the study period, the Perined database contained 586,630 records of 77 MCNs; 184,422 of these records concerned women with a nulliparous, term, singleton, vertex pregnancy: the NTSV group. The mean number of NTSV women per MCN in this three-year period was 2416.4 (SD 1334.4; range 660–6183). Overall, 23.6% of these women experienced an IOL: 23.3% in 2016, and 23.8% in both 2017 and 2018. The observed IOL rate per MCN in the NTSV group ranged from 14.3% to 41.1%.

MCNs were assigned to the lowest quartile (Q1), moderate quartiles (Q2-3) and highest quartile (Q4). The IOL rate ranged from 18.0% in Q1 to 30.8% in Q4, and the rate for spontaneous start of labor ranged from 66.6% (Q4) to 77.8% (Q1) in the three categories (see Table 1). Overall, the planned caesarean section rate was low and ranged from 1.0% in Q1 to 1.4% in Q4. Various methods for performing an IOL were used. In all groups, around half of the IOLs started with a Foley catheter. In Q4, more IOLs were performed from the beginning of the term period until the gestational age of 41+6 weeks, compared to Q2-3 and Q1. In week 42, more IOLs were performed in Q1. In all three categories, IOL rates were highest in week 38 and 41.

Table 1. NTSV start of labor characteristics in MCNs with low, moderate or high induction of labor rates.

  Q1 (low)
n = 52979		 Q2-3 (moderate)
n = 91638		 Q4 (high)
n = 39805
Start of labor      
Spontaneous 41209 77.8% 67908 74.1% 26513 66.6%
Induction of labor (IOL) 9537 18.0% 21793 23.8% 12255 30.8%
Planned caesarean section 535 1.0% 1139 1.2% 557 1.4%
Unknown 1698 3.2% 798 0.9% 480 1.2%
Method IOL % within NTSV % within IOL % within NTSV % within IOL % within NTSV % within IOL
Amniotomy only 1301 2.5% 13.6% 3381 3.7% 15.5% 1013 2.5% 8.3%
Prostaglandins 1468 2.8% 15.4% 2672 2.9% 12.3% 1814 4.6% 14.8%
Oxytocin 2281 4.3% 23.9% 5856 6.4% 26.9% 3144 7.9% 25.7%
Foley 4487 8.5% 47.0% 9884 10.8% 45.4% 6284 15.8% 51.3%
Total 9537 18.0% 100% 21793 23.8% 100% 12255 30.8% 100%
IOL in week % within NTSV % within IOL % within NTSV % within IOL % within NTSV % within IOL
37+0–37+6 1206 2.3% 12.6% 2724 3.0% 12.5% 1505 3.8% 12.3%
38+0–38+6 2034 3.8% 21.3% 4694 5.1% 21.5% 3172 8.0% 25.9%
39+0–39+6 1633 3.1% 17.1% 3851 4.2% 17.7% 2171 5.5% 17.7%
40+0–40+6 1386 2.6% 14.5% 3376 3.7% 15.5% 1737 4.4% 14.2%
41+0–41+6 2207 4.2% 23.1% 5671 6.2% 26.0% 3271 8.2% 26.7%
≥42+0 1071 2.0% 11.2% 1477 1.6% 6.7% 399 1.0% 3.1%
Total 9537 18.0% 100% 21793 23.8% 100% 12255 30.8% 100.0%
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Missings in variables are not shown. Due to missings, numbers not always add up to the total number in Q1, Q2-3 and Q4. Percentages are calculated on valid numbers.

Population characteristics in the three IOL rate categories showed no great differences (see S3 Table), although more women lived in a higher SES area in Q1, and more in a lower SES area in Q4. Pregnancy complications as registered in Perined did not show large differences over the three categories. As expected in this relatively healthy group of women, in most records no pregnancy complications were registered (Q1: 76.9%; Q2-3: 75.7%; Q4: 73.5%). In the lowest IOL rate category, a larger proportion of women received midwife-led primary care at the start of antenatal care (Q1: 94.0%; Q2-3: 93.3%; Q4: 90.5%) and a larger proportion of women stayed in midwife-led primary care until start of labor (Q1: 66.6%; Q2-3: 60.5%; Q4: 52.3%).

Neonatal characteristics showed small differences. In line with the lower IOL rate, gestational age was the highest in Q1 (Q1: 279.9 days (SD 8.5); Q2-3: 279.4 (SD 8.6); Q4: 278.6 (SD 8.6); p <0.001). In Q1 the mean birthweight was also slightly higher (Q1: 3443g (SD 457); Q2-3: 3434g (SD 460); Q4: 3387g (SD 456); p < 0.001).

Birth characteristics

Table 2 describes birth characteristics in the three IOL-rate categories. The pregnancy and birth care path varied between the three categories. At the time of birth, a higher proportion of women in Q1 received midwife-led primary care (Q1: 25.6%, Q2-3: 21.8%; Q4: 17.5%), and less received secondary or tertiary care (Q1: 74.4%, Q2-3: 78.2%; Q4: 82.5%). At the same time, more women in Q1 had experienced an intrapartum referral from primary to obstetrician-led secondary care (Q1: 44.5%; Q2-3: 40.4%; Q4: 36.7%). More women in Q1 gave birth at home (Q1: 10.0%; Q2-3: 9.6%; Q4: 6.2%). In line with this variation in care paths, the use of interventions during labor varied. Overall use of oxytocin use during labor was lower in Q1 (Q1: 50.9%; Q2-3: 53.6%; Q4: 60.0%), as was the use of pharmaceutical pain relief (no use of pain relief in Q1: 52.0%; Q2-3: 47.5%; Q4:40.2%).

