Developing and validating a Bayesian Network for predicting postpartum haemorrhage

This thesis presents the development and validation of a Bayesian Network for the prediction of postpartum haemorrhage, incorporating literature, perinatal data, and expert knowledge for use as a clinical decision support tool. The setting for this research is Victoria, Australia. The thesis approaches prediction of postpartum haemorrhage from a midwifery lens, and the work also involved interviews of women on their understanding, needs and preferences when discussing risk of haemorrhage.