OBJECTIVE: To identify the groups of women who are the largest contributors to the cesarean section rate at a maternity facility in South East Queensland, Australia. Examining the characteristics of these women will allow the development of unit-focused initiatives aimed at reducing
cesarean sections in these groups of women. METHOD: A modified version of the Robson Ten Group Classification System was identified as the most appropriate tool to determine cesarean section rates in different groups of women. A prospective clinical audit was then carried out during
a 6-month period in 2010 using the tool. FINDINGS: The Robson Ten Group Classification System identified that planned repeat cesarean section was the largest contributor to the cesarean rate. This was followed by women having their first baby, women having an induction, and women
who have a breech presentation at term. CONCLUSIONS AND IMPLICATIONS: The Robson classification tool was useful in identifying groups of women at risk of a cesarean section. Unit-specific strategies can now be developed and implemented in an effort to lower the rate. These include
increasing the vaginal birth after cesarean rate, the uptake of external cephalic version, supporting nonintervention birth environments, and implementing models of care where clinicians are skilled in facilitating normal birth. The value of using such a tool is the ability to monitor change
over time as well as facilitating the comparison of data between units of a similar nature.
The International Journal of Childbirth is a peer-reviewed, quarterly journal publishing original research, reviews, and case studies concerned with the practice of midwifery, women's health, prenatal care, and the birth process. The journal encourages the exploration of the complex and contextual issues surrounding childbirth provision and outcomes and invites manuscripts from a wide range of clinical, theoretical, political, methodological, psychological, public health, policy, and multicultural and interdisciplinary perspectives.