Table 2. Birth characteristics in MCNs with low, moderate or high induction of labor rates.

(NTSV group, excluding planned CS/congenital anomalies).

  Q1 (low)
n = 50419		 Q2-3 (moderate)
n = 89139		 Q4 (high)
n = 38360
Birth characteristics
Place and level of care at birth      
Birth in primary midwife-led care 12857 25.6% 19350 21.8% 6670 17.5%
primary care, home 5026 10.0% 8538 9.6% 2372 6.2%
primary care, birth center 2101 4.2% 1056 1.2% 425 1.1%
primary care, place unknown 999 2.0% 570 .6% 272 .7%
primary care, hospital 4731 9.4% 9186 10.3% 3601 9.4%
Birth in secondary/tertiary care, hospital 37343 74.4% 69442 78.2% 31459 82.5%
after referral from primary care during labor 22330 44.5% 35899 40.4% 14002 36.7%
Augmentation/oxytocin first stage 24262 50.9% 46854 53.6% 22461 60.0%
after spontaneous start 17802 45.9% 31472 47.7% 13044 51.2%
after IOL by prostaglandins 959 68.1% 1695 64.4% 1161 67.1%
after IOL by Foley 3436 80.8% 7906 81.3% 5155 84.0%
after IOL by oxytocin 2065 100.0% 5781 100.0% 3101 100.0%
Pharmaceutical pain relief first stage
none 26199 52.0% 42362 47.5% 15430 40.2%
opioid 5395 10.7% 10374 11.6% 5235 13.6%
epidural 15410 30.6% 32163 36.1% 15738 41.0%
other/unknown 3415 6.8% 4240 4.8% 1957 5.10%
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Missings in variables are not shown. Due to missings, numbers not always add up to the total number in Q1, Q2-3 and Q4. Percentages are calculated on valid numbers.

Association of variation in IOL rates with maternal and perinatal outcomes

In Table 3, the outcomes of interest are described. We observed that more women in Q1 had a spontaneous vaginal birth (Q1: 73.2%; Q2-3: 71.8%; Q4: 69.9%; p < 0.001) and less women gave birth by unplanned caesarean section (Q1: 10.2%; Q2-3: 12.1%; Q4: 12.8%; p < 0.001). Postpartum blood loss >1000 ml (Q1: 7.5%; Q2-3: 7.8%; Q4: 6.9%, p< 0.001) as well as a sphincter lesion (Q1: 3.9%; Q2-3: 3.5%; Q4: 2.9%; p <0.001) were more prevalent in Q1 in comparison with Q4. Less women in Q1 received an episiotomy (Q1: 31.1%; Q2-3: 34.4%; Q4: 38.8%; p < 0.001). The maternal composite (non-spontaneous birth, postpartum blood loss >1000 ml, 3rd/4th degree tear) showed a lower prevalence in Q1 than in Q4 (Q1: 33.8%; Q2-3: 35.7%; Q4: 36.3%, p < 0.001).

Table 3. Maternal and perinatal outcomes in MCNs with low, moderate or high induction of labor rates.

(NTSV group, excluding planned caesarean section/congenital anomalies).

Q1 (low)
n = 50419		 Q2-3 (moderate)
n = 89139		 Q4 (high)
n = 38360
n % (95% CI) n % (95% CI) n % (95% CI)
Mode of birth
Spontaneous vaginal** 36883 73.2 (72.8–73.5) 63972 71.8 (71.5–72.1) 26825 69.9 (69.5–70.4)
Assisted vaginal** 7329 14.5 (14.2–14.8) 13513 15.2 (14.9–15.4) 6200 16.2 (15.8–16.5)
Unplanned caesarean section** 5148 10.2 (9.9–10.5) 10742 12.1 (11.8–12.3) 4891 12.8 (12.4–13.1)
unknown 1059 2.1 (2.0–2.2) 912 1.0 (1.0–1.1) 444 1.2 (1.1–1.3)
Maternal outcomes
Postpartum blood loss (PPH) > 1000 cc** 3776 7.5 (7.3–7.7) 6989 7.8 (7.7–8.0) 2653 6.9 (6.9–7.2)
3rd/4th degree perineal tear** 1957 3.9 (3.7–4.1) 3085 3.5 (3.3–3.6) 1127 2.9 (2.8–3.1)
Episiotomy** 15688 31.1 (30.7–31.5) 30707 34.4 (34.1–34.8) 14880 38.8 (38.3–39.3)
Unfavorable maternal outcomes composite** (non-spontaneous birth, PPH, 3rd/4th degree tear) 16718 33.8 (33.4–34.2) 31571 35.7 (35.4–36.1) 13763 36.3 (35.8–36.8)
Perinatal outcomes
Apgar score 5 min <7# 946 1.9 (1.8–2.0) 1517 1.7 (1.6–1.8) 687 1.8 (1.7–1.9)
Apgar score 5 min < 4# 170 0.3 (0.3–0.4) 294 0.3 (0.3–0.4) 116 0.3 (0.3–0.4)
Perinatal mortality up to day 7# 66 0.13 (0.10–0.17) 130 0.15 (0.12–0.17) 42 0.11 (0.08–0.15)
NICU admission** 402 0.8 (0.7–0.8) 756 0.8 (0.8–0.9) 404 1.1 (1.0–1.2)
Adverse perinatal composite* (mortality, AS<4, NICU) 518 1.0 (0.9–1.1) 980 1.1 (1.1–1.2) 482 1.3 (1.1–1.4)
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Missings in variables are not shown. Due to missings, numbers not always add up to the total number in Q1, Q2-3 and Q4. Percentages are calculated on valid numbers. Outcomes were tested statistically (Chi Square)

