Abstract:
Induction of Labour (IOL) is an important practice that is carried out commonly in
modern day obstetrics. In medium to large healthcare facilities in Sri Lanka, it is
estimated that approximately 35.5% of all deliveries involve IOL. This research
attempts to identify the factors that affect IOL and to assess the association between
IOL and the pregnancy outcome. In this study, we considered 18309 women who were
admitted to 14 healthcare facilities for delivery in 3 randomly selected provinces in Sri
Lanka (Western, Southern and Eastern provinces), during July to October 2011.
Multinomial Logistic Regression model (MLR) and Fuzzy Expert System (FES) were
used to identify the factors that lead to IOL.
The MLR model predicts IOL with a classification rate of 65.5% and the FES predicts
IOL with an accuracy of 55.10%. 1Maternal age, number of previous caesarian sections,number of previous births, estimated gestational age, Pre-Eclampsia, number of previous
pregnancies, Placenta Preavia, Abruption Placenta, total number of neonates delivered, birth weight and Maternal Severity Index (MSI) were identified as factors associated with IOL. Neonatal status after seven days of life can also be predicted using the developed FES. FES is predictive of IOL and birth outcome, where if the FES score is between 0.8570 and 0.8854, the patient will belong to the induced group and the baby would be alive after seven days of birth.
This study concludes that, MLR and FES models can be used to predict IOL outcomes. These findings can be informative to healthcare providers when counselling women for labour induction and develop evidence-based protocols on IOL.
