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Empirical Investigations

The Effect of Multiprofessional Simulation-Based Obstetric Team Training on Patient-Reported Quality of Care

A Pilot Study

Truijens, Sophie E.M. MSc; Banga, Franyke R. MD; Fransen, Annemarie F. MD; Pop, Victor J.M. MD, PhD; van Runnard Heimel, Pieter J. MD, PhD; Oei, S. Guid MD, PhD

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Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare: August 2015 - Volume 10 - Issue 4 - p 210-216
doi: 10.1097/SIH.0000000000000099
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During the last decade, there has been a growing interest in patient-centered care, with perceived quality of care and patient satisfaction becoming important indicators of care quality.1–3 Besides medical outcome, measurement of the patient’s perspective is a common strategy to monitor quality of care in a number of countries.1,4 Therefore, patient-reported quality of care is becoming more important as an outcome measure of training and education.

In the Netherlands, obstetric care is organized through independent levels of care: primary care (represented by independent midwives providing care to low-risk pregnant women) and secondary care (represented by obstetric nurses, hospital midwives, residents, and obstetricians who are responsible for high-risk pregnancies). Within this care system, a low-risk pregnant woman has the possibility of planning her delivery either at home or in a primary care hospital setting, under the supervision of her own independent midwife. During pregnancy and/or delivery, a pregnant woman may evolve from low risk to high risk, resulting in a referral from primary to secondary care. Approximately 85% of pregnancies start antenatal care in primary care and 15% in secondary care, whereas eventually, 29% give birth in primary care and 71% in secondary care.5 Approximately 65% of all pregnant women are at least once referred from primary to secondary care during pregnancy or labor, resulting in multiple medical handovers that require optimal collaboration. Several studies showed that most adverse events in obstetrics are partially explained by ineffective teamwork and communication.6–8 Furthermore, recently published data showed that women who had been referred to hospital during pregnancy reported a lower perceived quality of care.9 Because trend analysis has shown an increase in referral rate,10 improving communication and collaboration between and within different levels of care are important to achieve better quality of care.

A recent review of Weaver et al11 concluded that team training in health care improves teamwork processes and can positively impact patient outcomes. With regard to team training methods, simulation-based team training is a common modality and has shown to produce substantial educational benefits.11–13 Therefore, a promising intervention that could enhance team performance in both acute and nonacute care is multiprofessional simulation-based team training in the whole obstetric collaborative network.

Previous studies have shown that simulation-based obstetric team training improves team performance14,15 and might improve perinatal outcomes.16,17 Furthermore, Crofts et al12 showed that multiprofessional simulation-based obstetric training improved perceived quality of care, although this was reported by patient-actors instead of real patients. Previous research showed that multidisciplinary team training in crew resource management (CRM) results in positive reactions among trainees.18 These positive reactions correspond to the first level of Kirkpatrick’s model for the evaluation of training. After effective training, a positive attitude should result in a learning effect (level 2) and behavioral change (level 3) and eventually be translated into improved patient outcomes (level 4: medical or patient-reported outcome).19,20 Haller et al18 reported a positive effect of CRM training in a multidisciplinary obstetrical setting, evaluated at Kirkpatrick’s first, second, and third level. The next step is the evaluation at patient outcome level (level 4).

As research on the effects of multiprofessional obstetric team training on patient-reported quality of care has not been reported earlier, the aim of this study was to explore whether multiprofessional simulation-based obstetric team training improves quality of care as perceived by patients who recently gave birth.


This experimental pilot study applied a multiprofessional simulation-based obstetric team training intervention in the area of the Máxima Medical Center, a large teaching hospital in the Netherlands, representing 1 of the 10 Dutch perinatal centers. The area of this hospital is defined as semirural, and the hospital has an annual rate of almost 3000 deliveries. The obstetricians, residents, hospital midwives, and nurses from the obstetric department of the Máxima Medical Center and 11 midwifery practices that mainly refer their clients to this hospital were invited to participate in the team training intervention. Furthermore, ambulance service and maternity care were also invited to participate in the training.