CI: confidence interval

# no statistically significant difference, p> 0.05

* statistically significant difference, p < 0.05

** statistically significant difference, p< 0.001

The perinatal composite (perinatal mortality, AS <4, NICU) showed a lower prevalence in Q1 (Q1: 1.0%; Q2-3: 1.1%; Q4: 1.3%, p = 0.005) in the descriptive analysis. Admittance to a NICU within 24 hours (Q1: 0.8%: Q2-3: 0.8%; Q4: 1.1%, p < 0.001) contributed most to this difference. The other elements in the perinatal composite showed no significant differences between the IOL categories in this analysis.

Table 4 presents the outcomes of the exploratory multilevel analysis for maternal and perinatal outcomes. Q2-3 was the reference category in all models. For the outcome unplanned caesarean section, the crude analysis showed a lower risk in the low IOL rate category Q1 (odds ratio (OR) 0.84; 95% CI 0.81–0.87; p <0.001), and a higher risk in the high IOL rate category Q4 (OR 1.07; 95% CI 1.03–1.11; p <0.001) in comparison with Q2-3. In the multilevel model, the lower risk remained statistically significant for Q1, but for Q4 the difference with the reference category was no longer statistically significant. Controlling for sociodemographic confounders and for pregnancy characteristics and macrosomia did not alter this result. In the final model, the OR for Q1 was 0.83 (95% CI 0.72–0.95; p = 0.009) after controlling for all confounders, suggesting a lower risk for unplanned caesarean section in MCNs with a low IOL rate in comparison with the reference category. For the high IOL rate category Q4, the multilevel analysis showed no difference in risk for an unplanned caesarean section, in comparison with the reference category.

Table 4. Associations of low and high rates in induction of labor in MCNs with primary outcomes, in comparison with MCNs with a moderate induction of labor rate in (multilevel modelling).

OR (95% CI)
Q1 (low)		 p-value OR (95% CI)
Q4 (high)		 p-value variance
UNPLANNED CAESAREAN SECTION
crude OR
(no modelling) 0.84 (0.81–0.87) < 0.001 1.07 (1.03–1.11) < 0.001 NA
1.Empty model
(fixed effect multilevel, no confounders) 0.83 (0.72–0.95) 0.006 1.02 (0.89–1.17) 0.777 0.053
2.Sociodemographic confounders
 2a: model 1 + SES and Ethnic background 0.83 (0.72–0.95) 0.008 1.01 (0.88–1.16) 0.885 0.057
 2b: model 1 + SES and Ethnic background + maternal age 0.82 (0.71–0.95) 0.007 1.01 (0.88–1.17) 0.874 0.061
3.Sociodemographic + pregnancy characteristics
 3a: model 2b + pregnancy complications 0.83 (0.72–0,96) 0.010 0.99 (0.88–1.16) 0.896 0.062
 3b: model 2b + macrosomia (birthweight ≥ 4500g) 0.82 (0.71–0.95) 0.006 1.02 (0.89–1.18) 0.747 0.062
 3c: model 2b + pregnancy complications + macrosomia 0.83 (0.72–0.95) 0.009 1.00 (0.87–1.16) 0.967 0.062
MATERNAL COMPOSITE
crude OR
(no modelling) 0.92 (0.90–0.94) < 0.001 1.02 (0.998–1.05) 0.073 NA
1.Empty model
(fixed effect multilevel, no confounders) 0.93 (0.85–1.01) 0.103 1.03 (0.94–1.12) 0.526 0.023
2.Sociodemographic confounders
 2a: model 1 + SES and Ethnic background 0.93 (0.85–1.01) 0.087 1.03 (0.94–1.12) 0.513 0.023
 2b: model 1 + SES and Ethnic background + maternal age 0.92 (0.84–1.01) 0.068 1.03 (0.94–1.13) 0,473 0.024
3.Sociodemographic + pregnancy characteristics
 3a: model 2b + pregnancy complications 0.92 (0.84–1.01) 0.085 1.02 (0.94–1.12) 0.608 0.025
 3b: model 2b + macrosomia (birthweight ≥ 4500g) 0.92 (0.84–1.01) 0.069 1.04 (0.95–1.14) 0.387 0.024
 3c: model 2b + pregnancy complications + macrosomia 0.92 (0.84–1.01) 0.085 1.03 (0.94–1.13) 0.508 0.025
NEONATAL COMPOSITE
crude OR
(no modelling) 0.93 (0.84–1.04) 0.210 1.14 (1.03–1.28) 0.016 NA
1.Empty model
(fixed effect multilevel, no confounders) 0.999 (0.67–1.50) 0.998 0.97 (0.64–1.47) 0.869 0.501
2.Sociodemographic confounders
 2a: model 1 + SES and Ethnic background 1.01 (0.67–1.52) 0.967 0.96 (0.63–1.47) 0.864 0.500
 2b: model 1 + SES and Ethnic background + maternal age 1.01 (0.67–1.52) 0.971 0.99 (0.63–1.47) 0.870 0.494
3.Sociodemographic including NICU availability
 3: model 2b + NICU availability 0.96 (0.76–1.22) 0.748 0.86 (0.67–1.10) 0.220 0.124
4.Sociodemographic + pregnancy characteristics
 4a: model 3 + pregnancy complications 0.96 (0.76–1.22) 0.757 0.86 (0.67–1.10) 0.218 0.124
 4b: model 3 + SGA (birthweight <p3) 0.97 (0.77–1.22) 0.761 0.86 (0.67–1.09) 0.215 0.123
 4c: model 3 + SGA + pregnancy complications 0.97 (0.77–1.22) 0.769 0.86 (0.67–1.09) 0.212 0.123
Open in a new tab

