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Two Unique Patients Means Double the Need for Simulation

The Continuum of Care

Women in the United States are more likely to die during childbirth or from pregnancy-related causes than women in any other developed country.1 In fact, 700 women die each year in the U.S. as a result of pregnancy and delivery complications.2 And, over 60% of these deaths are preventable.3

The most common factors contributing to a new mother’s death are:4

  • Patient/family factors (e.g. lack of knowledge about warning signs)
  • Provider factors (e.g. misdiagnosis and ineffective treatments)
  • System of care factors (e.g. lack of coordination between providers)

Each maternal death is a tear in the community fabric – a child without a mother, parents without a daughter, and partners without their other half.

David Goodman, PhD, Maternal Health Team, U.S. Centers for Disease Control & Prevention (CDC) *

Also, just as a woman’s age and lifestyle can affect her ability to get pregnant and have a healthy pregnancy, they can also influence how smoothly the delivery goes. For example, even though smoking has decreased overall, 1 out of every 14 women in the United States still smokes during their pregnancy.5  This can lead to birth defects, and can cause a baby to be born too early or to have a low birth weight – all of which put the mother and baby at risk. The lack of proper prenatal care can ultimately exacerbate a high-risk pregnancy and leave both patients vulnerable during the delivery.

In the U.S., approximately 25% of women do not receive any prenatal care in the first trimester.6 When a woman begins to receive prenatal care is largely affected by her race, ethnicity, economic status, and level of maternal education.7 This delay or altogether lack of prenatal care can directly translate into a need for emergency care.


Simulation training can better prepare healthcare professionals to react if and when an obstetric emergency occurs.8 One study found that simulation-based training for eclampsia management improved knowledge, performance, and confidence levels.9 This type of training can be particularly beneficial for obstetricians and labor and delivery nurses to fine-tune their teamwork skills in an emergency. A separate study found that simulation training for interdisciplinary team members improved inter-team communication as well as the communication with the family during actual deliveries.10

Training for a delivery is essential for a team of healthcare professionals because, unlike other medical arenas, there are two (or sometimes more) patients to monitor closely and simultaneously. Any decline in the mother’s health will impact the baby – and vice versa. Simulation can help to prepare learners to manage a safe delivery and reduce the risk of maternal and infant mortality. 

Read the next article in this series to learn how certain risk factors can also play into post-natal simulation scenarios.


  1. Centers for Disease Control & Prevention. (2018). Pregnancy-related deaths. Retrieved from
  2. Ibid
  3. McGowan, K. (2018). New report explores why preventable maternal deaths continue to occur in the United States. Maternal Health Task Force. Retrieved from
  4. Centers for Disease Control & Prevention. (2018). Building U.S. Capacity to Review and Prevent Maternal Deaths. Retrieved from
  5. Howard, J. (2018). 1 in 14 women still smokes while pregnant, CDC says. CNN. Retrieved from
  6. U.S. Department of Health & Human Services. (2016). Births: Provisional data for 2016. Retrieved from
  7. Ibid
  8. Deering, S. & Rowland, J. (2013). Obstetric emergency simulation. Seminars in Perinatology, 37(3), 179-88. DOI: 10.1053/j.semperi.2013.02.010
  9. Kolmogorova, E., Wright, D.,  Taneja, M., Marko, E., & Nieves, K. (2017). The effectiveness of simulation training in the management of eclampsia. Obstetrics & Gynecology. DOI: 10.1097/01.AOG.0000514386.27179.3c
  10. Dadiz, R., Weinschreider, J., Schriefer, J., Arnold, C., Greves, C.D., Crosby, E.C., et al. (2013). Interdisciplinary simulation-based training to improve delivery room communication. Simulation in Healthcare, 8(5), 279-291. DOI: 10.1097/SIH.0b013e31829543a3.

* McGowan, K. (2018). See reference #3.