The managers of the obstetric department of the hospital scheduled all secondary care providers, which resulted in a 100% participation rates with respect to the obstetric midwives, residents, and obstetricians, the 3 disciplines that have a key role in the communication with the primary care providers. The 11 midwifery practices that were invited to participate represented 35 primary care midwives, of which 24 (69%) could be scheduled in the training groups. Because the total number of obstetric nurses, ambulance staff, and maternity nurses working in this area is very large, we could only invite 2 of each of this discipline per training, organized by an open submission.

The obstetric collaborative network was trained in teams of approximately 16 health care professionals, including 2 ambulance staff, 2 maternity nurses, 4 to 5 independent community midwives, 2 obstetric nurses, 2 hospital midwives, 2 residents, and 2 obstetricians. During a 1-day training, the teams were trained in a medical simulation center with high-fidelity mannequins and extensive experience in obstetric team training. The groups were trained in teamwork skills by using the principles of CRM: know the environment, anticipate and plan, call for help early, exercise leadership and followership, distribute the workload, mobilize all available resources, communicate effectively, use all available information, prevent and manage fixation errors, cross (double) check, use cognitive aids, reevaluate repeatedly, apply good teamwork, allocate attention wisely, and set priorities dynamically.21 To strengthen the first element of deliberate practice—trainees’ motivation22—participants were expected to study a syllabus on communication, CRM, and medical knowledge. At the beginning of the training course, the participants completed a multiple-choice test about medical knowledge they should have learned from the syllabus. The training focused on process management (referral process between primary and secondary care in specific) of the 4 main causes of perinatal mortality, the so-called Big 4 disorders (causing 85.2% of the perinatal mortality): preterm delivery, congenital anomaly, small for gestational age, and low Apgar score.23 The 4 scenarios were unexpected home delivery of fetus in breech presentation, extreme premature delivery starting at home, home delivery with fetal distress and unexpected case of small for gestational age, and unexpected resuscitation of the newborn with congenital heart abnormality at home.

Before the start of the scenarios, the teams received an explanation concerning the equipment and environment of the simulation rooms. Each trainee participated actively in at least 1 scenario and often more and functioned as observer in the other scenarios (writing feedback about what they had observed). The scenarios started with a short introductory briefing video (approximately 2 minutes) with actors mimicking the medical situation and providing some background information about the simulated patient. Thereafter, the participants moved to the simulation room where they managed the simulated patient (Noelle, Gaumard Scientific, Miami, FL). The duration of the scenarios was approximately 15 minutes. All scenarios were videotaped (using B-Line Medical software, Washington, DC), and the recordings were used to facilitate the debriefing after each scenario. The debriefings had a duration of approximately 45 minutes and were facilitated by a communication trainer and an obstetrician who were educated in facilitating simulation-based team training. The debriefings contained 3 different phases: the reaction, analysis, and take home phase. The trainers provided feedback on nontechnical and technical skills using the video recordings. Elements of CRM were evaluated during the debriefing, such as attention situational awareness, self-awareness, leadership, assertiveness, decision making, flexibility, adaptability, and communication tools. There was a focus on standardized communication and handovers based on the SBAR [Situation, Background, Assessment, Recommendation] system of communication.

Before the team training intervention, a patient survey using a validated questionnaire was performed regarding the perceived quality of care during pregnancy and delivery. As Fox et al24 already stated, it is not easy to test the effect of simulation-based team training on patient outcomes, but the use of a validated questionnaire measuring quality of care as perceived by patients is one of the suggested possibilities.25 To measure quality of care as perceived by patients who have recently given birth, the Pregnancy and Childbirth Questionnaire (PCQ)9 was administered at 6 to 10 weeks postpartum. The PCQ has been developed after focus group interviews and has been validated using exploratory and confirmatory factor analyses in 2 separate samples of approximately 300 women who recently gave birth. More details with regard to the development and validation of this questionnaire have been described elsewhere.9 The PCQ consists of 25 items rated on a 5-point Likert scale from 1 (“totally agree”) to 5 (“totally disagree”). Positively formulated statements were recoded so that higher scores indicated higher quality of care. The PCQ showed good psychometric properties for both the total scale (25 items, Cronbach α = 0.92) and its 3 subscales as follows: personal treatment during pregnancy (11 items, α = 0.89), educational information (7 items, α = 0.83), and personal treatment during delivery (7 items, α = 0.86).9 Furthermore, the questionnaire contained items about demographic and obstetric features (age, level of education, gravidity, parity, previous miscarriage or abortion, gestational age when giving birth, trajectory of referral to secondary care, and mode of delivery). Dutch-speaking patients who gave birth in the hospital in March and April 2013 received a postal invitation at 6 weeks postpartum to fill out an online questionnaire (sample I, control group before the team training). Because of ethical reasons, patients with a perinatal death or preterm birth (<37 weeks of gestation) did not receive the questionnaire. Furthermore, patients who were not able to understand Dutch sufficiently were excluded because the questionnaires were only available and validated in Dutch. Responses were anonymous, which made it not possible to send a reminder to the nonresponders. The response rate of the first online patient survey without reminder was 36% within 4 weeks (sample I, control group before the team training).