OR: odds ratio; CI: confidence interval

The crude OR for the unfavorable maternal outcomes composite was significantly lower for Q1 (Q1: OR 0.92; 95% CI 0.90–0.94; p < 0.001). For Q4 no significant difference with the reference category was observed (Q4: OR 1.02; 95% CI 0.998–1.05; p = 0.073). In the multilevel analysis, we found no statistically significant association with the IOL rate categories in any model.

For the perinatal composite, neither the crude analysis nor the multilevel models showed any statistically significant association with the IOL rate categories.

Discussion

We observed high practice variation between maternity care networks (MCNs) in IOL rates in a relatively homogenous group of nulliparous women with a term singleton vertex birth (NTSV group). We also observed that the association of these IOL rates with maternal or perinatal outcomes is limited. In a multilevel logistic regression analysis, the unplanned caesarean section rate was lower in the MCNs with a low IOL rate compared to MCNs in the moderate group, but in MCNs with a high IOL rate this outcome was comparable with the moderate group. We found no other significant associations between IOL rates and perinatal or maternal outcomes in this multilevel analysis.

Our exploratory analysis suggests a lower number of unplanned caesareans in the NTSV group in MCNs with a low IOL rate, and no impact on the other investigated outcomes. This lower caesarean section rate in our observational study seems in contrast with several RCTs that report no significant differences in caesarean sections when IOL is compared with expectant management in case of specific pregnancy complications [16–19]. The results of the ARRIVE trial [20] even suggests that IOL at 39 weeks gestation reduced caesarean sections in comparison with expectant management in a study population of nulliparous women with uncomplicated pregnancies. However, the ARRIVE trial reported a caesarean section rate of 18.6% in the IOL group vs. 22.2% in the expectant management group, which is considerably higher than the caesarean section rate observed in our study groups. Furthermore, the ARRIVE trial might suffer from selection bias [38]. It is therefore questionable whether the results of the ARRIVE trial can be generalized to the Dutch setting.

Altogether, the causality of the association we observed is unclear and requires further investigation. We cannot simply recommend MCNs to lower their use of IOL based on this observation. Firstly, we do not know what mechanisms explain the association we found. For instance, it may well be that an overall non-interventionist-approach in these MCNs explains both the low IOL rate and the lower number of unplanned CS. This is underpinned by our observation that the pregnancy and birth care process varied between the MCNs, in association with the IOL rates. On average, the provision of midwife-led primary care during birth was higher in the MCNs with low IOL rates. In addition, early term IOL before 39 weeks, and interventions during labor and birth were lower than in the MCNs with high IOL rates. Interestingly, in these MCNs also more women gave birth at home. Altogether, this suggests that a low IOL rate in a MCN represents a maternity care philosophy with a stronger tendency to a physiological, non—interventionist approach, probably both in professionals and in the women to whom they provide care. Secondly, a general recommendation to lower the IOL rate in a specific MCN might affect the decision-making in situations where IOL is the optimal treatment based on sound evidence. A MCN that considers changing their overall IOL rates needs to investigate on what indications the decision-making process on IOL might be optimized, taking available evidence and national guidelines into account.

Considering the limited association with outcomes, the high practice variation in IOL in the NTSV group warrants close attention. In the Netherlands, the general advice during the study period was—and still is–not to actively offer elective induction of labor to women [39]. Only if medical complications or risks are present, such as pregnancy hypertension or suspected fetal growth retardation induction of labor should be advized [39], or if pregnancy is prolonged [40]. It is unlikely that in our relatively homogenous study population, the observed variation in IOL can be fully explained by the prevalence of such pregnancy complications, especially since maternal and pregnancy characteristics in our descriptive analysis showed limited differences between the MCNs with a lower, moderate or higher IOL rate.

