Pre-eclampsia, a complex and multi-system disorder specific to pregnancy, is a leading cause of preventable maternal and perinatal deaths in low-resource settings. Early detection and appropriate intervention with management of hypertension, prevention of eclampsia and timely delivery are effective at reducing mortality and morbidity. Outcomes can be greatly improved with the provision and uptake of good quality care. Cultural contexts of maternal care, social practices and expectations around pregnancy and childbirth profoundly shape understanding and prioritisation when it comes to seeking out care. Few studies have addressed health education specifically targeting pre-eclampsia in low resource settings. The existing literature has limited descriptions of contextual barriers to care or of the intervention development processes employed. More engaging, holistic approaches to pre-eclampsia education for women and families that recognise the challenges they face and that support a shared understanding of the disorder, are needed. We describe our experience of developing a Theory of Change (ToC) as part of the co-production of educational resources for pre-eclampsia in Haiti and Zimbabwe.
Early warning systems involve the routine monitoring and recording of vital signs or clinical observations on specifically designed charts with linked escalation protocols. Meeting criteria for abnormal physiological parameters triggers a color-coded or weighted scoring system aimed to guide the frequency of monitoring, need for, and urgency of clinical review. Color-coded systems trigger a clinical response when one or more abnormal observation is recorded in the red zone or two or more mildly abnormal parameters in the amber zone. The principle of maternity-specific early warning systems to structure surveillance for hospitalized women is intuitive. The widespread use and policy support, including recommendations following confidential enquiries and from the National Health Service Litigation Authority, is not, however, currently backed up by a strong evidence base. Research is required to develop predictive models and validate evidence-based maternity-specific early warning systems in the general maternity population.
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