In May and June 2013, the team training intervention was performed in the obstetric area of the hospital. In total, 80 health care professionals were trained in 5 groups of approximately 16 persons, representing the obstetric collaborative network. To measure the effect of the team training, the same questionnaire was sent to another sample of patients, at least 3 months after the intervention. The questionnaire was sent to a second sample of postpartum patients from the referral area of the obstetric network, who gave birth between September and November 2013 (sample II). Because of intensified hospital registration, at the time of the postintervention assessment, it was possible to collect e-mail addresses of the patients who gave birth in the hospital and invite them by e-mail to fill out the online questionnaire. As every patient received a unique link, it was possible to send a reminder to the patients who had not yet completed the questionnaire. The response rate with a reminder after 1 week resulted in a response rate of 57% within 4 weeks.

Statistical Analyses

Statistical analyses were performed using SPSS 20 (version 20, IBM, Chicago, IL). To test for differences between independent samples, Χ2 tests were used for categorical data (age category, educational level, parity, previous abortion or miscarriage, moment of referral to secondary care, and mode of delivery), and t tests were used for continuous data (gravidity, gestational age, and weeks since delivery). Frequency distributions of continuous data were checked on a normal distribution. To ensure a fair level of normality in the data, the skewness and kurtosis indices should not exceed absolute values of 3 and 10, respectively.26

With regard to the subgroups that we excluded because of ethical reasons, we calculated the rates of preterm birth and neonatal deaths in the period before the training (March-April 2013) and after the training (September-November 2013). We compared these rates post hoc as a secondary outcome measure.

Although the PCQ (in both primary and secondary obstetric care) has recently been validated, reliability analyses were repeated using Cronbach α.

Differences in questionnaire scores between groups were analyzed using independent samples t tests (2-tailed) or the Mann-Whitney U test (2-tailed), depending on violation of the assumption of normal distribution. Differences in scores between baseline and postintervention were analyzed on total scale, subscale, and item level. Finally, we explored which subscales and individual items showed the largest possible differences of scores after the team training intervention. When analyzing possible changes of scores on subscale level and item level, we performed Bonferroni adjustments to correct for multiple testing.

The Medical Ethic Research Committee of the Máxima Medical Center (Veldhoven, the Netherlands) decided that ethical approval was not required.


As shown in Table 1, demographic and obstetric features of the participants in the 2 samples (consisting of 76 postpartum patients in sample I and 68 in sample II) were comparable. There were no significant differences in patient characteristics between the 2 groups. Therefore, the questionnaire scores of the 2 samples were compared.

Patient Characteristics of the 2 Samples of Postpartum Women Who Completed the PCQ Between 6 and 10 Weeks After Giving Birth in Secondary Care

With regard to the subgroups (preterm birth and neonatal death), which we excluded because of ethical reasons, the rate of preterm births (between 24 and 37 weeks of gestation) was 17% in the first cohort (before the training, March-April 2013) and 21% in the second cohort, after the training (September-November 2013). The number of preterm babies that died decreased from 8.2% before the intervention to 5.4% after the intervention. The number of neonatal deaths (>37 weeks of gestations) was 1 (0.002%) in the first cohort and 0 (0.0%) in the second cohort. These post hoc comparisons might be included as surrogate outcome measures.