Instead, our study suggests that other mechanisms within the MCNs contribute to the variation. These mechanisms might be related to the organization or protocols within the MCNs, or to shared norms and beliefs [34, 41]. Various authors suggest that a perception of pregnancy and birth as predominantly physiological events or more as risky events, may influence maternity care professionals in their tendency to intervene [35, 42–45]. Especially in situations where the evidence base to perform an IOL is not very strong [21], such mechanisms may lead to variation between MCNs. For instance, studies on IOL such as the ARRIVE trial may influence beliefs and attitudes and may change the threshold to offer IOL, regardless of recommendations in national guidelines.

Although most studies on practice variation focus on professional decisions for medical treatment, the role of women should not be overlooked. Preferences of women are important, and variation should be found on the level of the patient rather than on the level of professionals or their organizations [46]. The literature on practice variation suggests that involvement of patient preferences by introducing shared decision-making may shift variation from the level of professionals and their organizations to variations on the individual level of patients. Some evidence supporting this suggestion is already available [47]. In recent years, the value of shared decision-making in maternity care in the Netherlands has been recognized and women are increasingly involved in decisions. Many women have strong preferences regarding IOL decisions, reflected in requests for elective IOL, or on preferences for expectant management in case of mild pregnancy complications [48]. However, research among women who recently gave birth in the Netherlands suggests that women’s involvement in IOL decisions is not optimal. A substantial proportion of women who experienced an IOL, perceived at least some pressure from professionals to accept this intervention [49], as was earlier described in other countries [50, 51].

Altogether, more in depth research is needed to understand the dynamics in professionals and their organizations and in women that contribute to the observed variation in IOL rates. Therefore, the next step in the VALID project will be to unravel the mechanisms that contribute to the observed practice variation, taking into account the social contexts of the MCNs and differences in population or policy. We use a sociological model for understanding practice variation that includes mechanisms in professionals and their local MCNs as well as in women, including the process of shared decision-making [52]. Insights in these mechanisms will help to define recommendations to optimize decision-making for IOL, and may reduce unwarranted practice variation in IOL.

Limitations and strength

We performed our study with routinely collected data from the Perined database. This database gives limited information on several health determinants that may vary between MCNs, such as smoking and obesity. Therefore, we could not include these factors in our analysis and some confounding may still be present. However, we do not expect that correction for these factors would have much impact on the results of the multilevel models. Correction for other potential confounders (SES, maternal age, pregnancy complications) had only limited impact on the outcome of the modelling procedures.

Another limitation of the Perined database is that a straightforward registration of pregnancy complications, such as hypertension or reduced fetal movements, is not available. Perined computes the presence of these complications using various variables recorded in the separate registers. Some misclassification may occur, but we do not consider this as a source for important bias in our study, as this misclassification is not selective.

Despite these limitations, the Perined database offers the optimal opportunity to study practice variation within the Netherlands. Variation in IOL rates may be a result of complex patterns in MCNs, at the level of women, midwifery practices and hospitals. A major strength of the Perined database is that information on all these levels is available on a national level. Therefore, we were able to include the total NTSV population of the Netherlands in our study.

Conclusion

Practice variation between MCNs in IOL rates in the NTSV group is high in the Netherlands, ranging from 14.3% to 41.1%. We observed no association between IOL rates and perinatal outcomes, and a limited association with maternal outcomes. MCNs with low IOL rates had lower unplanned caesarean section rates compared to MCNs with moderate IOL rates. MCNs with high IOL rates had similar unplanned caesarean section rates in comparison with MCNs with moderate IOL rates. More in depth research is necessary to understand the mechanisms that contribute to the observed high practice variation and to explain the observed association with unplanned caesarean sections. This may help to reduce unwarranted variation between MCN and improve quality of care.

Supporting information

S1 Table. Overview of nulliparous term singleton vertex (NTSV) population in MCNs 2016–2018.

(DOCX)

Click here for additional data file. (20.4KB, docx)
S2 Table. Start of labor per year in NTSV population.

(DOCX)

Click here for additional data file. (22.1KB, docx)
S3 Table. NTSV population and pregnancy characteristics in MCNs with low, moderate and high IOL rate.

(DOCX)

Click here for additional data file. (25.1KB, docx)
S1 Fig. MCN practice variation in IOL in nulliparous women with a term singleton pregnancy with a vertex presentation.

(DOCX)

Click here for additional data file. (92.7KB, docx)

Acknowledgments

We thank Lisa Broeders (Perined) for supporting data provision, and Marian Heins (NIVEL) for her support with the statistical analysis

Abbreviations

CI

Confidence interval

IOL

Induction of labor

MCN

Maternity care network (Verloskundig samenwerkings verband

NICU

Neonatal intensive care unit

NTSV

Nulliparous term singleton vertex (pregnancy)

SD

Standard deviation

SES

Social-economic status

SGA

Small for gestational age

Data Availability

"Data cannot be shared publicly because the perinatal register Perined does not allow public sharing of data that contain potentially identifying or sensitive information without women’s consent. Data are available from Perined (contact via info@perined.nl) for researchers who meet the criteria for access to confidential data. The dataset underlying the results presented in this study is available from Perined (WWW.Perined.nl) on request. The current study is registered at Perined as number 20.09. Data can be requested by sending an email to info@Perined.nl or by filling in the application form ‘Aanvraagformulier gegevens’ that can be found on the webpage https://www.perined.nl/onderwerpen/onderzoek/gegevensaanvragen."

