Objective To develop a patient decision aid (PtDA) for mode of delivery after caesarean section that integrates personalised prediction of vaginal birth after caesarean (VBAC) with the elicitation of patient preferences and evidence-based information.Design A PtDA was developed and pilot tested using the International Patients Decision Aid Standards (IPDAS) criteria.Setting Obstetric health care in the Netherlands.Population A multidisciplinary steering group, an expert panel, and 25 future users of the PtDA, i.e. women with a previous caesarean section.Methods The development consisted of a construction phase (definition of scope and purpose, and selection of content, framework, and format) and a pilot testing phase by interview. The process was supervised by a multidisciplinary steering group.Main outcome measures Usability, clarity, and relevance.Results The construction phase resulted in a booklet including unbiased balanced information on mode of birth after caesarean section, a preference elicitation exercise, and tailored risk information, including a prediction model for successful VBAC. During pilot testing, visualisation of risks and clarity formed the main basis for revisions. Pilot testing showed the availability of tailored structured information to be the main factor involving women in decision-making. The PtDA meets 39 out of 50 IPDAS criteria (78%): 23 out of 23 criteria for content (100%) and 16 out of 20 criteria for the development process (80%). Criteria for effectiveness (n = 7) were not evaluated.Conclusions An evidence-based PtDA was developed, with the probability of successful VBAC and the availability of structured information as key items. It is likely that the PtDA enhances the quality of decision-making on mode of birth after caesarean section.

ObjectiveAfter one previous caesarean section (CS), pregnant women can deliver by elective repeat CS or have a trial of labor which can end in a vaginal birth after caesarean (VBAC) or an unplanned CS. Despite guidelines describing women’s rights to make an informed choice, trial of labor and VBAC rates vary greatly worldwide. Many women are inadequately informed due to caregivers’ fear of an increase in CS rates in a high VBAC rate setting. We compared counseling with a decision aid (DA) including a prediction model on VBAC to care as usual. We hypothesize that counselling with the DA does not decrease VBAC rates. In addition, we aimed to study the effects on unplanned CS rate, patient involvement in decision-making and elective repeat CS rates.MethodsWe performed a prospective cohort study. From 2012 to 2014, 483 women in six hospitals, where the DA was used (intervention group), were compared with 441 women in six matched hospitals (control group). Women with one previous CS, pregnant of a singleton in cephalic presentation, delivering after 37 weeks 0 days were eligible for inclusion.ResultsThere was no significant difference in VBAC rates between the intervention (45%) and control group (46%) (adjusted odds ratio 0,92 (95% Confidence interval 0.69–1.23)). In the intervention group more women (42%) chose an elective repeat CS compared to the control group (31%) (adjusted odds ratio 1.6 (95% Confidence interval 1.18–2.17)). Of women choosing trial of labor, in the intervention group 77% delivered vaginally compared to 67% in the control group, resulting in an unplanned CS adjusted odds ratio of 0,57 (0.40–0.82) in the intervention group. In the intervention group, more women reported to be involved in decision-making (98% vs. 68%, P< 0.001).ConclusionsImplementing a decision aid with a prediction model for risk selection suggests unchanged VBAC rates, but 40% reduction in unplanned CS rates, increase in elective repeat CS and improved patient involvement in decision-making.

A large practice variation exists in elective repeat cesarean section and vaginal birth after cesarean rates that can only partially be explained by risk factors at patient level.

ObjectivesDiscussing the individual probability of a successful vaginal birth after caesarean (VBAC) can support decision making. The aim of this study is to externally validate a prediction model for the probability of a VBAC in a Dutch population.MethodsIn this prospective cohort study in 12 Dutch hospitals, 586 women intending VBAC were included. Inclusion criteria were singleton pregnancies with a cephalic foetal presentation, delivery after 37 weeks and one previous caesarean section (CS) and preference for intending VBAC. The studied prediction model included six predictors: pre-pregnancy body mass index, previous vaginal delivery, previous CS because of non-progressive labour, Caucasian ethnicity, induction of current labour, and estimated foetal weight ≥90th percentile. The discriminative and predictive performance of the model was assessed using receiver operating characteristic curve analysis and calibration plots.ResultsThe area under the curve was 0.73 (CI 0.69–0.78). The average predicted probability of a VBAC according to the prediction model was 70.3% (range 33–92%). The actual VBAC rate was 71.7%. The calibration plot shows some overestimation for low probabilities of VBAC and an underestimation of high probabilities.ConclusionsThe prediction model showed good performance and was externally validated in a Dutch population. Hence it can be implemented as part of counselling for mode of delivery in women choosing between intended VBAC or planned CS after previous CS.

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