As shown in Table 2, the mean (SD) scores were significantly higher in those patients who completed the PCQ after the obstetric teams received the training (108.9 [10.9], n = 68), compared with those who completed the PCQ before the teams were trained (103.5 [11.6], n = 76, t = 2.74, P = 0.007). The effect size of 0.5 (Cohen d) represented a medium effect size of the change in PCQ total score.27 Reliability analyses in this secondary care population showed good internal consistency (Table 2) with comparable Cronbach α’s (0.80 to 0.93) as found in the validation study of this questionnaire.9

Mean Scores, Internal Reliability (Cronbach α), and Differences in Mean Scores (Δ) on the PCQ and Its 3 Subscales, Between Patients Who Gave Birth Before the Obstetric Team Was Trained (Sample I, n = 76) and Patients Who Gave Birth After the Obstetric Network Was Trained (Sample II, n = 68)

Both the subscales “personal treatment during pregnancy” (P = 0.005) and “educational information” (P = 0.001) showed a significant increase in perceived quality of care, but the subscale “personal treatment during delivery” showed no significant difference (P = 0.63).

Subsequently, the differences in perceived quality of care before and after the team training intervention were explored on item level and presented in Table 3.

PCQ Items With the Change in Mean Scores (Δ) Between Patients Who Gave Birth Before the Team Training Intervention (Sample I, n = 76) and Patients Who Gave Birth After the Obstetric Teams Were Trained (Sample II, n = 68)

After Bonferroni adjustments, 5 of the 25 items showed a significant increase after the team training (Table 3). These 5 items with the largest and significant increase (P ≤ 0.001) were about “involvement in planning” (item 4), “communication between health care professionals” (item 7), “leadership during pregnancy” (item 9), and “information provision” (items 14 and 17).


The aim of this pilot study was to explore whether multiprofessional simulation-based team training improves quality of care as perceived by patients who recently gave birth. The results of this study showed a significant increase in scores on the PCQ in patients who gave birth with the aid of health care professionals who received team training compared with another group of patients with similar characteristics who gave birth under the supervision of untrained staff. The effect size of this change in PCQ total score was medium (Cohen d, 0.5). The mean scores on the PCQ and its 3 subscales (before the team training) were comparable with the mean scores in a larger population with both primary and secondary obstetric care.9

When focusing on the changes in the PCQ subscales, our results showed an increase in the pregnancy-related subscales but no significant change in score on the delivery subscale. Exploration at the item level found that 5 of the 25 items (items 4, 7, 9, 14, and 17) increased significantly after team training. These items were related to communication between health care professionals, clear leadership, involvement in planning, and providing patients with better information. These items are related to a topic of growing interest: “continuity of care” (which is divided into informational continuity, management continuity, and relational continuity) and is assumed to be important regarding patients’ feeling of safety during labor.28

It is important to notice that all increased items originated from the pregnancy subscales, not the delivery subscale. The fact that both pregnancy-related subscales increased significantly whereas the delivery subscale did not might be surprising, as the simulation-based team training consisted of 4 delivery room scenarios. However, effective multiprofessional teamwork and communication using CRM and SBAR communication was the main focus of the team training. These nontechnical skills are competencies that are important in care during both pregnancy and delivery. Moreover, the training focused on process management (the referral process in specific), which is important during both pregnancy and delivery because 35% of the pregnant women are referred from primary care to secondary during pregnancy and 22% of the women are referred to secondary care during labor.

This finding might also be partially explained by the assumption that recently gained skills and competencies are better applied in nonacute rather than acute situations, as elevated stress levels during emergency situations impairs retrieval of information from memory.29 Although a stressful learning episode (like medical simulation training) may consolidate well into memory, the retrieval of previously learned material is less efficient under high levels of acute stress.29 This might explain why improvements in communication and leadership may be better expressed during the nonacute period of pregnancy than in acute delivery situations. Another reason for not finding any difference in the delivery subscale could be explained by the fact that we did not survey patients with preterm birth and perinatal death.

Furthermore, the training days are expected to positively stimulate team building, as health care professionals get to know each other better. This increase in interpersonal contact probably strengthens the collaboration in the obstetric network and might improve the referral process.