Funding Statement

This study was supported by a grant from the Netherlands Organisation for Health Research and Development (www.ZonMw.nl) grant no. 543003312. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

David Desseauve

21 Dec 2022

PONE-D-22-29662Regional practice variation in induction of labor in the Netherlands: does it matter? A multilevel analysis of the association between induction rates and perinatal and maternal outcomesPLOS ONE

Dear Dr. Offerhaus,

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Reviewer #2: Partly

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Reviewer #1: Yes

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Reviewer #1: General comments

The objective of this Dutch population-based retrospective cohort study was to explore the association between IOL variations and maternal and perinatal outcomes. The authors focused on a homogeneous group: nulliparous women with a vertex singleton at term. They reported that IOL rates ranged from 14.3% to 41.1% in the Netherlands between 2016 and 2018 in 77 maternity care networks. They observed a lower risk of unplanned cesarean delivery in maternity care networks with low versus moderate IOL rates after controlling for maternal and neonatal cofunding factors and accounting for clustering in maternity care networks through multilevel logistic regression. They observed no difference between IOL rates and poor maternal or perinatal outcomes. Interestingly, interventions during labor (augmentation of labor with oxytocin, use of epidural analgesia, episiotomy) were lower in networks with low IOL rates than in networks with high IOL rates, suggesting a philosophy of maternity care based on a physiologic, noninterventionist approach.

The manuscript is original and well written. It covers a very interesting topic on obstetric interventions and their impact on adverse maternal and perinatal outcomes. Finally, the authors pointed out that women's preference may be the key to understanding variations in interventions. They pointed out that patient involvement through shared medical decisions is essential.

Nevertheless, there are some limitations. First, all results are presented without confidence intervals, which limits their interpretation. Second, the authors categorized maternity care networks according to their case-mix adjustment ranking in a logistic regression, but they did not explain why they used only two sociodemographic variables (social economic status and ethnicity) in their model. Thus, the categorization of low, moderate, or high IOL rate should be developed and clarified. In the multilevel logistic regression, there was no adjustment for gestational age. The authors considered gestational age not to be a cofactor but an outcome of IOL. However, poor neonatal outcomes are related to gestational age. In addition, the distribution of gestational age varied from the lowest to the highest IOL rates. There were significantly more IOLs performed for prolonged pregnancy (>42SA) in Q1 than in Q2-3 and Q4. Unfortunately, obesity was absent from the Perined database. Obesity may be a factor in IOL failure or adverse maternal outcomes. The authors discussed this limitation in the Discussion section.

Here are some minor comments

Abstract

Page 8 Lines 30-31 The objective is not clearly formulated

Page 9 Line 51-52 “Networks with low induction rates had lower unplanned caesarean section rates compared to networks with moderate or high rates”. Sentence should be rephrased as networks with low induction rates were not compared to networks with high rates.

Methods

Page 13 Line 149 : What did you mean by “birth characteristics were planned” ?

Page 14, Line 182- 183 “We analyzed unplanned caesarean sections, the maternal composite outcome and the perinatal composite outcome in separate models. » Why did you choose to analyze the association between IOL categories and unplanned cesarean deliveries and a maternal composite outcome which included cesarean delivery ?

Page 15 Line 188 Could you precise « pregnancy complications » ? Is it included small and large for gestational age ?

Page 15 Line 190 « NCIU availability » This variable was not described in the « database and variables » section. Could you provide clarification ?

Reviewer #2: The work presented here is very interesting and the variations in IOL is an important subject that needs to be better assessed.

My comments

Introduction : the introduction is quite long. Nevertheless, I don't feel that it reflects well the problematic that is the risk and benefit of IOL. Moreover it does not cite a very important paper on the subject that is the ARRIVE trial which significantly changed the current practice.

The introduction should better clarify the research question that is either to confirm that variation exist, which is my opinion is not such an important message and two what are the impact of such variations on maternal and neonatal outcomes which is indeed very interesting.

Methods & Results :

The reason for induction is not described. This is very important as it might significantly influence both maternal and neonatal outcomes. Similarly we lack information about maternal characteristics such as age or BMI which may influence outcomes. Although the authors controlled for such coufounding factors these should be clearly shown.

Table 3 Confidence interval are missing which impairs comparaison

Discussion The ARRIVE trial should be discussed

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Reviewer #2: No

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PLoS One. 2023 Jun 8;18(6):e0286863. doi: 10.1371/journal.pone.0286863.r002

Author response to Decision Letter 0

13 Feb 2023

We would like to thank both reviewers for their time and effort to comment on our study. We address the remarks one by one for each reviewer. Line numbers in our response refer to the revised version with track changes.

Response to reviewer 1

We thank the reviewer for the compliments on the article.

• “all results are presented without confidence intervals”

We added confidence intervals to Table 3 and 4, in which the outcomes of interest are presented and analysed. Table 1 and 2 present the description of the national study population. Since this information is purely descriptive, we do not think confidence intervals add much value and we did not calculate them.

• “[the authors] did not explain why they used only two sociodemographic variables (social economic status and ethnicity) in their model. Thus, the categorization of low, moderate, or high IOL rate should be developed and clarified.”

We performed case-mix correction for available socio-demographic factors that are associated with maternal health and therefore may have an impact on the IOL rate in MCNs based on population characteristics: women’s social economic status (SES) and ethnic background. Lifestyle factors that might have an impact the IOL rate such as BMI and smoking were not available in our data. Factors that may have variable impact per MCN on IOL decisions are not included in the case-mix correction, since controlling for these factors might mask the practice variation that we aim to explore in this project. Therefore, we did not include maternal age, birthweight, planned place of birth and NICU availability. We added this information on the case mix correction in line 168-174.

• “The authors considered gestational age not to be a cofactor but an outcome of IOL. However, poor neonatal outcomes are related to gestational age. In addition, the distribution of gestational age varied from the lowest to the highest IOL rates. There were significantly more IOLs performed for prolonged pregnancy (>42GA) in Q1 than in Q2-3 and Q4.”

We did consider adjustment for gestational age. However, our population consists of women with term pregnancies. Within the term period, the association of gestational age with perinatal outcomes exists but is of limited magnitude, until a gestational age of 42 weeks. Since we considered gestational age also an outcome, we decided altogether not to include this in the multilevel models.

We indeed observed a small difference in gestational age (Q1: 279.9 days; Q2-3: 279.4 days; Q4: 278.6 days) and somewhat more IOLs in Q1 (2.0% vs 1.6% in Q2-3 and 2.0% in Q4) for prolonged pregnancy. We hypothesize in the discussion that this is a result of different policies in Q1 and Q4. If more expectant management is practiced in a region, leading to less IOLs throughout the term period (as is shown in table 1), more women will reach a gestational age of 42 weeks and will receive an advice for labour induction. One could argue that having more prolonged pregnancies in a region might lead to less favourable neonatal outcomes, but we did not observe this in our models, even without controlling for gestational age.

Minor remarks:

• Lines 30-32 The objective is not clearly formulated

We changed the objective in: “We explored the association between induction rates and maternal and perinatal outcomes.”

• Line 51-53 “Networks with low induction rates had lower unplanned caesarean section rates compared to networks with moderate or high rates”. Sentence should be rephrased as networks with low induction rates were not compared to networks with high rates.

We removed “or high”.

• Line 155 : What did you mean by “birth characteristics were planned” ?

We added a colon to help the correct reading of this sentence (line 155): ‘ Birth characteristics were: planned and actual place of birth, …etc.’

• Line 195-196 “We analyzed unplanned caesarean sections, the maternal composite outcome and the perinatal composite outcome in separate models. » Why did you choose to analyze the association between IOL categories and unplanned cesarean deliveries and a maternal composite outcome which included cesarean delivery?

We decided to use this maternal composite, because we wanted to describe unfavorable maternal outcomes in one measure, to be able to perform our explorative analysis. In such a composite measure, unplanned caesarean section cannot be excluded. We also analyzed unplanned caesarean sections separately, because this is considered an important or primary maternal outcome in many studies.

• Line 201 Could you precise « pregnancy complications » ? Is it included small and large for gestational age ?

We added the following description of ‘pregnancy complications’ to the manuscript (line 201-203) ‘Presence of pregnancy complications (diabetes; suspected abnormal fetal growth: small for gestational age or large for gestational age; reduced fetal movements; hypertensive disorders) were combined in a dichotomous composite confounding variable.’

• Line 205 « NCIU availability » This variable was not described in the « database and variables » section. Could you provide clarification?

In the method section, we added: ‘For each MCN, the presence of a NICU (level 4) in its own hospital or not is also registered (NICU availability)’ (line 141-142).

Response to reviewer 2

• “The work presented here is very interesting and the variations in IOL is an important subject that needs to be better assessed.”

We thank the reviewer for this compliment and for acknowledging the importance of this topic.

• Introduction: I don't feel that [the introduction] reflects well the problematic that is the risk and benefit of IOL (##). Moreover, it does not cite a very important paper on the subject that is the ARRIVE trial which significantly changed the current practice (###).

The introduction should better clarify the research question (#) that is either to confirm that variation exist, which is my opinion is not such an important message and two what are the impact of such variations on maternal and neonatal outcomes which is indeed very interesting.

We react on the various underlined topics (#, ## and ###) in this remark

# We better clarified in the introduction that our research is an explorative study, that aims to explore the association between IOL rates and maternal and perinatal outcomes (line 97): ‘The objective of this substudy of the VALID project therefore is to explore the potential impact of this variation on maternal and perinatal outcomes.’

## Our study is not on the risk or benefit of IOL, but on practice variation in IOL and it is part of a larger research project into practice variation, the VALID study. We presented some more information on the VALID study in lines 77-80. The introduction of the current substudy aims to explain why we focus on practice variation in IOL in the VALID project. In the final stage of the VALID study, we plan to discuss to what extent practice variation is warranted or unwarranted. Information on outcomes associated with this practice variation can contribute to this discussion.

### In the introduction, we present some of the issues concerning IOL. One of the issues is that the evidence for the benefit or harm of IOL versus expectant management is not always clear. We refer in that context to the ARRIVE trial (reference 20, line 88), among other studies. We added a sentence (line 90-91): ‘In short, risks and benefits of IOL in the term period are not always clear.’