So far, no other studies have evaluated the effect of multiprofessional simulation-based obstetric team training on patient-reported quality of care. A recent study evaluated the effect of communication training among residents on the doctor-woman relationship during labor and delivery but found no significant increase in patient satisfaction.30 However, only the residents were trained instead of the whole obstetric collaborative network. Comparing these studies might advocate simulation-based training to promote more experiential learning. Moreover, a review of Rowe et al31 concluded that focused communication skills training for midwives and physicians may be of benefit but that further research was required. The study of Crofts et al12 showed multiprofessional training to improve perception of care but based this conclusion on the reports of actors instead of real patients.

The current study is among the first that investigates the effect of simulation-based obstetric team training on quality of care as perceived by patients. Patient-reported quality of care, measured with a validated questionnaire, could be classified as a level 4 outcome of Kirkpatrick’s model for the evaluation of training.19,20 Another strength is the multiprofessional character of this study, training an obstetric collaborative network, including ambulance staff, maternity nurses, independent community midwives, obstetric nurses, hospital midwives, residents, and gynecologists.

However, the current study has several limitations. The major limitation of this study was its nonrandomized design. To confirm a causal relationship, it would be better to perform baseline and postintervention measurements in the same group of patients or to use a randomized controlled trial design. However, as pregnancy and delivery are life events, it is not possible to ask the same participants before and after the intervention. Within the obstetric department of this hospital, a randomized controlled trial was not possible because patients receive care from several health care professionals and a clear distinction between trained and nontrained health care professionals has logistic limitations. In the future, researchers should perform a cluster trial with randomization at the hospital level (eg, a cluster randomized trial or a stepped wedge design).

The second limitation relates to the response rate. In the first sample, the response rate without a reminder was 36%, whereas in the second sample, with the option to send a reminder after 1 week, the response rate was 57%. The low response rates may bias the results and could have represented the measured differences in PCQ score between the 2 groups. A higher response rate would have achieved a better representation of the whole population. However, it should be mentioned that previous studies showed that unannounced Web-based surveys are known to have a low response rate. Cook et al32 presented a review including 68 survey studies and found a mean response rate of 39.6%, with approximately half of the surveys including a reminder. The review of Hoonakker and Carayon33 reported Web-based surveys to have a response of 50.5%. In this light, our response rates of 36% without reminder and 57% with a reminder were not in contrast to the general response rates of unannounced Web-based surveys.

With regard to the difference in group characteristics, the trend in different referral patterns might bias the results. One point that might partly explain this trend is the general trend in the Netherlands toward delivery in secondary care (partly as a consequence of the increase in request for pain relief).5 However, one should realize that, although the difference between the referral groups is not significant, this trend in change toward secondary care might bias the results.

Furthermore, patients with a perinatal death (0.002%) or preterm birth (17%–21%) did not receive the questionnaire because of ethical reasons, but because this might bias the results, this exclusion criterion should be mentioned as a limitation of this study.

Another limitation is the gap regarding measures of team performance or behavior (Kirkpatrick’s level 3) between the training and the patient-reported outcomes. Because we did not measure team performance, we cannot make the causal leap from the intervention to an improved team performance and to an improved patient-reported outcome. Future research should include data about the change in team performance, for example, using a tool such as the clinical teamwork scale.15,34

Another suggestion for further research is the implementation of repetition elements of deliberate practice.35 Because the results of this study showed an improvement in patient-reported quality of care during pregnancy but not during delivery, we assume that repetition of the learned skills will contribute to better performance, even during stressful delivery situations. The retrieval of previously learned material is assumed to be less efficient under high levels of acute stress, and the gained skills should therefore be repeatedly trained.29

In summary, the results of this pilot study showed a higher score on overall patient-reported quality of care after multiprofessional simulation-based obstetric team training of staff in an obstetric collaborative network. The possibility that the improvement in perceived quality of care might be related to the team training intervention is supported by the fact that the 5 items with a large and significant increase are related to the principles of CRM in which the teams were trained. Given the limitations of the study, we cannot show a causal association between the training and the results. Taking into account these limitations, this study contributes to the field of research that evaluates the effects of simulation-based obstetric team training on patient outcome level and will hopefully stimulate further research.


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Simulation; Obstetrics; Multiprofessional team training; Quality of health care; Patient outcome assessment

© 2015 Society for Simulation in Healthcare