At this moment, the effects of the ARRIVE trial on the Dutch IOL policy are not clear. A national guideline on elective induction was published after publication of the ARRIVE trial, in which it is recommended not to actively offer elective induction to women with uncomplicated term pregnancies. We mention this guideline in the discussion section (reference 39, see lines 338-340). However, the publication of the ARRIVE trial generated some discussion in the Netherlands. It is possible that it influenced the individual attitudes and beliefs of care professionals or pregnant women – in both directions, either a more liberal or more restricted attitude towards IOL- , resulting in different regional policies towards IOL. We added a sentence in the discussion section to explain this (lines 351-352: “For instance, studies on IOL such as the ARRIVE trial may influence beliefs and attitudes and may change the threshold to offer IOL, regardless of recommendations in national guidelines.”)

This highlights the importance of the broader VALID project: to explore and understand the mechanisms of practice variation on IOL and the association with outcomes.

• Methods & Results :

The reason for induction is not described. This is very important as it might significantly influence both maternal and neonatal outcomes. Similarly, we lack information about maternal characteristics such as age or BMI, which may influence outcomes. Although the authors controlled for such confounding factors these should be clearly shown.

The main reason for not describing the reasons for induction is that this information is not reliably available in the Perined dataset. Furthermore, ‘reason for induction’ is not a stable indicator for the health or complications in pregnancy. Reasons for induction are subject to regional variation within the Netherlands. This is our experience in the broader VALID project (publication in preparation). Recently other authors showed this also for the topic ‘fetal growth restriction’ (Marijnen et al. Practice variation in diagnosis, monitoring and management of fetal growth restriction in the Netherlands. Eur J Obstet Gynecol Reprod Biol. 2022, doi 10.1016/j.ejogrb.2022.07.021).

We agree with the reviewer that pregnancy problems that might be reason for IOL may influence outcomes. We therefore used registered pregnancy complications as an indicator for maternal health in pregnancy. In this revised version, we explain our definition of pregnancy complications in lines 201-203. We added the presence of pregnancy complications as a confounder in the multilevel analysis as shown in table 4. We also present information on registered pregnancy complications in supplementary table S3.

Information on relevant lifestyle factors such as BMI and substance abuse (e.g. smoking) are not available in the database. Information on maternal age and a limited number of other influencing factors are available and are presented in supplementary table S3, as mentioned in line 232.

• Table 3 Confidence interval are missing which impairs comparison

We have added confidence intervals in table 3 and 4.

• Discussion: The ARRIVE trial should be discussed

We added a paragraph in the discussion on the difference between our results regarding caesarean sections and the results of RCTs on IOL vs expectant management (line 310-319) and a line on the possible effect on attitudes and beliefs regarding IOL (line 351-352).

We are aware that results of observational research does not always reflect the results in RCTs. In case of the ARRIVE trial, we think that this study cannot be generalized to the Dutch setting. In this revised version of the article, we discuss this in line 315-319: “However, the ARRIVE trial reported a caesarean section rate of 18.6% in the IOL group vs. 22.2% in the expectant management group, which is considerably higher than the caesarean section rate observed in our study groups. Furthermore, the ARRIVE trial might suffer from selection bias. It is therefore questionable whether the results of the ARRIVE trial can be generalized to the Dutch setting.”

Attachment

Submitted filename: response to reviewers_def.docx

Click here for additional data file. (25.6KB, docx)

Decision Letter 1

David Desseauve

25 May 2023

Regional practice variation in induction of labor in the Netherlands: does it matter? A multilevel analysis of the association between induction rates and perinatal and maternal outcomes

PONE-D-22-29662R1

Dear Dr. Offerhaus,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

David Desseauve, MD, MPH, PhD

Academic Editor

PLOS ONE

Acceptance letter

David Desseauve

30 May 2023

PONE-D-22-29662R1

Regional practice variation in induction of labor in the Netherlands: does it matter? A multilevel analysis of the association between induction rates and perinatal and maternal outcomes

Dear Dr. Offerhaus:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Overview of nulliparous term singleton vertex (NTSV) population in MCNs 2016–2018.

    (DOCX)

    Click here for additional data file. (20.4KB, docx)
    S2 Table. Start of labor per year in NTSV population.

    (DOCX)

    Click here for additional data file. (22.1KB, docx)
    S3 Table. NTSV population and pregnancy characteristics in MCNs with low, moderate and high IOL rate.

    (DOCX)

    Click here for additional data file. (25.1KB, docx)
    S1 Fig. MCN practice variation in IOL in nulliparous women with a term singleton pregnancy with a vertex presentation.

    (DOCX)

    Click here for additional data file. (92.7KB, docx)
    Attachment

    Submitted filename: response to reviewers_def.docx

    Click here for additional data file. (25.6KB, docx)

    Data Availability Statement

    "Data cannot be shared publicly because the perinatal register Perined does not allow public sharing of data that contain potentially identifying or sensitive information without women’s consent. Data are available from Perined (contact via info@perined.nl) for researchers who meet the criteria for access to confidential data. The dataset underlying the results presented in this study is available from Perined (WWW.Perined.nl) on request. The current study is registered at Perined as number 20.09. Data can be requested by sending an email to info@Perined.nl or by filling in the application form ‘Aanvraagformulier gegevens’ that can be found on the webpage https://www.perined.nl/onderwerpen/onderzoek/gegevensaanvragen."

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